Дисертації з теми "Smarth energy"

Världens energibehov förväntas ökar samtidigt som miljökraven blir allt hårdare. För att komma till rätta med klimatförändringarna och utsläppen av växthusgaser måste användningen av fossila bränslen minska samtidigt som energieffektiviseringar och förnybara energikällor måste öka. En större andel intermittenta förnybara energikällor på elmarknaden medför utmaningar. Finns det inget elbehov då det exempelvis blåser eller när solen skiner går den producerade elen förlorad, detta leder till att produktion och konsumtion av elektricitet måste ske samtidigt. För att förnybar energi ska kunna expandera men också effektiviseras måste samhället utveckla smarta elnät. Det finns olika uppfattningar vad som krävs för att skapa smarta elnät men elektrisk energilagersystem återkommer ofta i litteraturen. Det finns forskare som anser att satsning på intermittenta förnybara energikällor inte är ett alternativ om inte energin går att lagra. Compressed air energy storage är ett energilager som använder komprimerad luft för att lagra energin tills det finns ett behov. Industrin i Sverige står för drygt en tredjedel av den totala energianvändningen. Över 90 % av tillverkningsindustrin använder tryckluft. Det finns stora och små förbrukare av tryckluft beroende på användningsområde.  I denna studie kommer en internationell nulägesbeskrivning ges i utvecklingen av smarta elnät med fokus på elektriska energilagersystem. Syftet är att studien ska vara ett diskussionsunderlag, en informationsbärare och idéskapare. Den internationella nulägesbeskrivningen baseras på studiebesök, litteratursammanställning samt intervjuer. Resultatet från den internationella nulägesbeskrivningen visar att intresset för elektriska energilagersystem ökar då det är en central del i utvecklingen av smarta elnät.  Mellan 2011-2013 ökade investeringarna i elektriska energilager med 521 %. En anledning till denna ökning är den internationella trenden med microgrids och mindre decentraliserade kraftverk. Med ökad efterfrågan på energilagringssystem kommer nya energilagringssystem skapas och befintliga system utvecklas. Syftet med studien är även att undersöka om energilager är en lösning till hållbar tryckluftsförsörjning inom industrin. Målet är att dimensionera ett luftningssystem bestående av vindkraftverk och energilager, med en viss volym och maxtryck, för en stor- och liten tryckluftsförbrukare. I studien kommer även kostnadsbesparingen för den stora förbrukaren optimeras genom arbitrage. Dimensioneringen görs utifrån simuleringar i Simulink och optimering görs i MATLAB. Dimensionerat luftningssystemet för den stora tryckluftsförbrukaren består av ett vindkraftverk, ett energilager på 200 m3 med maxtryck på 10 bar. Täckningsgraden, det vill säga andelen av luftbehovet som kan täckas med vindkraft tillsammans med ett energilager, är 26 % för det dimensionerade luftningssystemet. Resultatet ger då 48 % mindre energiförbrukning, cirka 1,2 miljoner kronor i kostnadsbesparing och en miljövinning motsvarande 532 ton CO2-ekvivalenter. Kostnadsbesparing, då el köps via arbitrage, för den stora förbrukaren optimeras till maximalt 1,2 miljoner kronor. Generatorn har då en verkningsgrad på 85 % och kompressorn 90 %. Dimensionerat luftningssystemet för den mindre tryckluftsförbrukaren består av en vindsnurra, ett energilager på 20 m3 med maxtryck på 30 bar. Täckningsgraden, det vill säga andelen av luftbehovet som kan täckas med vindsnurra tillsammans med ett energilager, är 61 % för det dimensionerade luftningssystemet. Resultatet ger då 93 % mindre energiförbrukning, cirka 26 tusen kronor i kostnadsbesparing och en miljövinningen motsvarande 10,7 ton CO2-ekvivalenter. Skillnaden mellan en vindsnurra och ett vindkraftverk är att vindsnurran inte producerar el utan använder rörelseenergin direkt. Ett system bestående av energilager som drivs av energi från vinden lämpar sig bättre för ett mindre tryckluftsbehov där det går att nå upp i högre täckningsgrad. Övergången till smarta elnät är nödvändigt för att tillgodose alla aspekter av hållbar utveckling. Det är ingen del av smarta elnät som är viktigare än någon annan. En hållbar tryckluftanvändning inom industrin är en del av smarta elnät och för att göra det möjligt har energilager en avgörande roll. Nulägesbeskrivningen visar att det i dagsläget finns ett ökat intresse för EES internationellt men att det inte finns ett EES som ensamt kommer lösa integrationen av förnybar energi. Tekniken för energilagring finns idag och växer imorgon.
The world’s energy demand is expected to increase and at the same time the environmental requirements are becoming stricter. To deal with the climate change and the greenhouse gas emissions, the use of fossil fuel need to decrease, while the energy efficiency and renewable energy production must increase. A greater share of intermittent renewable energy on the electricity market entails challenges. If there is no need for electricity when the wind is blowing or when the sun is shining the electricity is lost, this leads to production and consumption of electricity must occur simultaneously. To expand the renewable energy and make it more efficient, society must develop a smart grid. There are different opinions about what it takes to create smart grids, but electrical energy storage, EES, reappears frequently in the literature. There are even scientists who believe that investment in intermittent renewable energy sources is not an option unless energy can be stored. Compressed air energy storage is a technique that uses compressed air to store energy until there is a demand.   The Swedish industry accounts for over a third of total energy consumption in the country. Over 90 % of the all manufacturing industry uses compressed air. There are big and small users of compressed air depending on the industry.  In this study, an international status description is given in the development of smart grids with a focus on electrical energy storage systems. The aim of this study is to be an information carrier that creates discussion and new ideas. The international status description is based on field visits, literature surveys and interviews. The results from the international status description shows that interest in electric energy storage systems is increasing since it is a central part in the development of smart grids. Between 2011 and 2013 the investments increased in electrical energy storage with 521 %. One reason for this increase is the international trend of micro grids and small decentralized power plants. With the increased demand for energy storage, new energy storage systems are created and existing systems evolve. The purpose of the study is also to examine if energy storage is a solution for a sustainable supply of compressed air in the industry. The goal is to design a compressed air system consisting of wind turbines and energy storage with a certain volume and maximum pressure, for a large and a small compressed air consumer. The study will also determine the cost saving for the big users is an optimized through arbitrage. The design is based on simulations in Simulink and the optimization is done in MATLAB. The selected compressed air system for the large consumer is based on one wind turbine, energy storage of 200 m3 with a maximum pressure of 10 bar. The coverage ratio, i.e. the proportion of the air need that is covered by wind energy with energy storage, is 26 %. An investment in this system would give reduced energy consumption by 48 % leading to a cost reduction of about 1.2 million SEK and a reduced environmental impact equivalent to 532 tons of CO2-equivalents. The generator then has an efficiency of 85 %, and the compressor has 90 %. The selected compressed air system for the smaller consumer achieves a coverage rate of 61 % with the following dimensions; one windmill, energy storage of 20 m3 and maximum pressure of 30 bar. An investment in this system would give a reduced energy consumption by 93 %, leading to a cost reduction of about 26 000 SEK and a reduced environmental impact equivalent to 10.7 ton of CO2 equivalents. The difference between a windmill and a wind turbine is that the windmill does not produce electricity instead it uses kinetic energy directly. A system consisting of energy storage driven by energy from the wind is more suited for smaller air requirements where it is possible to achieve greater coverage. The transition to smart grids is necessary to be able to meet all aspects of sustainable development. There is no part of smart grids that is more important. Sustainable use of compressed air in industry is a part of smart grids and to make it possible energy storage is crucial. The international status description shows that there is a growing international interest in EES but there isn’t one EES alone that will solve the integration of renewable energy. The techniques for energy storage are existing today and are growing tomorrow.

Den länge stabila elbolagssindustrin genomgår stora förändringar. Regelverk, miljömässiga problem, framsteg inom förnybar generering och ICT har orsakat allvarliga tryck på affärsmodellerna för konventionella elbolag. Konsekvenserna på dessa elbolag är; vinstmarginalerna har minskat avsevärt, stora elkraftverk fasas ut och det finns ett stort behov av att generera investeringar för att uppfylla regulatoriska krav. På jakt efter nya affärsmöjligheter utforskar elbolag nya affärsområden så som "Smart Energy Solutions" området. "Smart Energy Solutions" utgör en växande marknad med outnyttjad potential. Uppdragsgivaren för denna rapport är det svenska elbolaget Vattenfall AB. Där uppdraget är att identifiera marknadsmöjligheter för Vattenfall "Smart Energy Solutions" för målgruppen små och medelstora företag (SME). Syftet med denna forskning har varit att undersöka anpassningen som krävs mellan organisationen, "Smart Energy Solutions" och SME marknaden. Resultaten av denna forskning användes för att föreslå en strategi för utveckling av smarta energilösningar med inriktning på SME marknaden. Vid analys av egenskaperna hos "Smart Energy Solutions" och egenskaperna hos SME konstaterandes tre resultat. "Smart Energy Solutions" identifieras som "teknisk konfiguration". SME är heterogena till sin natur och kan därför inte mötas med enhetliga lösningar. Samt det tredje resultatet, baserat på de tidigare två resultaten, en strategi för hur framgångsrika innovationen "Smart Energy Solutions" ska rikta in sig i SME marknaden.
The long-stable eletric utility industry is undergoing major transformations. Regulatory frameworks, enviromental concerns, advancements in the renewable genration and ICT have caused severe pressure on the business model of conventional electric utilites. For these utilities; profit margins have declined considerably, large generation assests are being phased-out,and there is a pressing need to generate investments to meet the regulatory requirements. In search for new business opportunities, electric utilties are exploring new business areas, Smart Energy Solutions represent an emerging market, with untapped potentials. This research was commissioned by the Swedish electric utility Vattenfall AB, to identify market opportunities for Vattenfall Smart Energy Solutions, targetting the small and medium size enterprises SMEs. The purpose of this research has been to investigate the required alignment between the organization, Smart Energy Solutions and the SMEs market; the findings were used to propose a strategy for the development of Smart Energy Solutions targeting the SMEs. Upon analyzing the characteristics of Smart Energy Solutions and the characteristics of SMEs, the finding of this research are: first, Smart Energy Solutions is identified as "Technological Configuration", second: the SMEs are heterogeneous in nature; thereby they can’t be targeted through uniform solutions, third: based on the previous two findings; and considering the organizational context; a strategy was proposed for the successful innovation of Smart Energy Solutions targeting the SMEs.

In recent years, energy crisis and climate changes have raised a significant attention globally. There’s an increasing awareness of maximising the utilisation of distributed energy resources to ease local network congestion, reduce carbon emissions and even support the grid. This thesis presents a shared energy storage system across multiple apartments to reduce investment and operation costs. Both hardware integration solution and software Cloud connected energy management system are designed and implemented. The solution has been deployed and trialled in residential building block running for two years in a pilot project. The performance of is evaluated through data analytics from the deployed systems. The business model for the above system is proposed and explored. The optimisation is enhanced with various energy services based on fuzzy logic rules to manage controllable loads and incorporate with grid tariffs are designed and evaluated. The feasibility and performance of the proposed energy services is validated through simulation platform with load and generation data profiles extracted from the deployed systems. An aggregated energy management services for apartment buildings is proposed. Business models with incentive scheme are exploited to minimise the operation cost. Its performance is conducted in case studies through various scenarios.

The increase in the energy consumption of cities forecasted for the coming years makes these urban areas tend to be representative of the energy sustainability of their countries. In this sense, on the basis of the analysis of the management model and technological development "Smart City", the objective of this Thesis is to study the scalability from buildings to country level of the reduction in the energy consumption and the increase of the photovoltaic self-consumption . The contribution of this Thesis is based on its relevance in the process of energy transition towards a decarbonised economy, more specifically,in the study of the flexibilization of the functioning of the electrical system through the empowerment of the consumer. Thus ,through its six chapters ,this Thesis addresses broad research focused on identifying the relationship between energy sustainability and "Smart Cities", based on the study of active demand management and the evaluation of the technical-economic performance of buildings and cities with almost zero energy consumption. Chapter 1 serves as a preface to the research of the Thesis describing the relationship between the study of climate change, energy sustainability and the energy transition under the "Smart City" concept. In Chapter 2,"Contribution of Cities to Transition and Energy Sustainability" presents an analysis of the relationship between both concepts. The main contribution of this chapter is the presentation of the hypothesis of the representativeness of the energy sustainability of cities in the energy sustainability of their countries. In Chapter 3, "Electricity strategic conservation through Smart Meters and Demand Side Response: A review", the contribution of the consumer to the flexibilization of the operation of the electrical system is studied. Based on a systematic review of references ,this chapter analyzes the results of the empirical works on the reduction of electricity consumption in households through the feedback of energy information. Chapter 4,"A model for an economic evaluation of energy systems using TRNSYS", contributes with the description and validation of the economic calculation methodology of a model proposed to evaluate "Nearly Zero Energy Buildings " and distributed generation systems. Continuing with this contribution, in Chapter 5 "Economic evaluation of Nearly Zero Energy Cities", the economic evaluation model is applied to a simulation model of the energy performance of the urban energy self­ consumption, performance which is based on the distribution of energy among consumers, prosumers and energy producers and the increase in the consumption of local renewable energy resources to the detriment of the consumption of external sources. Both of these two Chapters 4 and 5 were published in the scientific journal Applied Energy (Q1). Finally,Chapter 6 presents the conclusions of the research, highlighting among them that to maintain the balance of the security of electricity supply,equity in access to energy and environmental sustainability of the city-country, the evaluation of energy sustainability should be addressed from the effectiveness of the electric systems of "Smart Cities". The research covered in this Thesis opens the possibility of addressing the following three research works in the future. 1) Designing a methodology to assess the energy sustainability of cities, which links the evaluation of the effectiveness of "Smart Energy Systems" with the evaluation of local and national climate targets. 2) Expanding the application of the "Nearly Zero Energy City" model to convert its results into an indicator of the flexibility of urban electrical systems. And 3) evaluating other cities in the world with this model, and including electrical storage systems and urban wind generation .
El aumento del consumo energético de las ciudades previsto para los próximos años hace que estas urbes tiendan a ser representativas de la sostenibilidad energética de sus países. En este sentido, en base al análisis del modelo de gestión y desarrollo tecnológico para áreas urbanas "Smart City", el objetivo de esta Tesis es estudiar la escalabilidad desde edificios hasta el nivel de país, de la reducción del consumo energético y el aumento del autoconsumo fotovoltaico. La contribución de esta Tesis se basa en su relevancia en el proceso de transición energética hacia una economía descarbonizada. Específicamente, en el estudio de la flexibilización del funcionamiento del sistema eléctrico a través del empoderamiento del consumidor. Así, dividida en seis capítulos, esta Tesis aborda un amplio trabajo de investigación centrado en identificar la relación entre la sostenibilidad energética y las "Smart Cities", en base al estudio de la gestión activa de la demanda y la evaluación del desempeño técnico-económico de edificios y ciudades de consumo energético casi nulo. El Capítulo 1 sirve de prefacio a la investigación de la Tesis describiendo la relación entre el estudio del cambio climático, la sostenibilidad energética y la transición energética bajo el concepto "Smart City". En el capítulo 2, "Contribution of Cities to Transition and Energy Sustainability", se presenta el análisis de la relación entre ambos conceptos . La principal contribución de este capitulo es la presentación de la hipótesis de la representatividad de la sostenibilidad energética de las ciudades en la sostenibilidad energética de sus países. En el capítulo 3, "Electricity strategic conservation through Smart Meters and Demand Side Response: A review", se estudia la contribución del consumidor a la flexibilización de la operación del sistema eléctrico. Basado en una revisión sistemática de referencias, este capítulo analiza los resultados de los trabajos empíricos sobre la reducción del consumo eléctrico en los hogares a través de la retroalimentación de la información energética. El Capítulo 4, "A model for an economic evaluation of energysystems using TRNSYS", contribuye con la descripción y validación de la metodología de cálculo económico de un modelo propuesto para evaluar "Nearly Zero Energy Buildings" y sistemas de generación distribuida. Continuando con esta contribución, en el capítulo 5 "Economic evaluation of Nearly Zero Energy Cities", el modelo de evaluación económica es aplicado a un modelo de simulación del desempeño energético del autoconsumo energético de ciudades. Desempeño el cual, se basa en la distribución de energía entre consumidores, prosumidores y productores de energía, y el aumento del consumo de recursos energéticos renovables locales en detrimento del consumo de fuentes externas. Cada uno de estos dos capítulos 4 y 5, fue publicado en la revista científica Applied Energy (Q1). Finalmente, el capítulo 6 presenta las conclusiones de la investigación, destacando entre ellas que para mantener en equilibrio la seguridad del suministro eléctrico, la equidad en el acceso a la energía y la sostenibilidad ambiental del binomio entre ciudad y país, la evaluación de la sostenibilidad energética debe abordarse desde la efectividad de los sistemas eléctricos de las Smart Cities. La investigación cubierta en esta Tesis abre a la posibilidad de abordar los siguientes tres trabajos de investigación en el futuro. 1) Diseñar una metodología para evaluar la sostenibilidad energética de las ciudades que vincule la evaluación de la efectividad de "Smart Energy Systems" con la evaluación de objetivos climáticos locales y nacionales .2) Ampliar la aplicación del modelo "Nearly Zero Energy Cities" para convertir sus resultados en un indicador de la flexibilidad de los sistemas eléctricos urbanos. Y 3) evaluar con este modelo otras ciudades del mundo,

Smart energy cities have a potential to lead the transition from fossil age into the age of renewables. After a theoretical background is presented, of why the transition is necessary and what steps need to be taken in that direction, this paper brings insight into the paradigm of smart cities. The focus is set on the smart building as its fundamental building block. Fifteen cases of turning Norwegian and Croatian households into smart ones have been analyzed. Those are various combinations of consumption, generation and storage options. Expenses and revenues in case of implementing such smart households are presented by conducted cost and benefit analysis, as well as profitability of such projects.This assignment is realized as a part of the collaborative project "Sustainable Energy and Environment in Western Balkans" that aims to develop and establish five new internationally recognized MSc study programs for the field of "Sustainable Energy and Environment", one at each of the five collaborating universities in three different WB countries. The project is funded through the Norwegian Programme in Higher Education, Research and Development in the Western Balkans, Programme 3: Energy Sector (HERD Energy) for the period 2011 - 2014.

The increasing price of fossil fuels, coupled with the increased worldwide focus on their contribution to climate change has driven the need to develop cleaner forms of energy generation. The transition to cleaner energy sources has seen a much higher penetration of renewable sources of electricity on the grid than ever before. Among these renewable generation sources are wind and solar power which provide intermittent and often unpredictable energy generation throughout the day depending on weather conditions. The connection of such renewable sources poses problems for electricity network operators whose legacy systems have been designed to use traditional generation sources where supply can be increased as required to meet demand. Among the solutions proposed to address this issue with intermittency in generation are storage systems and automation systems which aim to reduce demand in order to match the available renewable generation. Such a transition would introduce a requirement for more advanced technology within homes to provide network operators with greater control over domestic loads. Another aspect to the transition towards a low-carbon society is the change that will be required to domestic heating systems. Current domestic heating systems largely rely on Natural Gas as their fuel source. In order to meet carbon reduction targets, changes will need to be made to domestic buildings including insulation and other energy efficiency measures. It is also possible that present systems will begin to be replaced by new heating technologies such as ground and air source heat pumps. Due to the effect that such technological transitions will have on domestic end-users, it is important that these new technologies are designed with end-users in mind. It is therefore necessary that software tools are available to model and simulate these changes at the domestic level to guide the design of new systems. This thesis provides a summary of some of the existing building energy analysis tools that are available and shows that there is currently a shortcoming in the capabilities of existing tools when modelling future domestic smart grid technologies. Tools for developing these technologies must include a combination of building thermal characteristics, electrical energy generation and consumption, software control and communications. A new software package was developed which allows for the modelling of small smart grid systems, with a particular focus on domestic systems including electricity, heat transfer, software automation and control and communications. In addition to the modelling of electrical power flow and heat transfer that is available in existing building energy simulation packages, the package provides the novel features of allowing the simulation of data communication and human interaction with appliances. The package also provides a flexible framework that allows system components to be developed in full object-orientated programming languages at run time, rather than having to use additional third-party development environments. As well as describing the background to the work and the design of the new software, this thesis describes validation studies that were carried out to verify the accuracy of the results produced by the package. A simulation-based case study was also carried out to demonstrate the features offered by the new platform in which a smart domestic energy control system including photovoltaic generation, hot water storage and battery storage was developed. During the development of this system, new algorithms for obtaining the operating point of solar panels and photovoltaic maximum power point tracking were developed.

The link between fossil generated electricity for home energy use and climate change means that the ever‐rising residential energy requirements contribute significantly to the greenhouse gas emissions and therefore household demand also has a negative impact on the environment. As a result, home energy management has gained significant attention over the years. The anticipated incentive to the home energy user is household energy cost reduction while the network operator gains from peak demand reduction. Effective Demand Response (DR) programs in the form of Smart Home Energy Management systems have the potential to fulfill both the consumer’s and network operator’s expectations. This project analyses the challenges of DR and the effects of incorporating local Renewable Energy (RE) generation to a domestic installation with the aim of turning the household into an energy neutral home whose net annual energy consumption is almost zero. Power demand and the consumption characteristics of households through common household appliances were investigated using smart meters and the associated load profiles. Some of Synergy’s Western Australian (WA) electricity retail tariffs were analysed and applied to the load profile downloads to verify the cost benefits of tariff shopping, standby mode elimination and load shifting. The Homer Pro micro grid analysis tool was used to investigate the possibility of turning a Perth household into an energy neutral home by attempting to match its possible loading with the most viable solar generation system. The results show that the Power Shift (PS1) tariff was the cheapest with a 1.44% cost reduction from the Home plan (A1) project base plan. The cost reduction analysis was performed by applying the House 1 June load profile to all the tariffs considered in this investigation. The research results show that it is possible to achieve an energy neutral home in WA although this would be accompanied by high costs and regulatory restrictions. This thesis project found that about 96% renewable fraction is achievable to typical WA households within reasonable technical, economic and regulatory considerations.

Der KOMKIS Report fasst die Ergebnisse einer Kurzstudie zusammen, die methodisch mit Hilfe eines teilstandardisierten Leitfadeninterviews mit Experten zu Smart Metering im kommunalen Kontext geführt wurde. Ziel war es, explorativ erste Einschätzungen für den aktuell erfolgenden Smart Meter Rollout für Kommunen in Sachsen zu erhalten. Ei-nerseits ist das Ergebnis, dass ein erneuter Strukturwandel in der Stromwirtschaft be-vorsteht, der jedoch aus Sicht der Experten noch offen für die einzelnen Marktakteure ist. Andererseits ist klar, dass sowohl das kommunale Energiemanagement als auch die kommunalen öffentlichen Unternehmen in der Energiewirtschaft mit neuen Chancen und Risiken konfrontiert sind, die es zu gestalten gilt.

A smart grid is an electricity network that accommodates two-way power flows, and utilizes two-way communications and increased measurement, in order to provide more information to customers and aid in the development of a more efficient electricity market. The current electrical network is outdated and has many shortcomings relating to power flows, inefficient electricity markets, generation/supply balance, a lack of information for the consumer and insufficient consumer interaction with electricity markets. Many of these challenges can be addressed with a smart grid, but there remain significant barriers to the implementation of a smart grid.

This paper proposes a novel method for the development of a smart grid utilizing a bottom up approach (starting with smart buildings/campuses) with the goal of providing the framework and infrastructure necessary for a smart grid instead of the more traditional approach (installing many smart meters and hoping a smart grid emerges). This novel approach involves combining deterministic and statistical methods in order to accurately estimate building electricity use down to the device level. It provides model users with a cheaper alternative to energy audits and extensive sensor networks (the current methods of quantifying electrical use at this level) which increases their ability to modify energy consumption and respond to price signals

The results of this method are promising, but they are still preliminary. As a result, there is still room for improvement. On days when there were no missing or inaccurate data, this approach has R² of about 0.84, sometimes as high as 0.94 when compared to measured results. However, there were many days where missing data brought overall accuracy down significantly. In addition, the development and implementation of the calibration process is still underway and some functional additions must be made in order to maximize accuracy. The calibration process must be completed before a reliable accuracy can be determined.

While this work shows that a combination of a deterministic and statistical methods can accurately forecast building energy usage, the ability to produce accurate results is heavily dependent upon software availability, accurate data and the proper calibration of the model. Creating the software required for a smart building model is time consuming and expensive. Bad or missing data have significant negative impacts on the accuracy of the results and can be caused by a hodgepodge of equipment and communication protocols. Proper calibration of the model is essential to ensure that the device level estimations are sufficiently accurate. Any building model which is to be successful at creating a smart building must be able to overcome these challenges.

As the world seeks to transition away from fossil fuel technologies, there has been a driving market for the safe and smart consumption of electricity. Effective energy usage at the residential side has enormous potential for energy saving and power load balancing. This thesis presents a comprehensive study on the Home Energy Management System (HEMS) especially in the aspect of Appliance Load Monitoring (ALM) system. The study reviews the state of art of intrusive load monitoring (ILM) technology and Non-intrusive Appliance Load Monitoring (NILM), and compares their advantages and disadvantages. This paper also introduces household electrical devices modelling and HEMS scheduling strategies. Case studies showed a satisfying performance on the real time electricity price prediction and HEMS optimal scheduling models. Moreover, a low-cost smart socket based on the internet of things (IoT) for the real-time measurement of instantaneous power during the operation of home appliances was designed and fabricated. The experimental results showed the designed smart socket can be fully utilized for monitoring and controlling home electrical devices. Finally, a residential load monitoring algorithm based on bidirectional long short-term memory (BLTSM) has been proposed for electrical load identification. Through experimental demonstrations, the performance of the proposed BLSTM can achieve more than 90% load identification accuracy which is shown to be higher than five commonly used benchmark algorithms in the literature. Moreover, the power history curves of five common household appliances can be accurately identified during vastly different operational states demonstrating the robust and accurate performance of this innovative smart socket. Furthermore, a minor cost analysis versus load identification accuracy validates the reduced cost using the innovative 3D printed smart socket and BLSTM proposed in this work.

Renewable energy connection to power systems has been growing worldwide, which brings more challenges to power systems than ever before and correspondingly, the investment in wind farms is increasing rapidly. Instead of connecting single wind turbines or small wind farms to the distribution network, energy companies and manufactures tend to connect large wind farms to the transmission network. These wind farms can contain 200 plus turbines and have a rated capacity of 100 MW up to several GW. Consequently, significant new challenges appeared in the transmission system. Wind intermittency is one of the biggest issues in power systems in that it affects both frequency and system power flow. This project has focused on the transmission system power flow issue that was caused by wind intermittency, and defined it as Wind Intermittency Constraint (WIC). To avoid studying the whole system, WIC was used as a new method in this project to calculate and identify the problematic circuits that were caused by wind intermittency only. These circuits will be calculated in the Power Transfer Distribution Factor (PTDF) method, which is the key part of WIC calculation, and will be defined as WIC. WIC for each circuit in transmission system will be ranked, and circuits with higher WIC ranking over 20% are wind intermittency circuits and will be closely monitored. Smart grid technology has been considered as an effective way to improve system visibility and controllability when attempting to overcome difficulties caused by renewable energy. There are three major parts for this project, which are flexible demand mechanism, generator participation and Flexible AC Transmission (FACTs) equipments. To have a more accurate FACTs control and calculation for wind intermittency only, this project uses a new concept of DI (Dynamic Impedance) to contribute to the controller algorithm. A novel algorithm has been introduced to build three controllers of demand, generation and impedance. To achieve different goals, these three controllers will take instruction from the central selector. The three goals identified in this project are economical, green and secure functions, where economical function is to minimise system cost during different wind scenarios, green function is to maximise system renewable energy output, and security function is to make sure the system is secure when it minimizes cost and maximizes renewable energy. The algorithm will also calculate different wind scenarios and produce a 24 hour profile for system demand, generation and impedance. This profile will be achieved by the three controllers (Demand, generation and impedance controller) A new model for wind scenarios is also used in this project which is called A to B model. It calculates a continuous 24 hour wind profile and find out the system stress points. These points are define as A and B. The controller algorithm will download wind scenario and calculate the best strategy to move from period A to period B. During the A to B process, cost, green and security factors are considered and the best strategy will be presented. 6-node, 9 nodes and 39 nodes IEEE standard models are used across the project to prove the concept of WIC (Wind Intermittency Constraint), DI (Dynamic Impedance), A to B wind profiles and controller algorithm. A simplified UK model has also been used to test real weather data and produce the best strategy to achieve economical, green and security goal. For thermal and voltage study, standard IEEE models are used. For stability study, a dynamic model is used to monitor rotor angle.

The impact of distributed energy resources (DERs), electric vehicles/plug-in hybrid electric vehicles (EVs/PHEVs), and smart appliances on the distribution grid has been expected to be beneficial in terms of environment, economy, and reliability. But, it can be more beneficial by implementing smart controls. In the absence of additional controls, a negative effect was identified regarding the service lifetime of power distribution components. This research presents a new class of a smart house energy management system that can provide management and control of a residential house electric energy without inconvenience to the residents of the house and without overloading the distribution infrastructure. The implementation of these controls requires an infrastructure that continuously monitors the house power system operation, determines the real-time model of the house, computes better operating strategies over a planning period of time, and enables control of house resources. The smart house energy management system provides benefits for the good of utility and customer. In case of variable electricity rates, the management system can reduce the customer’s total energy cost. The benefits can be also extended to provide ancillary services to the utility such as control of peak load and reactive power support– assuming that this is worked out under a certain mutually beneficial arrangement between the utility and customer.

Mitigating climate change lies to a large part within the Energy System. In order to make it sustainable and efficient, policies have to be framed accordingly. This study focuses on formulation of policies based on future projections of the energy demand in Oskarshamn municipality of Sweden. Oskarshamn is a former industrial municipality, whose economic activity is in decline and it requires policies that accelerates its growth. It is also stereo-typical of much of Europe, as industrial activities are transferred elsewhere and regions are left to re-invent themselves. Questions such as “how to make the existing system more efficient” and “what is the best energy saving alternative”, have to be answered. For which, Long range Energy Alternatives Planning (LEAP) tool is used to create scenarios based on different pathways and to project the energy demand in the future. The business as usual scenario is compared with mitigation scenario considering various energy efficiency measures. The measures mainly focus on Demand Side Management and improving energy lifestyle interactions. Examples include the impact of electric vehicles (EV) in the transport sector and effects of better insulation in residential buildings, etc. Nuclear is currently the main source and would possibly be phased out in the horizon and thus creating a need for alternative and sustainable sources of energy. The renewable energy scenario focuses on proposals for mixing renewable fuels in the energy supply side. These are not without costs and opportunities which are discussed in the study. The outcomes work a clear delineation of Greenhouse gas mitigation options, which in collaboration with the municipality would form the basis for a policy action plan.

Utility providers are under constant pressure to meet the ever-increasing demand for energy with a finite production capacity. Due to this, utility providers need to ensure that the demand does not exceed the supply. The use of demand response programs has been used as a solution to better match the available supply to the demand experienced on the grid. While demand response programs may improve the relationship between the supply and the demand, increasing consumer participation can further improve the effectiveness of demand response programs. The level of consumer participation is highly dependent on the incentives offered and the convenience of participating in the demand response program. However, most of these programs require consumers to actively monitor the available services and take appropriate action on their appliances. Home energy management systems attempt to provide convenience to consumers as well as increase their participation in demand response programs. They do this by enabling autonomous control and remote control of appliances. In addition, a home gateway makes it possible for the consumer and utility provider to interact with devices in the home remotely. Current solutions host the home energy management software on a home gateway or on a dedicated device in the home. Furthermore, these systems make use of proprietary software and devices to monitor and control the home environment. However, proprietary systems are costly to implement and maintain due to their dependence on the developers and the varying needs of consumers. This dissertation proposes a home energy management system solution that makes use of a standardized distributed machine-to-machine (M2M) middleware framework to support heterogeneous devices, technologies and protocols. In addition, the proposed solution shifts the software logic of the home energy management system from the gateway to a private cloud. This allows the system to leverage the benefits of virtualization and cloud computing such as cost efficiency, faster deployment and easier maintenance of the system. The proposed solution was implemented using a European Telecommunications Standards Institute (ETSI) compliant distributed M2M middleware framework (i.e. OpenMTC) and an open-source private cloud platform (i.e. OpenStack). A prototype was developed and tested with demand response programs that included a control demand response (DR) service, a consumption monitoring service and a time-of-use (ToU) service. In addition, the prototype made use of various third party applications, protocols and devices to support the aforementioned demand response services and provide automated and remote control of home appliances. Finally, an evaluation of the proposed system was conducted and concluded that the number of home energy management systems subscribed to the defined services influenced the effectiveness of these services because of the additional processing that the utility provider is required to perform.

The present thesis is devoted to synthesis, through the environmentally friendly citrate sol-gel route, of YIn0.9O3 −ZnO near infrared reflective based pigments, having different chromophore elements (Mn, Cu, Fe), with the aim to add in binder and obtaining cool coatings. A “cool” coating for roofing consists of paint (or glaze) containing color pigments, which do not absorb the infrared portion of the solar spectrum. Cool coatings applied over buildings surface provide an effective solution for passive cooling of building indoors and influencing local outdoor microclimate, mitigating urban heat islands effect (UHIE). The primary purpose is to produce pigments according to an environmentally friendly route, using non-toxic raw materials, as well as short times and low temperatures for synthesis, and without residual waste. The resulting pigments must have high reflectance in the near-infrared so that they can be used in the field of cold paints. To realize the corresponding coatings, pigments were dispersed in two different binders (standard PMMA and industrial binder). For the most interesting pigments, in terms of NIR reflectance, other property, was decided to explore, which define these NIR reflective pigments as smart pigments for building application: the photocatalytic ability.

In the European Union (EU), increasing final energy efficiency, so as to save energy, has become mandatory. This obligation will fundamentally alter the EU energy sector. The relevant EU directive, 2006/32/EG, requires that adjustments be made to energy billing and, where technically feasible, that new metering technologies (i.e. smart metering) be introduced. Individual EU countries are implementing these requirements in different ways: Smart metering is either being nearly fully implemented (e.g. in Italy), is being planned (e.g. in Germany), or completely disregarded (e.g. in the Czech Republic). Since the introduction of smart metering affects virtually all value-added steps, organisational structures and areas of operation in medium-sized energy providers, these providers must take the relevant requirements into account at as early a stage as possible. The present thesis analyses the effects of the introduction of smart metering on the business management of such companies. A deductive method was chosen and the effects of intro- ducing smart metering were assessed through a cross-sectional study of two separate data collections. Experts were interviewed and their statements were qualitatively evaluated. A written survey followed via online questionnaires, the results of which were quantitatively evaluated. Institutional, functional and activity-based perspectives were considered as well as normative, strategic and operative aspects of business management. The evaluation of the survey enabled a better assessment and analysis of the introduction of smart metering. An analysis of the scope of the upcoming alterations within energy providers illustrates just how fundamental a change this will bring to medium-sized energy providers. However, the outcome of the written survey shows that most executives do not recognise this need for change and therefore are unable to initiate it. These management deficiencies threaten the very existence of these companies and must be resolved through the timely initiation of consistent change management.

A automação já é utilizada como ferramenta para se obter a eficiência energética. Este trabalho apresenta e quantifica a potencialidade desta ferramenta com objetivo de diminuir picos de energia, diminuindo também a necessidade de construir rapidamente novas usinas geradoras de energia elétrica, regulando a transmissão e distribuição desta energia, aproveitando recursos renováveis e sustentáveis, tudo isso através de um sistema que já existe implantado em vários países do mundo e tem todas as condições de ser implementado no Brasil. Este sistema é a rede inteligente de energia ou smart grid. Analisa, também, a matriz energética brasileira, apresenta anomalias ocorridas, como apagões regionais e nacionais, verifica a necessidade de energia elétrica para o crescimento do País, propõe soluções para o sistema energético nacional utilizando inovações tecnológicas, como a implantação do sistema smart grid na matriz energética, sempre objetivando melhor eficiência e qualidade da energia, levantando o comportamento dos usuários em busca da implementação destas inovações tecnológicas. A partir de idéias que rompam os paradigmas atuais de busca de energia através de grandes obras propõe este trabalho a mudança de hábito e procedimentos da população, das próprias empresas e dos órgãos públicos brasileiros buscando a diminuição da utilização da energia especialmente nos horários hoje considerados como picos, ou seja, aqueles que demandam a maior geração, transmissão e distribuição da energia utilizada. Apresenta também a necessidade de energia elétrica para desenvolvimento econômico do Brasil, agregando todas as inovações tecnológicas aos processos atuais, buscando minimizar a possibilidade da ocorrência de apagões, ocasionados por ineficiência técnica da matriz energética ou por racionamento de energia.
Automation is already used as a tool to achieve energy efficiency. This paper presents and quantifies the potential of this tool in order to reduce power surges, reducing the need rapidly build new electricity generating plants, transmission and regulating distribution of this energy, using renewable and sustainable resources, all through a system that is already deployed in several countries worldwide and has all the conditions to be implemented in Brazil. This system is the intelligent network of energy or "smart grid". It also analyzes the Brazilian energy matrix, has deficiencies occurred as a regional and national blackouts, there is need of electricity for the growth of the country, proposes solutions to national energy system, using technological innovations such as the deployment of the "smart grid" energy source, always aiming for better energy efficiency and quality, raising the behavior of users seeking the implementation of these technological innovations. From ideas that break current paradigms of seeking power through great works this paper proposes changes in the habits and procedures of the population, own businesses and public agencies are looking to decrease energy use especially in times like now considered "peaks", ie, those that demand the greatest generation, transmission and distribution of energy used. It also shows the need for electricity to Brazils economic development, adding all the technological innovations to the current processes in order to minimize the possibility of the occurrence of blackouts, caused by technical inefficiency of the energy or energy shortages.

Buildings account for approximately 40% of the energy demand and 33% of the total greenhouse gas emissions in the European Union. Accordingly, there are several efforts that target energy efficiency in buildings both at the European and Swedish levels. The role of buildings in climate change mitigation, however, is not limited to energy savings. Buildings are expected to become key elements of the future smart energy systems by supplying and using energy in a more flexible way. Reducing the energy demand in buildings effectively and shifting the role of buildings in energy systems from ‘passive’ consumers to ‘active’ prosumers, however, require close interaction and cooperation between the energy and buildings sectors. Based on the data collected from interviews and a web survey, this doctoral thesis investigates the relationship between the energy and buildings sectors in Sweden at the inter-company level, presents key stakeholder views on smart energy features in buildings and investigates the opportunities and barriers for their adoption in Sweden and Hong Kong. The results of this thesis suggest a potential for improving the cooperation between the Swedish energy and buildings sectors, which was identified to be influenced by the following factors: district heating monopolies; energy efficiency efforts in the buildings sector; unsuccessful technology-neutrality of the building regulations; self-generation systems in buildings; and energy use patterns. Shifting the focus from self-gains to mutual gains appears crucial to strengthen the inter-sectoral cooperation, as there are several opportunities for achieving mutually beneficial solutions for the two sectors. This would, however, require significant changes in current practices and business models as well as the introduction of new technologies, which would allow for a more flexible energy supply and use. Accordingly, technologies that target flexible energy use in buildings are considered the most important smart energy features in buildings. The current high costs of technologies, such as home automation and smart electrical appliances, however, create the strongest barrier to adoption. Therefore, the introduction of new business and ownership models and the elimination of the institutional and regulatory barriers are crucial to achieve a wide-scale development of smart energy features in buildings. The results from Hong Kong suggest that institutional and regulatory barriers can particularly create strong hinders to the adoption of technologies. It is possible to achieve more sustainable energy systems, where buildings are active elements of networks that supply and use energy in a more flexible and ‘smarter’ way. Cooperation between the energy and buildings sectors can play a key role in the adoption of smart energy features in buildings and pave the way for the smart built environment of the future.

Detta kandidatexamensarbete utvärderar och jämför en befintlig solcellsanläggning med installerat energilager samt en smart växelriktare i Farsta, Stockholm. Jämförelsen ställer denna anläggning mot ett konventionellt solcellssystem med enbart solceller. Studiens syfte är att identifiera mängden egenanvänd solenergi, ta fram optimeringsförslag samt belysa eventuella kostnadsbesparingar. Den smarta växelriktaren har möjliggjort datainsamling via en webbaserad användarportal, portalen loggar och sparar anläggningens energi- och effektdata.   Studien påvisar att systemet inte bidrar med en betydande ökning av egenanvändningen av solenergi, ty batteriets inställningar ofta medför att batteriet är fulladdat under dagens soltimmar. Det smarta systemets mest fördelaktiga funktion är att kapa fastighetens effekttoppar vilket skapar möjlighet till nedsäkring.   Hur stor del av effekttopparna som kan kapas är starkt beroende av batteriets inställningar. Under studien har två olika scenarier testats. Det mest essentiella är att batteriet alltid kan kapa de högsta effekttopparna samtidigt som det aldrig laddas ur helt. Nyttan maximeras när batteriet aktiveras vid förbrukningar över 24 kW. Säkringsanalyserna från studien visar att fastighetens minsta möjliga huvudsäkringar som kan brukas är 35 A, dock rekommenderas nyttjande av huvudsäkringar om 50 A då en säkerhetsmarginal är önskvärd. Den rekommenderade nedsäkringen ger möjlighet att teckna ett billigare elavtal. Slutsatsen är att säkringsabonnemanget TID relativt effektabonnemanget L0,4S ger en kostnadsbesparing om 33 547 kronor per år.
This bachelor thesis is evaluating and comparing an existing photovoltaic system including an energy storage and a smart bidirectional converter in Farsta, Stockholm. This smart system will be compared with a conventional PV plant. The aim of the report is to identify the amount of self-consumed solar energy, give optimizing suggestions and shed light on possible cost savings. The smart converter has given the possibility to collect data from a web-based portal. The portal logs and stores the energy and power data of the system.   The study proves that this smart system does not contribute with an increased amount of self-consumed solar energy, since the battery settings implies a fully charged battery during the day. The most advantageous benefit in the smart system is to cut power peaks, which gives opportunities to use smaller main fuses in the real estate.   The magnitude of the power peaks that can be reduced is depending on the settings of the battery. Two different scenarios have been examined in the study. The most essential is that the battery is always able to cut the highest power peaks without being fully discharged. The maximum utility occurs when the battery is activated when the consumption is higher than 24 kW. Fuse analysis proves that the lowest possible main fuses that could be used in the real estate is 35 A. Though, this study recommends main fuses of 50 A since a safety margin is desired. This gives opportunities to sign a more beneficial electricity contract. Conclusively, the fuse rating contract that can be used is 33 547 SEK cheaper per year than the power rating contract that is used in the real estate today.

Orientador: Gilberto De Martino Jannuzzi
Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica
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Resumo: Este trabalho parte da premissa que as tecnologias para smart grid se apresentam como oportunidade para criar um novo negócio de energia. Todos os stake-holders devem ser envolvidos, e organizados para construir ou modernizar a rede de energia em seus aspectos de qualidade, disponibilidade, infraestrutura, padronização, interoperabilidade, confiabilidade e sustentabilidade. Deve-se também buscar a consciência de uso/demanda, de renda e de entendimento dos clientes de forma adequada. Pondera-se que as estratégias governamentais, no âmbito da legislação e da regulamentação, devem ser objetivas para garantir o novo negócio e proteger o interesse público. Os consumidores (como clientes) devem ser ouvidos, tornando-se partícipes ativos no mercado de energia. Com o desenvolvimento de um relacionamento dinâmico a indústria de energia necessitará de novas condições e requisitos operacionais que devem ser criados para garantir a transformação dentro e fora do ambiente de negócios regional. Foram estudadas novas tecnologias, novas possibilidades de serviços e preços. Incentivos, bem como a evolução das normas regulatórias apareceram como fundamentais para manter e expandir o fornecimento da energia e gerenciar a demanda, com implicações na melhora do relacionamento e nos investimentos/receitas para o capital investido, que necessitam resultar na ampliação da percepção de valor da energia pelos clientes. Uma avaliação para o caso brasileiro é feita considerando-se a experiência internacional até a data e através de exemplo de aplicação em consumidores residenciais como um estudo de caso. Demonstra-se o impacto para e do consumidor doméstico nos processos de uso da energia, bem como a evolução necessária de sistemas, estratégias para que se alcance o desejado momento histórico do desenvolvimento, da reorganização do mercado de energia e da legislação/regulamentação. Em suma, a evolução do negócio de energia no Brasil é um fato que, para sua eficácia, deve ser estrategicamente planejado nos diversos âmbitos de aplicação de tecnologias e modelagem do negócio, receber incentivos e ser regulado. Questões relacionadas aos investimentos a serem realizados e o retorno destes investimentos devem ser respondidas caso a caso, segundo a realidade regional das concessões, segundo as previsões de compartilhamento de custos com os consumidores e também totalmente relacionadas com a regulamentação adotada. A possiblidade da oferta de serviços e produtos para atendimento e ampliação do espaço de atuação das concessionárias brasileiras é uma transformação necessária para seu reconhecimento como provedoras de soluções energéticas.
Abstract: The smart grid technologies present themselves as opportunities to create new energy business. All stake holders must be involved, organizing, building and upgrading the power grid in its aspects of quality, availability, infrastructure, standards, reliability, interconnectivity, and sustainability. It is necessary the awareness target of supply-demand, incomes and strongly understand their clients. The Governmental strategies must be clear, with regulatory and legislative initiatives to foster new business and protect the public interest. Consumers (as clients) must be heard, as they become active players in the energy market. As they develop a dynamic relationship with the operating power industry new conditions and requirements need to be created in order to lead the strategic transformation inside and outside regional businesses. Deals on new energy sources, new technologies, new possibilities of differentials service and prices were studied. Incentives as well as the evolution of regulation rules seem a fundamental role to maintain and to expand the power supply and demand-side management, with implications for a better relationship between client-consumers, dealers and incomes/revenues on invested capital. It is also important to relate and to rethink the affordability of the tariffs and energy delivery costs to clients. An evaluation to the Brazilian market was done, considering the up to date international experiences and running an application, specially built to demonstrate the domestic consumption, as a case study. This implemented case is presented in order to demonstrate the domestic consumer impact to the energy use as well as the required evolution of systems and strategies to move on to this historical moment of development and reorganization of the energy market as well as the legislation/regulation. To sum up, evolving energy business in Brazil does not appear in this analysis merely as a possibility but as fact to be accomplished. It should be strategically planned considering the scope of a number of different technology applications, business models and be promoted by the policies agencies. Questions related to investments and their profits should be answered according to the regional energy business, as well as the consumer's participation and obviously new legislation and market regulation. Services and products to be offered by the Brazilian energy dealers should evolve correspondingly in order to improve business and recognition as energy solution providers
Doutorado
Planejamento de Sistemas Energeticos
Doutor em Planejamento de Sistemas Energéticos

With the widespread adoption of smart meters in buildings, an unprecedented amount of high- resolution energy data is released, which provides opportunities to understand building consumption patterns. Accordingly, research efforts have employed data analytics and machine learning methods for the segmentation of consumers based on their load profiles, which help utilities and energy providers for customized/personalized targeting for energy programs. However, building energy segmentation methodologies may present oversimplified representations of load shapes, which do not properly capture the realistic energy consumption patterns, in terms of temporal shapes and magnitude. In this thesis, we introduce a clustering technique that is capable of preserving both temporal patterns and total consumption of load shapes from customers’ energy data. The proposed approach first overpopulates clusters as the initial stage to preserve the accuracy and merges the similar ones to reduce redundancy in the second stage by integrating time-series similarity techniques. For such a purpose, different time-series similarity measures based on Dynamic Time Warping (DTW) are employed. Furthermore, evaluations of different unsupervised clustering methods such as k-means, hierarchical clustering, fuzzy c-means, and self-organizing map were presented on building load shape portfolios, and their performance were quantitatively and qualitatively compared. The evaluation was carried out on real energy data of ~250 households. The comparative assessment (both qualitatively and quantitatively) demonstrated the applicability of the proposed approach compared to benchmark techniques for power time-series clustering of household load shapes. The contribution of this thesis is to: (1) present a comparative assessment of clustering techniques on household electricity load shapes and highlighting the inadequacy of conventional validation indices for choosing the cluster number and (2) propose a two-stage clustering approach to improve the representation of temporal patterns and magnitude of household load shapes.
M.S.
With the unprecedented amount of data collected by smart meters, we have opportunities to systematically analyze the energy consumption patterns of households. Specifically, through using data analytics methods, one could cluster a large number of energy patterns (collected on a daily basis) into a number of representative groups, which could reveal actionable patterns for electric utilities for energy planning. However, commonly used clustering approaches may not properly show the variation of energy patterns or energy volume of customers at a neighborhood scale. Therefore, in this thesis, we introduced a clustering approach to improve the cluster representation by preserving the temporal shapes and energy volume of daily profiles (i.e., the energy data of a household collected during 1 day). In the first part of the study, we evaluated several well-known clustering techniques and validation indices in the literature and showed that they do not necessarily work well for this domain-specific problem. As a result, in the second part, we introduced a two-stage clustering technique to extract the typical energy consumption patterns of households. Different visualization and quantified metrics are shown for the comparison and applicability of the methods. A case-study on several datasets comprising more than 250 households was considered for evaluation. The findings show that datasets with more than thousands of observations can be clustered into 10-50 groups through the introduced two-stage approach, while reasonably maintaining the energy patterns and energy volume of individual profiles.

Hybrid Energy Resource System (HERS) is studied and applied aroundworld in recent years. Control and monitor of them are quite important in realapplication. HERS also has the equirement to integral with power grid such asdistribution grid networks. Therefore, to design and implement the informationcommunication system following IEC 61850, which is most promising standard fordesign of substation communication and automation system, is necessary. This paperpresents the design of Information Communication Technology (ICT) architectureand Unified Modeling Language (UML) models and final implementation through LabVIEW programming for Smart Energy Container. Applying design following IEC61850 series standards allow the HERS can communicate and interoperate with other IEC61850 devices and SCADA systems. The implementation is applied to SmartEnergy Container which contains wind power, solar power, battery energy storagesystem, and hydrogen energy storage system. Verification and testing results shows thedesign is qualified to control and monitor Smart Energy Container.
Smart Energy Container

With the number of interconnected devices, many of which being wireless, exceeding the human population, there is a need to power resource-constrained devices through means other than disposable batteries. Harvesting ambient energy from the vicinity of the device is one solution.SKF, a producer of rolling element bearings, produces approximately one billion bearings per year. If parts of the produced bearings could be self-sucient devices powered through ambient energy, the smart integration of electronics in mechanical systems could be achieved. A scenario in which rolling element bearings are embedded with electronics is presented, through which the development of new services, data collection, data transfer and data interpretation can be realized. This scenario is the key motivation for thisthesis.This thesis presents some of the most common sources of energy used for harvesting energy in rotating environments and discusses how dierent transduction methods can convert ambient energy into electrical energy. Finding a general, robust and cost-eectivetechnology that can be applied to or in the vicinity of a rotating system is one of the main focuses of this thesis. The investigated technologies should be applicable to a dirty and encapsulated industrial environment; therefore, certain energy sources, e.g., sun light and radio frequencies, are not investigated. Advancements in vibrational energy harvesting are also presented in the form of a parameterized SPICE model of a piezoelectric vibrationharvester that can be simulated in conjunction with non-ideal and non-linear circuit models. The SPICE model is used to verify the performance of a novel energy harvesting circuit that actively extracts energy from a piezoelectric transducer. The harvesting circuit enables the enforcement of greater electrical damping on the mechanical system, thereby enabling more electrical energy to be extracted. For weak electromechanically coupled piezoelectric harvesters, the circuit can increase the power output by more than 300% compared to a full-wave rectifying bridge. The simulation results with the modeledharvester under the dened operating conditions in conjunction with the active harvesting circuit indicate that an average of more than 1 mW of power can be extracted, which is assumed to be sucient for powering a resource-constrained embedded device.
Godkänd; 2015; 20150211 (hagfre)

With increasing electricity demand and environmental concerns, utilities are looking for improved network operations and efficient energy consumption. Telecom sites with their flexible energy storage and controllable power flows have significant potential to improve reliability, efficiency, security and quality of electricity supply in the AC distribution system.Power quality events such as voltage sags, flickers and energization of power devices cause disturbances in the operational grid. Moreover, extensive use of power electronics devices requires additional reactive power from the grid and cause distortion in the source current waveforms. These power quality problems were identified both from the literature studies and measurements obtained from Sintef Energy, a research organization in Norway. Line rectifiers are being used as grid/utility interfaces for the telecom sites. In this master thesis, an idea is proposed to replace rectifiers with bi-directional AC/DC converters. Operational control schemes for up-to three converters have been developed with the help of vector control technique. These converters with the battery banks on DC side; are not only capable of supplying power for telecommunication services but also of providing the possibility of voltage support, harmonics and reactive power compensation. Basic distribution network models were developed in the software package MATLAB/SIMULINK® to analyse the impact of connected telecom converters both for the voltage support and ancillary services. Simulations were performed and it was observed that the Total Harmonic Distortion (THD) was reduced to maximum 3.4%, reactive power drawn from the grid became zero and voltage dip in case of wind distributed generation rises from 83.5% to 97.5% when three Telecom sites started supporting the grid. It was also seen that with proper energy management system, Telecom sites can also support utilities by supplying active power during peak hours load demand and for islanding operation.THD level within the IEEE, IEC, EN power quality standards, compensation of reactive power and provision of voltage support prove that the efficiency of a network can be improved by properly implementing Smart Grid together with the support from distributed telecom sites. Keywords:Smart Grid, power quality issues, Telecom Power Infrastructure, power electronics, voltage source converter, vector oriented control, harmonics, active and reactive power, voltage support.

The flow-induced vibration is one of the most common vibrational phenomena in the ambient environment, on which the previous studies were mainly dealing with methodologies as to how to control and reduce vibrations of objects in the flow field. Facing the growing demand of the power supply of the Internet of Things (IoT) and the Wireless Sensor Network (WSN), the energy harvesting technique utilizing multifaceted dynamic effects incurred within natural water flows is a new and meaningful area worth of further research. In this thesis, two novel strategies of the flow-induced vibration energy harvesting techniques were proposed and investigated. One is focused on the flow pattern control with the creative layouts of the bluff bodies. The other could harvest the energy from the reciprocating water flows with the utilization of the torsional vibration mode of the energy harvester. Both methods were firstly proposed and verified in this thesis. The work could not only develop the power output of the energy harvester, but also be applied in the actual hostile ambient environment. The contributions to the research provided by this thesis were made also on the optimization of the proposed topologies with numerous experimental, analytical and computational approaches. The detailed characteristics were investigated and concluded in the thesis to promote the applications of the technologies. The energy storage system was also studied and tested.

Many countries are rolling out smart electricity meters. A smart meter measures the aggregate energy consumption of an entire building. However, appliance-by-appliance energy consumption information may be more valuable than aggregate data for a variety of uses including reducing energy demand and improving load forecasting for the electricity grid. Electricity disaggregation algorithms – the focus of this thesis – estimate appliance-by-appliance electricity demand from aggregate electricity demand. This thesis has three main goals: 1) to critically evaluate the benefits of energy disaggregation; 2) to develop tools to enable rigorous disaggregation research; 3) to advance the state of the art in disaggregation algorithms. The first part of this thesis explores whether disaggregated energy feedback helps domestic users to reduce energy consumption; and discusses threats to the NILM. Evidence is collected, summarised and aggregated by means of a critical, systematic review of the literature. Multiple uses for disaggregated data are discussed. Our review finds no robust evidence to support the hypothesis that current forms of disaggregated energy feedback are more effective than aggregate energy feedback at reducing energy consumption in the general population. But the absence of evidence does not necessarily imply the absence of any beneficial effect of disaggregated feedback. The review ends with a discussion of ways in which the effectiveness of disaggregated feedback may be increased and a discussion of opportunities for new research into the effectiveness of disaggregated feedback. We conclude that more social science research into the effects of disaggregated energy feedback is required. This motivates the remainder of the thesis: to enable cost-effective research into the effects of disaggregated feedback, we work towards developing robust NILM algorithms and software. The second part of this thesis describes three tools and one dataset developed to enable disaggregation research. The first of these tools is a novel, low-cost data collection system, which records appliance-by-appliance electricity demand every six seconds and records the whole-home voltage and current at 16 kHz. This system enabled us to collect the UK’s first and only high-frequency (kHz) electricity dataset, the UK Disaggregated Appliance-Level Electricity dataset (UK-DALE). Next, to help the disaggregation community to conduct open, rigorous,repeatable research, we collaborated with other researchers to build the first open-source dissaggregation framework, NILMTK. NILMTK has gained significant traction in the community,both in terms of contributed code and in terms of users. The third tool described in this thesis is a metadata schema for disaggregated energy data. This schema was developed to make it easier for researchers to describe their own datasets and to reduce the effort required to import datasets. The third part of this thesis describes our effort to advance the state of the art in disaggregation algorithms. Three disaggregation approaches based on deep learning are discussed: 1) a form of recurrent neural network called ‘long short-term memory’ (LSTM); 2) denoising autoencoders; and 3) a neural network which regresses the start time, end time and average power demand of each appliance activation. The disaggregation performance was measured using seven metrics and compared to two ‘benchmark’ algorithms from NILMTK: combinatorial optimisation and factorial hidden Markov models. To explore how well the algorithms generalise to unseen houses,the performance of the algorithms was measured in two separate scenarios: one using test data from a house not seen during training and a second scenario using test data from houses which were seen during training. All three neural nets achieve better F1 scores (averaged over all five appliances) than either benchmark algorithm. The neural net algorithms also generalise well to unseen houses.

>Magister Scientiae - MSc
The Smart Renewable Energy project at the University of The Western Cape, under the guidance of the Intelligent Systems and Advanced Telecommunication (ISAT) group, aims at developing a dynamic system that enables users to (1) design smart architectures for next generation wind and solar systems to meet African power challenges (2) use these architectures to dimension the underlying solar and wind power systems and (3) simulate, implement and evaluate the performance of such power systems. The project's existing web and mobile monitoring system will undergo a much needed upgrade to cater for monitoring of the existing system's environmental and battery bank parameters. This will be implemented by allowing users to monitor input, storage and output trends over various time frames. These time frames would include hourly, daily, weekly and monthly readings. The visual evaluation of the system will be generated by mathematical, statistical and machine learning techniques. Trends will be discovered that will allow users to optimize the system's efficiency and their usage patterns. The accompanied dimensioning system will allow users to cater for their needs in a two way fashion. Users will be able to specify the number of devices that they want to run from a solar or wind based system and their power needs will be generated. They will also be able to determine what a given system is capable of producing and the number of devices that can be used simultaneously, as a result.
National Research Foundation (NRF) and Namibia Students Financial Assistance Fund (NSFAF)

"Smart grids'' identifies what future electrical network would represent: an intelligent integrated system where every device available to modify their generation/absorption is responsive, awaken of its role, eco-sensitive, flexible and interconnected with others. In this scenario, smart technologies, such as Information and Communication Technologies and smart meters, will allow interconnections and interactions among these devices that are available to participate in ancillary services; whereas a smart management system would ensure quality, reliability, efficiency, effectiveness in the supply service and the free participation in services for the grid support of these new customers. However, even if the smart grid scenario seems to be clearly defined, investigation on the management system is still required, in order to efficiently co-ordinate all distributed resources in distribution networks and to exploit the potentiality of new possible participants in the network regulation, such us energy storage devices and electrical vehicles. By the way, energy markets seem to be ideally suited to support the system operator in the co-ordination of different energy resources, also allowing the exploitation of synergy among different energy carries to increase the overall efficiency and reliability of the system. In fact, energy markets could create suitable price signals able to make responsive devices available to modify their generation/absorption to network requirements. For this reason, it seems reasonable to refer to these devices as customers. Investigations on smart management procedures for the co-ordination of different resources in energy networks is the main thread of this thesis. In particular, the importance of price signals to obtain a virtuous behavior of customers has been exploited, focusing on co-ordinated management procedures, in order to ensure the management of the complex electrical network system. In the first chapter a brief introduction to smart grids, energy markets and storage devices is provided, in order to present general background and motivation of this work. The modeling basis of the software environment developed during the PhD and used to investigate management issues in smart energy network are presented in chapter 2. Chapter 3 presents preliminary investigations on energy hub, a generation, conversion and storage center, management based on suitable price signals to optimally manage exchanges of flows among different energy vectors, in order to exploit synergy properties. In chapter 4, investigation on the management of a multi-energy vector systems through price coefficients is presented. In particular, price coefficients proportional to reference signals, that represents network requirements, have been analyzed in a decoupled management procedure between network and energy hubs with storage devices. In chapter 5, it is described how to exploit this decoupled optimisation procedure, considering aggregators of EVs as flexible distributed storage devices. In chapter 6, an innovative management procedure based on token ring philosophy, aimed to co-ordinate distributed resources, ensuring their free participation in services for the grid support is proposed. The thesis ends with chapter 7, where the most important achievements and suggests in possible future work are summarizes and discusses.
Con "smart grids'' si può identificare quello che rappresenteranno le reti elettriche del futuro, ovvero un sistema integrato ed intelligente, dove ogni dispositivo disponibile a modificare la propria generazione e il proprio assorbimento, è reattivo, attento ai segnali di prezzo, consapevole del proprio ruolo, sensibile agli aspetti ambientali, flessibile e interconnesso con gli altri. In questo scenario, tecnologie intelligenti, come i sistemi ICT (Information and Communication Technologies) e gli smart meter, permetteranno le interconnesioni e le interazioni tra questi dispositivi disponibili a partecipare nei servizi ancillari; mentre un sistema di gestione intelligente dovrebbe essere in grado di assicurare qualità, affidabilità, efficienza, efficacia nel servizio di fornitura e la libera partecipazione nei servizi per il supporto della rete di questi nuovi clienti. Sebbene lo scenario identificato dal termine "smart grids'' sembri essere chiaramente definito, risulta ancora necessario lo studio relativo al sistema di gestione fondamentale per coordinare in maniera efficiente le risorse distribuite nelle reti di distribuzione e le potenzialità introdotte da nuovi possibili participanti nella regolazione della rete, come per esempio i sistemi di accumulo e i veicoli elettrici. A questo proposito, i mercati energetici sembrano ideali per aiutare l'operatore di sistema a coinvolgere tutte le risorse energetiche nella regolazione della rete, permettendo anche lo sfruttamento della singergia tra differenti vettori energetici, allo scopo di incrementare l'efficienza e l'affidabilità generale di tutto il sistema. Infatti, i mercati energetici possono creare appropriati segnali di prezzo in grado di rendere sensibili alle esigenze della rete quei dispositivi disponibili a modificare la loro generazione e il loro assorbimento. È per questo motivo che sembra opportuno identificare questi dispositivi come clienti. Il principale filo conduttore di questa tesi è stato la ricerca di procedure intelligenti di gestione per la coordinazione di differenti risorse nelle future reti energetiche intelligenti. In particolare, è stata sfruttata l'idea chiave dell'importanza dei segnali di prezzo per ottenere un comportamento virtuoso dei clienti, concentrandosi su metodi di coordinamento in grado di assicurare con meccanismi semplici la gestione di un complesso sistema come quello della rete elettrica. Nel primo capitolo di questa tesi è presente una breve introduzione alle smart grids, ai mercati energetici e ai sistemi di accumulo, al solo scopo di presentare background e motivazioni di questo lavoro. Il capitolo 2 raccoglie le basi teoriche della modellizzazione dell'ambiente software sviluppato durante il dottorato e usato per studiare la gestione in reti energetiche intelligenti. Il capitolo 3 presenta le prime indagini sulla gestione di un energy hub, un centro di generazione, conversione e assorbimento, basata su segnali di prezzo adeguati a permettere una gestione ottima di flussi tra differenti vettori energetici, in modo da sfruttare la loro sinergia. Il capitolo 4 riporta quanto studiato per la gestione di un sistema multi-vettore energetico attraverso coefficienti di prezzo. In particolare, è stata analizzata la possibilità di utilizzare termini di prezzo proporzionali ad un segnale di riferimento che rappresenti la richiesta della rete in una gestione disaccoppiata di rete ed energy hub con sistemi di accumulo. Questa precudura di ottimizzazione disaccoppiata è stata applicata nel capitolo 5 a degli agglomerati di veicoli elettrici, intesi come sistemi di accumulo flessibili e distribuiti. Nel capitolo 6, infine, viene presentata un'innovativa procedura di gestione, basata sulla filosofia del token ring, mirata a coordinare risorse distribuite assicurando la loro libera partecipazione nei servizi per il supporto della rete. La tesi si chiude con il capitolo 7, che riassume e discute i più importanti traguardi raggiunti e suggerendo possibili lavori futuri.

Utveckling av det moderna samhället och den fortsatt accelererande energiintensiva tillvaro människan lever i sätter stor press på klimatet. För att nå de hållbarhetsmål FN satt upp som bland annat innebär minskade utsläpp och effektivare energianvändning krävs krafttag i det globala energisystemet. För att öka andelen modern och ren energi krävs att sol- och vindkraft prioriteras. Ett stort problem med dessa energikällor är dess intermittenta produktion vilken alstrar oregelbunden elektricitet och ställer nya krav på elnätet. För att underlätta implementering av förnybara energikällor på det nationella elnätet och i mindre energisystem undersöks i den här rapporten de förutsättningar som finns för att integrera batterienergilagringssystem i kombination med intermittenta energikällor. Rådande förutsättningar redogörs för i en omfattande litteraturundersökning där bland annat elnätets funktion, lovande batteriteknologier, ekonomiska incitament för batterienergilagring och framtidspotential undersöks. Ett globalt engagemang för att öka andelen förnybar energi med hjälp av batterienergilagring i det globala energisystemet identifieras. Vidare visas batterienergilagringssystem har stor potential att minimera den belastning intermittenta energikällor har på elnätet. Potentialen begränsas i nuläget av rådande politiska styrmedel och elmarknadens utformning då en småskalig elproducent idag gynnas av att direkt mata ut överskottsel på elnätet istället för att använda energilagring. Med en växande andel intermittent elproduktion förväntas minskade begränsningar och batterienergilagring kopplat till elproduktion bli mer lönsamt.
The development of the modern society and the global continuously accelerating energy intensive way of living is putting stress on the climate. In order to achieve the UNs set of sustainability goals, including reduced emissions and more efficient use of energy, vigorous actions in the global energy system is required. To increase the share of clean and modern energy generation a larger quantity of solar and wind power is required. Due to weather dependency these resources generate intermittent electricity which will put new challenges on the grid.   To facilitate the implementation of intermittent energy sources on the national grid and in smaller energy systems this report aims to investigate current prerequisites on integrating battery energy storage systems and intermittent resources to increase the share of clean energy sources in the power system. Current prerequisites are presented as the result of an extensive literature study where the electrical grid, promising battery technologies, financial incentives for battery energy storage and future potential is examined.   A global commitment to increase the share of renewable energy sources using battery energy storage system in the global energy system is identified. Furthermore, battery energy storage systems are shown to have great potential in limiting the negative impact of intermittent energy sources on the electrical grid. This potential is currently being limited by existing political control means and the design of the electricity market such that small producers are benefitted by directly supplying the grid with excess electricity instead of using energy storage. With a growing share of intermittent power generation these limitations are expected to ease and battery energy storage systems in connection with power production becoming more profitable.​

Sweden has developed ambitious goals regarding energy and climate politics. One major goal is to change the entire electricity production from fossil fuels to sustainable energy sources, this will contribute to Sweden being one of the first countries in the world with non-fossil fuel in the electricity sector. To manage this, major changes need to be implemented and difficulties on the existing grid will occur with the expansion of digitalization, electrification and urbanization. By using smart grids, it is possible to deal with these problems and change the existing electricity grid to use more distributed power generation, contributing to flexibility, stability and controllability. The goal with smart grids is to have a sustainable electricity grid with low losses, security of supply, environmental-friendly generation and also have choices and affordable electricity for customers. The purpose of this project is to identify and evaluate several indicators for a smart grid, how they relate and are affected when different scenarios with different technologies are implemented in a test system. Smart grid indicators are quantified metrics that measure the smartness of an electrical grid. There are five scenarios where all are based on possible changes in the society and electricity consumption, these scenarios are; Scenario A – Solar power integration, Scenario B – Energy storage integration, Scenario C – Electric vehicles integration, Scenario D – Demand response and Scenario E – Solar power, Energy storage, Electric vehicles and Demand response integration. A model is implemented in MATLAB and with Monte Carlo simulations expected values, standard deviation and confidence interval were gained. Four selected indicators (Efficiency, capacity factor, load factor and relative utilization) was then analyzed. The results show that progress on indicators related to all smart grid characteristics is needed for the successful development of a smart grid. In scenario C, all four selected indicators improved. This shows that these indicators could be useful for promoting the integration of electric vehicles in an electricity grid. In Scenario A, solar power integration contributed to all indicators deteriorate, this means that, technical solutions that can stabilize the grid are necessary to implement when integrating photovoltaic systems. The load factor is a good indicator for evaluating smart grids. This indicator can incentivize for an even load and minimize the peak loads which contributes to a flexible and efficient grid. With the capacity factor, the utilization and free capacity can be measured in the grid, but it can counteract renewable energy integration if the indicator is used in regulation.

Thesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2007.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 61-63).
With the environmental crisis involving climate change fast approaching, all potential mitigation techniques must be explored and implemented. A key approach comes from the power towns and cities have to influence land use and building standards in their jurisdiction. This thesis uses a scenario planning approach to explore the energy implications of four potential futures for the town of Littleton, MA. Four scenario storylines (Business as Usual (BAU), Baby Steps (high residential density, no mixing), Mixed Use Village (higher residential density, mixed uses), and Thoroughly Green (similar to Mixed Use Village with added green building requirements)) were used to frame the potential outcomes. Typical development typologies from nearby Massachusetts towns served as proxies for the scenarios. Using an elasticity method based on the density, diversity and design of the typologies, the reduction in Vehicle Miles Traveled (VMT) for each alternative scenario as compared to the BAU scenario was calculated and used to determine the reduction in gasoline usage and CO2 emissions. Local and regional average electricity and heating values were used to calculate the home energy consumption for each scenario.
(cont.) The Baby Steps and Mixed Use Village/Thoroughly Green scenarios reduced VMT by 14% and 32%, respectively. The Baby Steps scenario used 45% less electricity, the Mixed Use Village used 55% less, and the Thoroughly Green scenarios used 65% less than the BAU scenario. The annual cost savings per capita from the above energy savings run from $321 to $737 for transportation and CO2 reduction, and $242 to $408 for housing energy consumption. The total savings per capita run from $563-$1,145. The total savings for the hypothetical development are $1.2 million to $2.4 million. Policy makers should take the results of this scenario analysis to support the inclusion of energy implications in land use planning. Recommended measures include requiring an energy section in master plans, providing state-wide technical support for these plans, supporting processes to incorporate energy considerations in public planning processes, and funding for further research into the quantification of the energy land use connection and what steps towns can take to address it.
by Katherine Van Tassel.
M.C.P.

In recent years, the need for personal urban mobility has increased a lot especially in emerging and developing countries. It becomes increasingly important to explore propulsion systems that use alternative energy sources and are related to the chain of production, storage and use of renewable energy. Several studies have been conducted in this area, but very few have achieved solutions for the interaction of the vehicle with the building by which it is parked in terms of a multi-energy exchange. Technological innovation of house plant parts, of large residences / hotels, of shelter stations for vehicles, it is now crucial to implement the integration of more renewable energy sources within the same building structure: this is one of the aspects covered by the most general definition of "Smart Housing". Sustainable mobility is perceived as a strong need to match individual urban and sub-urban mobility, to the least environmental and social impact of such personal need. This research project proposes a possible scenario for energy integration between smart housing and smart mobility using a common energy platform that allows self-generation, storage and energy exchange between residential district buildings and smart vehicles. The project integrates multidisciplinary approaches with the aim of designing, evaluating technical and industrial feasibility for the development of: 1) Modular and scalable energy storage devices dedicated to a smart house. 2) a modular city vehicle, with high flexibility of use, with energy storage system and energy-efficient switching capabilities with smart building.

Transforming our energy system towards 100% renewable energy sources requires radical changes across all energy sectors. Heat pumps as efficient heat generation technology link the electricity and heat sector. From 2010 to 2015 between 750,000 and 800,000 heat pumps have been sold every year across Europe. Those heat pumps, when connected to thermal storage or using the buildings’ thermal inertia, have the potential to offer demand flexibility to the power system. In a renewable, interconnected and to a large extend decentralised energy system - the smart grid - heat pumps can be operated according to the need of the electric power system. This might impact heat pump system design, controls and operation, which is investigated in this thesis. The main objective of this thesis is to add knowledge and suggest methods to facilitate the transition towards a renewable and smart energy system, in which heat pump systems and their flexibility are used and designed in an optimal way. Therefore this thesis investigates the integration of heat pumps in a smart grid on three different system boundary levels. On each boundary level the focus is on different aspects and different methods are used. On the highest boundary level, the integration of heat pumps into a smart grid and the resulting requirements for heat pump system design are studied. Results of a literature study show, that currently discussed applications of heat pumps in a smart grid focus on the provision of ancillary services, the integration of renewable energy sources, and the operation under time variable electricity prices. Integrating heat pumps into the power system can be achieved by direct, indirect and agent based control strategies. The next level of investigation covers the aggregation of heat pumps into pools. For this purpose a stochastic bottom-up model for heat pump pools has been developed. This model accounts for the diversity of buildings, heat pump systems and occupants. Results of a simulation study of a heat pump pool highlight the fact that flexibility of heat pumps is not constant and is changing during the course of the day and year. A characteristic response of a heat pump pool towards direct load control signals is identified and shows three characteristic phases 1) charging/ activation phase, 2) steady state phase, 3) discharging/regeneration phase. It is found that the duration of the control signal and the load shift strategy implemented in the heat pump systems are decisive for flexibility. Further it is shown that flexibility might come at the cost of efficiency of the local heat pump systems. On the level of individual buildings this thesis explores to which extent the sizing of heat pumps, storage and back-up heater as well as system controls have to be adjusted when integrating heat pumps into a smart grid. Results of a structural optimisation study, targeting to minimise total cost of ownership, show that sizing of the heat pump unit and the electric back-up heater remain almost unchanged when PV and time variable electricity prices are introduced. However an increase in storage capacity is beneficial to profit from time variable prices or onsite photovoltaic (PV). It showed that the ways heat pumps and storages are sized in Germany today provided sufficient storage capacity for most of the investigated scenarios. Furthermore increasing storage leads to diminishing returns as investment costs and system losses increase with increasing storage size. This leads to the conclusion that local heat pump system efficiency as well as flexibility requirements of the power system should be considered, when designing heat pump systems. Improving the controls shows great potential for increasing heat pump system efficiency, reducing operation cost and scheduling heat pump operation along to match the requirements from the power system. A dynamic building simulation study, where rule-based, predictive rule-based and model predictive control approaches were compared, reveals that the use of model predictive controls can reduce annual electricity cost and increase PV self-consumption significantly, compared to tailored rule-based and predictive rule-based control approaches. When deciding upon a control strategy the following should be taken into account: complexity of design, robustness against changes in external conditions and computational resources. It is shown that operating heat pumps in a smart grid changes operating hours, temperatures, on/off cycles and seasonal performance compared to today’s heatdriven operation. It is shown that the goals to reduce operating cost, maximise system efficiency or increase PV self-consumption can be conflicting and are often impossible to achieve simultaneously. Not necessarily will operation in a smart grid increase the efficiency of individual systems, rather offers the possibility to increase efficiency of the overall energy system. It is found that sizing, controls and use-case are interconnected and should be considered simultaneously in the design process of heat pump systems. A goal for future research should be the design of optimum flexible heat pump systems, where the heat pump unit, the building, the hydraulic system, heat distribution, storage and controls are designed optimally for the flexibility requirements of both the end-users and the power system.

Augmentar l’ús d’energia provinent de fonts renovables és important en la lluita contra el canvi climàtic. No obstant, la seva implantació planteja reptes importants deguts a la manca de continuïtat en la seva generació i al desajust que existeix amb els perfils de consum. La present tesi doctoral s’emmarca en dues propostes per incrementar el rendiment dels panells fotovoltaics en l’àmbit dels sistemes de calefacció per edificis. Per una banda, el sistema integra un tanc d'emmagatzematge d'energia tèrmica, que permet emmagatzemar l'energia generada pels panells durant el dia, a fi de poder-la consumir a les hores amb més demanda. D'altra banda, el sistema també compta amb una estratègia de control predictiu, que permet pronosticar les condicions meteorològiques i les demandes de calefacció futures, per tal d'ajustar el funcionament de tot el conjunt d'elements, considerant aquesta informació. El sistema proposat ha demostrat ser efectiu en diferents tipus de clima i habitatges.
Aumentar el uso de energía procedente de fuentes renovables es importante en la lucha contra el cambio climático. No obstante, su implantación plantea retos importantes debidos a la falta de continuidad en su generación y al desajuste que existe con los perfiles de consumo. La presente tesis doctoral se enmarca en dos propuestas para incrementar el rendimiento de los paneles fotovoltaicos en el ámbito de los sistemas de calefacción para edificios. Por un lado, el sistema integra un tanque de almacenaje de energía térmica, que permite almacenar la energía generada por los paneles durante el día, a fin de poderla consumir a las horas con más demanda. Por otro lado, el sistema también cuenta con una estrategia de control predictivo, que permite pronosticar las condiciones meteorológicas y las demandas de calefacción futuras, para ajustar el funcionamiento de todo el conjunto de elementos, considerando esta información. El sistema propuesto demostró ser efectivo en distintos tipos de climas y viviendas.
To increase the use of energy that comes from renewables is important to fight against climate change. However, their deployment leads to significant challenges due to the intermittence in their generation and the mismatch between energy demand and supply. In that sense, this PhD thesis is framed in two proposals to increase the performance of photovoltaic panels in heating systems integrated in the building sector. On the one hand, the system considers a thermal energy storage tank, which allows to store the energy produced by the panels during the solar hours, in order to consume it along the peak demand periods. On the other hand, the system also takes into account a model predictive control strategy, which enables to forecast weather conditions and future heating demands, to adjust the operation of all the elements. The proposed system demonstrated a good and effective behaviour in different climate conditions and buildings.

This thesis presents an approach to design and implementation of a Renewable Power Complex (RPC) containing several intermittent sources. The purpose of RPC is to improve the poor rural distribution network voltage portfolio which can be traced back to the typical long distance radial lines. With the purpose of improve system overall voltage, iterative studies are conducted to calculate the requirements of RPC in terms of capacity. Afterwards, the proposed approach is verified at a test system. From implementation perspective, the capacity of the inverter interfacing the generation unit is a bottleneck that limits the possible dimension of the RPC. Consequently, the RPC is actually composed by several atomic units with a much smaller scale. The software where the potentials of intermittent generation sources can be estimated given the geographic information is used to optimize the size of RPC atomic units. Finally, the thesis tackles a high level design of automations system under which the RPC is operated. The functionality described are all compliant with commonly accepted IEC 61850 standards with the intention to ease the future implementation.

The goal of the thesis was constructing a control system for a curtain that would regulate its position between up- and down states depending on out/indoor temperature and incoming solar radiation in order to be more energy efficient. A curtain hanging in front of a window creates a pocket of air, which in tandem with the curtain insulates the window and decreases heat loss, but at the same time it vastly decreases how much solar energy enters the room. A considerable part of a households total heat energy loss occurs through its windows. In order to lower this outflow and maximize the inflow of solar energy, it was decided upon to build a system that regulates the state of a window’s curtain. A scaled down prototype was constructed, consisting of a Styrofoam box with a window on one side, and a curtain in front of it. It was used to measure actual energy savings and also compare theoretical coefficients with experimentally procured ones, and extrapolate the results unto a larger scale. Heat transfer rates both with and without the curtain were experimentally tested. This data was then used to implement a computer program, which was developed specifically for the project. It took input arguments needed for the calculations and output whichever curtain state would be most beneficial at any given moment. The program input was partially collected from two temperature sensors and one light sensor. The output was then used to control an actuator in the form of a stepper motor to change the curtain state. Finally, wireless controlling and monitoring of the system utilizing a dashboard accessible via the internet was implemented to permit tracking of data and overriding of the control system’s decisions, should the user desire. It was found that a system of this type could deliver energy savings on the magnitude of tenths of a kilowatt-hour per day during the winter in central Sweden.
Målet med denna kandidattes var att konstruera ett kontrollsystem åt en rullgardin för att reglera dess position mellan upp- och nedfällt läge, beroende på inne- och utetemperatur samt inkommande solstrålning för att spara energi. En gardin som hänger framför ett fönster ger upphov till en luftficka, som tillsammans med gardinen bidrar till att isolera fönstret och minskar värmeförluster, samtidigt som det drastiskt minskar solinstrålning in i rummet. En väldigt stor del av en byggnads totala värmeförluster sker via dess fönster. För att minska detta utflöde och maximera inflöde av solenergi, beslöts det att bygga ett system som reglerar en gardins läge. En prototyp i reducerad skala konstruerades, beståendes av en cellplastlåda med ett fönster med gardin på ena sidan. Den användes för att mäta energibesparingar och för att jämföra teoretiska koefficienter med koefficienter framtagna ur egna experiment, och extrapolera resultaten till en större skala. Värmeöverföringshastighet både med och utan gardin testades experimentellt. Dessa data användes sedan för att implementera ett datorprogram speciellt framtaget för projektet. Det tog emot indata som krävdes för beräkningar, och gav utdata i form av vilket gardinläge som skulle vara mest fördelaktigt vid varje givet tillfälle. Indata hämtades delvis från två temperatursensorer och en ljussensor. Utsignalen användes sedan för att styra en aktuator i form av en stegmotor för att ändra gardinpositionen. Slutligen infördes trådlös styrning och övervakning av systemet via en internet dashboard som samverkar med en MQTT-mäklare, för att tillåta kontroll av data och manuell styrning av gardinen. Slutsatsen nåddes att ett system av denna typ kunde leverera energibesparingar med en magnitud på tiondelars kilowattimmar per dag under vintern i centrala Sverige.

Context: Recent trends show that there is a tremendous shift from IT companies following traditional methods by hosting their applications/systems in self-managed on premise data centers to using the so-called cloud data centers. Cloud computing has received immense popularity due to its architecture and the ease of usage. Due to this increase in demand and shift in practices, there has been a tremendous increase in number of data centers over a period, resulting in increase of energy consumption. In this thesis work, a research is carried out on optimizing the energy consumption of a typical cloud data center. OpenStack cloud computing software is chosen as the platform in this research. We have used live migration as a key aspect in this research. Objectives: In this research, our objectives are as follows: Design an OpenStack testbed to implement the migration of virtual machines. To estimate the energy consumption of the data center. To design a heuristic algorithm to evaluate the performance metrics and to optimize the overall energy consumption. Methods: We have used PowerAPI, a software tool to estimate the energy consumption of hosts as well as virtual machines. A heuristic algorithm is designed and implemented in an instrumental OpenStack testbed to optimize the energy consumption. Server consolidation and load balancing of virtual machines methodologies are used in the heuristic algorithm design. Our research is carried out against the functionality of Nova scheduler of OpenStack. Results: Results section describes the values of performance metrics yielded by carrying out the experiment. The obtained results showed that energy can be optimized significantly by modifying the way OpenStack nova scheduler can work. The experiment is carried out on vanilla OpenStack and OpenStack with the heuristic algorithm in place, In the second case, the nova scheduler algorithms are not used but the heuristic algorithm is used instead. The CPU utilization and CPU load were noticed to be higher than the metrics observed in case of OpenStack with nova scheduler. Energy consumption is observed to be lesser than the consumption in OpenStack design with nova scheduler. Conclusions: The research tells that energy consumption can be optimized significantly using desired algorithms without compromising the service quality it offers. However, the design impacts on CPU slightly as the metrics are observed to be higher when compared to that in case of OpenStack with nova scheduler. Although it won’t have noticeable impact on the system.

Real-time data of power infrastructures collected by wireless sensors are the foundation of many smart grid applications. However, the finite life span of the batteries which power the wireless sensor becomes a bottleneck problem as it is expensive to periodically replace these batteries. Energy harvesting can be an effective solution for autonomous, self-powered wireless sensors. In the vicinity of high voltage/current equipment, a strong magnetic field is generated, which could be a consistent energy source. The purpose of this thesis is to present a comprehensive study into a magnetic field energy harvesting system which mainly consists of coil and rectifying circuit with the ultimate goal to obtain the maximum energy as efficiently as possible for a given condition. The main contribution of this thesis is in two research areas: The first area is about the design of an energy harvesting coil. The ferromagnetic core is the most important part to determine the output power from the whole energy harvesting system. Thus, the precise knowledge of ferromagnetism is critical. As the harvesting coil may not fully enclosure the current conductor, the demagnetization factor which is closely related to the core geometry is carefully studied and minimized. Two new core shapes have been proposed and optimized to have much lower demagnetization factors (hence more power) than that of a conventional rod. 1. A bow-tie-shaped core is introduced and designed to have two large end surfaces. By making its two ends broader, more magnetic flux can be guided from the air into the ferromagnetic core. This intensifies the magnetization at the middle of the core where the wire is wound on. 2. A new helical core is introduced as a further improved version of the bow-tie core. It utilizes two big circular plates fitted at the both ends for the flux collection. In the middle, a helical-shaped core is introduced to increase the path of the magnetic flux. Therefore, the separation between the north pole and south pole is lengthened dramatically, which leads to a reduction in the demagnetization factor and an increase in the magnetic flux density. In addition to the core shape, the selection of the core material is studied and found that high permeability ferrite is the most suitable core material due to its high relative permeability and ultra-low conductivity. Thus, the eddy current losses in the ferromagnetic core can be significantly reduced. Experimental results show that the proposed helical coil with only 400 turns of wire can have a power density of 2.1 μW/cm3 when placed in a magnetic flux density of 7 μTrms. This value is 17 times greater than a previously reported design with 40,000 turns of wire (0.12 μW/cm3 ) placed in the same magnetic field. If a longer helical coil with 8,000 turns of wire is placed in a magnetic flux density of 11 μTrms, the produced power density is around 131.4 μW/cm 3 which is comparable to a solar panel working during a cloudy day. The second area is about the rectifying circuit design which utilizes the energy harvested from the coil to power a commercial wireless sensor. A voltage doubler is applied to provide full-wave rectification and simultaneously boost the output voltage. A transient analysis is carried out to calculate the input resistance of a charging capacitor as a function of time. The theoretical analysis indicates that the input resistance is highly related to the input and output voltages. Therefore, a conventional matching network which consists of linear components cannot work well. A switch mode power converter is introduced as a matching network so that the charging capacitor can be isolated from the harvesting coil. The emulated input resistance looking into the power converter is a constant and determined by the frequency and the duty cycle of the power width modulation applied on the switch. The system is designed and made. The experimental results demonstrate that the energy conversion efficiency from the harvesting coil to the storage capacitor is around 74.6% which is twice as large as a previously reported design. Finally, an energy management unit is developed and it effectively utilizes the energy stored in the capacitor to power a commercial wireless sensor. It is shown in this thesis that a highly efficient magnetic field energy harvesting system has been successfully demonstrated. A wireless sensor can be properly powered up by using a small coil (15 cm long) placed in a small magnetic flux density (7 μTrms). The proposed solution is a very efficient and attractive method for harvesting the magnetic field energy for a wide range of smart grid applications.

Yes
Concrete with smart and functional properties (e.g., self-sensing, self-healing, and energy-harvesting) represents a transformative direction in the field of construction materials. Energy-harvesting concrete has the capability to store or convert the ambient energy (e.g., light, thermal, and mechanical energy) for feasible uses, alleviating global energy and pollution problems as well as reducing carbon footprint. The employment of energy-harvesting concrete can endow infrastructures (e.g., buildings, railways, and highways) with energy self-sufficiency, effectively promoting sustainable infrastructure development. This paper provides a systematic overview on the principles, fabrication, properties, and applications of energy-harvesting concrete (including light-emitting, thermal-storing, thermoelectric, pyroelectric, and piezoelectric concretes). The paper concludes with an outline of some future challenges and opportunities in the application of energy-harvesting concrete in sustainable infrastructures.
The full-text of this article will be released for public view at the end of the publisher embargo on 19 Jul 2022.

ENABLING DEMAND RESPONSE ON ENERGY MANAGEMENT IN SMART HOME With the penetration of the Internet of Things (IoT) paradigm into the household scenario, an increasing number of smart appliances have been deployed to improve the comfort of living in the household. At present, most smart home devices are adopting the Cloud-based paradigm. The increasing electricity overhead from these smart appliances, however, has caused issues, as existing home energy management systems are unable to reduce electricity consumption effectively. To address this issue, we propose the use of an Edge-based computing platform with lightweight computing devices. In our experiments, this Edge-based platform has proven to be more energy efficient when compared to the traditional Cloud-based platform. To further reduce energy tariffs for households, we propose an energy management framework, namely Edge-based energy management System (EEMS), to be used with the Edge-based system that was designed in the first stage of our research. The EEMS is a low infrastructure investment system. A small-scale solar energy harvesting system has also been integrated into this system. The non-intrusive load monitoring (NILM) algorithm has been implemented in appliances monitoring. Regarding to energy management function, the scheduling strategy can also conform to user preference. We have conducted a realistic experiment with several smart appliances and Raspberry Pi. The experiment resulted in the electricity tariff being reduced by 82.3%. The last part of research addresses demand response (DR) technology. With the development of DR, energy management systems such as EEMS are better able to be implemented. We propose the use of an electricity business trading model, integrated with user-side demand response resources. The business trading model can be adopted to manage risks, increase profit and improve user satisfaction. Users will also benefit from tariffs reduction with the use of this model.

This thesis has contributed to the design of suitable decision-making techniques for energy management in the smart grid with emphasis on energy efficiency and uncertainty analysis in two smart grid applications. First, an energy trading model among distributed microgrids (MG) is investigated, aiming to improve energy efficiency by forming coalitions to allow local power transfer within each coalition. Then, a more specific scenario is considered that is how to optimally schedule Electric Vehicles (EV) charging in a MG-like charging station, aiming to match as many as EV charging requirements with the uncertain solar energy generation. The solutions proposed in this thesis can give optimal coalition formation patterns for reduced power losses and achieve optimal performance for the charging station. First, several algorithms based on game theory are investigated for the coalition formation of distributed MGs to alleviate the power losses dissipated on the cables due to power transfer. The seller and buyer MGs can make distributed decisions whether to form a coalition with others for energy trading. The simulation results show that game theory based methods that enable cooperation yield a better performance in terms of lower power losses than a non-cooperative approach. This is because by forming local coalitions, power is transferred within a shorter distance and at a lower voltage. Thus, the power losses dissipated on the transmission lines and caused by power conversion at the transformer are both reduced. However, the merge-and-split based cooperative games have an inherent high computational complexity for a large number of players. Then, an efficient framework is established for the power loss minimization problem as a college admissions game that has a much lower computational complexity than the merge-and-split based cooperative games. The seller and buyer MGs take the role of colleges and students in turn and apply for a place in the opposite set following their preference lists and the college MGs’ energy quotas. The simulation results show that the proposed framework demonstrates a comparable power losses reduction to the merge-and-split based algorithms, but runs 700 and 18000 times faster for a network of 10 MGs and 20 MGs, respectively. Finally, the problem of EV charging using various energy sources is studied along with their impact on the charging station’s performance. A multiplier k is introduced to measure the effect of solar prediction uncertainty on the decision-making process of the station. A composite performance index (the Figure of Merit, FoM) is also developed to measure the charging station’s utility, EV users charging requirements and the penalties for turning away new arrivals and for missing charging deadlines. A two-stage admission and scheduling mechanism is further proposed to find the optimal trade-off between accepting EVs and missing charging deadlines by determining the best value of the parameter k under various energy supply scenarios. The numerical evaluations give the solution to the optimization problem and show that some of the key factors such as shorter and longer deadline urgencies of EVs charging requirements, stronger uncertainty of the prediction error, storage capacity and its initial state will not affect significantly the optimal value of the parameter k.

Smart grid is an emerging technology that aims to empower the current power grid with the integration of two-way communication and computer technology. This thesis deals with energy management in smart grid with focus on the smart home and the Intelligent Transportation System (ITS). The smart home contains a network that connects home elements like smart appliances, HVAC (heating, ventilation, and air conditioning), thermostat, smart meter, sensors, solar panels and energy storage. ITS integrates computer and communication technologies for advanced traffic management and communication among road infrastructure, vehicles and users. A web service describes a collection of operations that are accessible via the Internet. Web services can also provide security and interoperability. Due to the rising cost of energy, more and more residential consumers are interested in controlling temperature or appliances in order to reduce energy consumption. In this thesis, we propose an approach that uses Web services to remotely and efficiently interact with smart home devices in order to manage energy consumption, in a smart grid environment. Consequently, the user is able to adjust the temperature, control appliances or read energy consumption values quickly, remotely and securely. A smart home with a wireless network based on ZigBee and XMPP (eXtensible Messaging and Presence Protocol) is simulated. The advantage of XMPP is that it provides near real-time communication and security. There is a central computer that can communicate with all home elements. Business Process Execution Language (BPEL) is used to implement the Web service on a central computer. Furthermore, quality of service is offered. Therefore, different levels of security and an access control mechanism are provided. An algorithm is proposed that can sell stored energy back to the grid from smart home. Another algorithm is proposed that can facilitate demand response. Moreover, dynamic programming is used to minimize energy consumption. Also, a broadcasting algorithm is presented that can be used by an electric vehicle to find the most suitable charging station in ITS. Simulation and analytical study is undertaken to demonstrate the performance and advantage of the proposed approach and algorithms.

This work deals with technology and innovation management issues on the particular case of electricity smart metering in the Czech Republic. The popular literature on this topic is not reflecting on industries with high level of regulation in demand determination, which is the precise case of this industry. Positions of distribution network operators, technology suppliers, end-consumers and the regulatory players are analyzed. Comparison with other European countries is shown with market development predictions also taking part of the analysis. The outcome of this work reflects on the 2012 decision of the regulatory authority in the Czech Republic, which is to decide on a mandatory roll-out of this technology. This work presents the path towards this decision and discusses the potential outcomes.

Belysning är en väsentlig del i ett fungerande samhälle. Utveckling av belysning går framåt hela tiden, för att bli så användarvänligt som möjligt. Idag kan belysning förutsäga hur utrymmen används med hjälp av information från andra armaturer, så att området blir belyst även om brukaren rör sig precis på gränsen av det belysta området. Att få fram en energieffektiv belysning tillsammans med dagsljus, utan att ge avkall på den visuella komforten är en viktig fråga för beställare av belysning. Visuell komfort är dock mer komplicerat än energibesparing, eftersom det innebär fler faktorer och det gynnsamma resultatet är svårare att uppskatta. Visuell komfort, så som rumsuppfattning beskriver hur vi ser ett rums storlek och form. Något att ha i åtanke är också att rummet inte alltid uppfattas så som det är planerat och tänkt. Idag blir energibesparande styrsystem allt viktigare i kommersiella byggnader då det finns hög potential att minska energiförbrukningen. Utöver att spara energi kan smarta styrsystem också användas för att förbättra ljuskvalitet samt öka produktiviteten. Följande examensarbete undersöker hur smarta styrsystem kan påverka den visuella rumsuppfattningen i kontor, samt om energiförbrukningen förändras av styrsystem, kontra statisk belysning. Undersökningen utgår från två frågeställningar. För att besvara den första frågeställningen som behandlar rumsuppfattning utgår arbetet från en kvantitativ ansats i form av en digital enkätundersökning. Undersökningen omfattar hur belysningen på kontor uppfattas av personal på olika företag som använder sig av smarta styrsystem, jämfört med de som använder statisk belysning. Enkätens syfte var att få reda på deltagarnas uppfattningar om belysningen på sitt kontor. Deltagarna fick svara utifrån sina egna uppfattningar och värderingar. Totalt svarade 37 personer på enkäten. Den andra frågeställningen som handlar om energiförbrukning, beräknas utifrån en armatur från Aura Light. Undersökningen går ut på att jämföra armaturens energiförbrukning då den är statisk och har 100% ljusflöde och sedan titta på energiförbrukningen när den är uppkopplad till ett styrsystem. Därefter jämförs resultaten. De slutsatser som dras i studien kring resultatet av rumsuppfattningen påvisar att det förekom skillnader. Majoriteten av de som hade statisk belysning uppfattade rummet som allmänt och ljust, medan majoriteten med styrsystem uppfattade rummet som lugnt och trivsamt. Detta tyder på att styrsystem i viss mån kan ha en påverkan på hur människor uppfattar ett rums karaktär tillsammans med belysningen. Gällande resultatet kring energiförbrukningen med styrsystem kontra statisk belysning, visar det att det finns potential att spara energi vid byte av belysningssystem på kontor.
Lighting is an essential part of a functioning society. The development of lighting is constantly advancing in order to be as user-friendly as possible. Illumination can predict how spaces are used, using information from other luminaires, so that the area is illuminated even if the user moves exactly on the border of the illuminated area. Obtaining an energy-efficient lighting together with daylight without sacrificing visual comfort is an important issue for lighting buyers. However, visual comfort is more complicated than energy saving, as it means more factors and the favorable result is more difficult to estimate. Visual comfort, such as room perception describes how we see a room's size and shape. Something to keep in mind is that the room is not always perceived as planned and intended. Today energy-saving control systems are becoming increasingly important in commercial buildings as there is a high potential to reduce energy consumption. In addition to saving energy, smart control systems can also be used to improve light quality and increase productivity. This thesis examines how smart control systems can change the visual room perception in offices, as well as how energy consumption is affected by control systems, versus static lighting. The thesis is based on two questions. To answer the first question that deals with room perception, the study is based on a quantitative approach in the form of a digital survey. The survey covers how office lighting is perceived by staff at different companies using smart control systems compared to those using static lighting. The purpose of the survey was to find out the test persons' perceptions of the lighting in their office. The test subjects were given answers based on their own perceptions and values. A total of 37 people answered the survey. The second question is about energy consumption, which is calculated from a luminaire from Aura Light. The study is based on comparing the luminaire, when it is static with 100% flux and then when it is connected to a control system, so as to be able to compare the energy consumption. The conclusions drawn in the study of the result of the room perception show that some differences existed. The majority of those who had static lighting perceived the room as general and bright, while the majority with control systems perceived the room as calm and pleasant. This indicates that control systems can to some extent have an impact on how people perceive a room's character together with the lighting. Regarding the result of energy consumption with control systems versus static lighting, it shows that there is definitely potential to save energy when changing lighting systems in offices.

With the ever-growing concerns of environmental and climate concerns for energy consumption in our society, it is crucial to develop novel solutions that improve the efficient utilization of distributed energy resources for energy efficiency and demand response (DR). As such, there is a need to develop targeted energy programs, which not only meet the requirement of energy goals for a community but also take the energy use patterns of individual households into account. To this end, a sound understanding of the energy behavior of customers at the neighborhood level is needed, which requires operational analytics on the wealth of energy data from customers and devices. In this dissertation, we focus on data-driven solutions for customer energy behavior characterization with applications to distributed energy management and flexibility provision. To do so, the following problems were studied: (1) how different customers can be segmented for DR events based on their energy-saving potential and balancing peak and off-peak demand, (2) what are the opportunities for extracting Time-of-Use of specific loads for automated DR applications from the whole-house energy data without in-situ training, and (3) how flexibility in customer demand adoption of renewable and distributed resources (e.g., solar panels, battery, and smart loads) can improve the demand-supply problem. In the first study, a segmentation methodology form historical energy data of households is proposed to estimate the energy-saving potential for DR programs at a community level. The proposed approach characterizes certain attributes in time-series data such as frequency, consistency, and peak time usage. The empirical evaluation of real energy data of 400 households shows the successful ranking of different subsets of consumers according to their peak energy reduction potential for the DR event. Specifically, it was shown that the proposed approach could successfully identify the 20-30% of customers who could achieve 50-70% total possible demand reduction for DR. Furthermore, the rebound effect problem (creating undesired peak demand after a DR event) was studied, and it was shown that the proposed approach has the potential of identifying a subset of consumers (~5%-40% with specific loads like AC and electric vehicle) who contribute to balance the peak and off-peak demand. A projection on Austin, TX showed 16MWh reduction during a 2-h event can be achieved by a justified selection of 20% of residential customers. In the second study, the feasibility of inferring time-of-use (ToU) operation of flexible loads for DR applications was investigated. Unlike several efforts that required considerable model parameter selection or training, we sought to infer ToU from machine learning models without in-situ training. As the first part of this study, the ToU inference from low-resolution 15-minute data (smart meter data) was investigated. A framework was introduced which leveraged the smart meter data from a set of neighbor buildings (equipped with plug meters) with similar energy use behavior for training. Through identifying similar buildings in energy use behavior, the machine learning classification models (including neural network, SVM, and random forest) were employed for inference of appliance ToU in buildings by accounting for resident behavior reflected in their energy load shapes from smart meter data. Investigation on electric vehicle (EV) and dryer for 10 buildings over 20 days showed an average F-score of 83% and 71%. As the second part of this study, the ToU inference from high-resolution data (60Hz) was investigated. A self-configuring framework, based on the concept of spectral clustering, was introduced that automatically extracts the appliance signature from historical data in the environment to avoid the problem of model parameter selection. Using the framework, appliance signatures are matched with new events in the electricity signal to identify the ToU of major loads. The results on ~1500 events showed an F-score of >80% for major loads like AC, washing machine, and dishwasher. In the third study, the problem of demand-supply balance, in the presence of varying levels of small-scale distributed resources (solar panel, battery, and smart load) was investigated. The concept of load complementarity between consumers and prosumers for load balancing among a community of ~250 households was investigated. The impact of different scenarios such as varying levels of solar penetration, battery integration level, in addition to users' flexibility for balancing the supply and demand were quantitatively measured. It was shown that (1) even with 100% adoption of solar panels, the renewable supply cannot cover the demand of the network during afternoon times (e.g., after 3 pm), (2) integrating battery for individual households could improve the self-sufficiency by more than 15% during solar generation time, and (3) without any battery, smart loads are also capable of improving the self-sufficiency as an alternative, by providing ~60% of what commercial battery systems would offer. The contribution of this dissertation is through introducing data-driven solutions/investigations for characterizing the energy behavior of households, which could increase the flexibility of the aggregate daily energy load profiles for a community. When combined, the findings of this research can serve to the field of utility-scale energy analytics for the integration of DR and improved reshaping of network energy profiles (i.e., mitigating the peaks and valleys in daily demand profiles).
Doctor of Philosophy
Buildings account for more than 70% of electricity consumption in the U.S., in which more than 40% is associated with the residential sector. During recent years, with the advancement in Information and Communication Technologies (ICT) and the proliferation of data from consumers and devices, data-driven methods have received increasing attention for improving the energy-efficiency initiatives. With the increased adoption of renewable and distributed resources in buildings (e.g., solar panels and storage systems), an important aspect to improve the efficiency by matching the demand and supply is to add flexibility to the energy consumption patterns (e.g., trying to match the times of high energy demand from buildings and renewable generation). In this dissertation, we introduced data-driven solutions using the historical energy data of consumers with application to the flexibility provision. Specific problems include: (1) introducing a ranking score for buildings in a community to detect the candidates that can provide higher energy saving in the future events, (2) estimating the operation time of major energy-intensive appliances by analyzing the whole-house energy data using machine learning models, and (3) investigating the potential of achieving demand-supply balance in communities of buildings under the impact of different levels of solar panels, battery systems, and occupants energy consumption behavior. In the first study, a ranking score was introduced that analyzes the historical energy data from major loads such as washing machines and dishwashers in individual buildings and group the buildings based on their potential for energy saving at different times of the day. The proposed approach was investigated for real data of 400 buildings. The results for EV, washing machine, dishwasher, dryer, and AC show that the approach could successfully rank buildings by their demand reduction potential at critical times of the day. In the second study, machine learning (ML) frameworks were introduced to identify the times of the day that major energy-intensive appliances are operated. To do so, the input of the model was considered as the main circuit electricity information of the whole building either in lower-resolution data (smart meter data) or higher-resolution data (60Hz). Unlike previous studies that required considerable efforts for training the model (e.g, defining specific parameters for mathematical formulation of the appliance model), the aim was to develop data-driven approaches to learn the model either from the same building itself or from the neighbors that have appliance-level metering devices. For the lower-resolution data, the objective was that, if a few samples of buildings have already access to plug meters (i.e., appliance level data), one could estimate the operation time of major appliances through ML models by matching the energy behavior of the buildings, reflected in their smart meter information, with the ones in the neighborhood that have similar behaviors. For the higher-resolution data, an algorithm was introduced that extract the appliance signature (i.e., change in the pattern of electricity signal when an appliance is operated) to create a processed library and match the new events (i.e., times that an appliance is operated) by investigating the similarity with the ones in the processed library. The investigation on major appliances like AC, EV, dryer, and washing machine shows the >80% accuracy on standard performance metrics. In the third study, the impact of adding small-scale distributed resources to individual buildings (solar panels, battery, and users' practice in changing their energy consumption behavior) for matching the demand-supply for the communities was investigated. A community of ~250 buildings was considered to account for realistic uncertain energy behavior across households. It was shown that even when all buildings have a solar panel, during the afternoon times (after 4 pm) in which still ~30% of solar generation is possible, the community could not supply their demand. Furthermore, it was observed that including users' practice in changing their energy consumption behavior and battery could improve the utilization of solar energy around >10%-15%. The results can serve as a guideline for utilities and decision-makers to understand the impact of such different scenarios on improving the utilization of solar adoption. These series of studies in this dissertation contribute to the body of literature by introducing data-driven solutions/investigations for characterizing the energy behavior of households, which could increase the flexibility in energy consumption patterns.