Dissertations / Theses on the topic 'Electricity modelling'
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Katsigiannakis, Konstantinos. "Electricity price risk : modelling the supply stack." Thesis, Imperial College London, 2006. http://hdl.handle.net/10044/1/7429.
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Maiorano, Annalisa. "Modelling and analysis of oligopolistic electricity markets." Thesis, Brunel University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.367886.
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Jędrzejewski, Piotr. "Modelling the European High-voltage electricity transmission." Thesis, KTH, Energiteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-284152.
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This Master’s thesis describes modelling of the cross-border electricity transmission network of Europe. Under this work an extension of The Open Source Energy Model Base for the European Union (OSeMBE) was developed, implementing interconnections to the already existing model. The model is built using the Open Source Energy Modelling System (OSeMOSYS). The purpose of the model is to find cost optimal shape of the electricity system of Europe in the modelling period from 2015 to 2050. The model was used to analyse plans for the development of the electricity interconnection network, defined by the European Union on the list of Projects of Common Interests. For the thesis four scenarios of the European electricity system’s future development were modelled. The aim was to analyse on which borders new interconnection capacity would be beneficial and to test the influence of the interconnection development on the whole electricity system, particularly generation capacities and CO2 emissions. The electricity flows were analysed on each border. For a better overview in the analysis four regions were defined. The regions are adequate to the four priority corridors for electricity defined in Trans-European Networks for Energy (TEN-E). The major finding of the scenario that optimized the capacity of the interconnections in Europe, was that only 16% of capacities planned as the PCI are needed to be built. Most of those capacities should be developed in the northern Europe, particularly on the subsea borders Germany-Norway, United Kingdom-Norway, Poland-Lithuania, but also land ones Finland-Sweden, Denmark-Germany. The analysis also included utilization factors of the interconnection lines. However, due to the simplifications and limitation of modelling tool OSeMOSYS, the results needs to be taken with certain dose of caution and may serve only for indicating the direction of further analysis. The work conducted under this Master’s thesis, might also be a base for the future work, such as deeper look on the already obtained data with purpose to find relationship between electricity generation sources being utilized and interconnections utilization. The model might be also improved by implementation interconnection representation to the borders which were omitted here due to the lack of cost data.Detta examensarbetebeskriver modellering av Europas gränsöverskridande elektriska transmissionsnät. Under detta arbete utvecklades en utvidgning av Open Source Energy Model Base för Europeiska unionen (OSeMBE) för implementering av sammankopplingar med den redan existerande modellen. Modellen är byggd med hjälp av Open Source Energy Modeling System (OSeMOSYS). Syftet med modellen är att hitta en kostnadseffektiv form av Europas elsystem under modelleringsperioden 2015 till 2050. Modellen användes för att validera planer för utveckling av sammankoppling för elnätet, definierade av Europeiska unionen i listan över projekt av gemensamt intresse. Under denna avhandling modellerades fyra scenarier för det europeiska elsystemets framtida utveckling. Målet för scenarierna var att analysera för vilka gränser en ny sammankopplingskapacitet skulle vara till nytta, samt att testa påverkan av samtrafikutvecklingen på hela elsystemet, särskilt produktionskapacitet och koldioxidutsläpp. Därefter analyserades flödena av elektricitet vid varje gräns, och för att förenkla analysen delades området upp i fyra regioner. Regionerna är uppdelade i enlighet med de fyra prioriterade korridorerna för elektricitet, definierade i Transeuropeiska Nät för Energi (TEN-E). Det huvudsakligaresultatet i scenariot som optimerade kapaciteten för sammankopplingarna i Europa var att endast 16% av den kapacitet som planerades som PCI behöver byggas. De flesta av dessa kapaciteter bör utvecklas i norra Europa, särskilt vid havsgränserna Tyskland-Norge, Storbritannien-Norge, Polen-Litauen, men också Finland-Sverige och Danmark-Tyskland. Även användningsfaktorer för samtrafikledningarna analyserades i arbetet.
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Fanone, Enzo. "Three Essays on Modelling of Electricity Markets." Doctoral thesis, Università degli studi di Trieste, 2012. http://hdl.handle.net/10077/7424.
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Richardson, Ian. "Integrated high-resolution modelling of domestic electricity demand and low voltage electricity distribution networks." Thesis, Loughborough University, 2011. https://dspace.lboro.ac.uk/2134/7968.
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Assessing the impact of domestic low-carbon technologies on the electricity distribution network requires a detailed insight into the operation of networks and the power demands of consumers. When used on a wide-scale, low-carbon technologies, including domestic scale micro-generation, heat pumps, electric vehicles and flexible demand, will change the nature of domestic electricity use. In providing a basis for the quantification of the impact upon distribution networks, this thesis details the construction and use of a high-resolution integrated model that simulates both existing domestic electricity use and low voltage distribution networks. Electricity demand is modelled at the level of individual household appliances and is based upon surveyed occupant time-use data. This approach results in a simulation that exhibits realistic time-variant demand characteristics, in both individual dwellings, as well as, groups of dwellings together. Validation is performed against real domestic electricity use data, measured for this purpose, from dwellings in Loughborough in the East Midlands, UK. The low voltage distribution network is modelled using real network data, and the output of its simulation is validated against measured network voltages and power demands. The integrated model provides a highly detailed insight into the operation of networks at a one-minute resolution. This integrated model is the main output of this research, alongside published articles and a freely downloadable software implementation of the demand model.
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Urquhart, Andrew J. "Accuracy of low voltage electricity distribution network modelling." Thesis, Loughborough University, 2016. https://dspace.lboro.ac.uk/2134/21799.
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The connection of high penetrations of new low carbon technologies such as PV and electric vehicles onto the distribution network is expected to cause power quality problems and the thermal capacity of feeder cables may be exceeded. Replacement of existing infrastructure is costly and so feeder cables are likely to be operated close to their hosting capacity. Network operators therefore require accurate simulation models so that new connection requests are not unnecessarily constrained. This work has reviewed recent studies and found a wide range of assumptions and approximations that are used in network models. A number of these have been investigated further, focussing on methods to specify the impedances of the cable, the impacts of harmonics, the time resolution used to model demand and generation, and assumptions regarding the connectivity of the neutral and ground conductors. The calculation of cable impedances is key to the accuracy of network models but only limited data is available from design standards or manufacturers. Several techniques have been compared in this work to provide guidance on the level of detail that should be included in the impedance model. Network modelling results with accurate impedances are shown to differ from those using published data. The demand data time resolution has been shown to affect estimates of copper losses in network cables. Using analytical methods and simulations, the relationship between errors in the loss estimates and the time resolution has been demonstrated and a method proposed such that the accuracy of loss estimates can be improved. For networks with grounded neutral conductors, accurate modelling requires the resistance of grounding electrodes to be taken into account. Existing methods either make approximations to the equivalent circuit or suffer from convergence problems. A new method has been proposed which resolves these difficulties and allows realistic scenarios with both grounded and ungrounded nodes to be modelled. In addition to the development of models, the voltages and currents in a section of LV feeder cable have been measured. The results provide a validation of the impedance calculations and also highlight practical difficulties associated with comparing simulation models with real measurement results.
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Sayin, Ipek. "Modelling Electricity Demand In Turkey For 1998-2011." Master's thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615515/index.pdf.
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This thesis estimates the quarterly electricity demand of Turkey. First of all proper seasonal time series model are found for the variables: electricity demand, temperature, gross domestic product and electricity price. After the right seasonal time series model are found Hylleberg, Engle, Granger and Yoo (1990) test is applied to each variable. The results of the test show that seasonal unit roots exist for the electricity price even it cannot be seen at the graph. The other variables have no seasonal unit roots when the proper seasonal time series model is chosen. Later, the cointegration is tested by looking at the vector autoregressive model. As the cointegration is seen vector error correction model is found. There is long-run equilibrium when the price is the dependent variable and independent variable is gross domestic product. Temperature is taken as exogenous variable and demand is not statistically significant.
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Figueroa, Marcelo Gustavo. "Modelling electricity markets : swing options and hybrid models." Thesis, Birkbeck (University of London), 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.439778.
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Ma, Yuning. "Statistical modelling of rural distribution networks." Thesis, Queen's University Belfast, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.269157.
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Chan, Kam Fong. "Modelling short-term interest rates and electricity spot prices /." [St. Lucia, Qld.], 2006. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe19289.pdf.
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Thomas, Stuart John, and stuart thomas@rmit edu au. "Modelling Commodity Prices in The Australian National Electricity Market." RMIT University. Economics, Finance and Marketing, 2007. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080528.160806.
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Beginning in the early 1990s several countries, including Australia, have pursued programs of deregulation and restructuring of their electricity supply industries. Dissatisfaction with state-run monopoly suppliers and a desire for increased competition and choice for consumers have been the major motivations for reform. In Australia, the historical, vertically-integrated, government-owned electricity authorities were separated into separate generation, transmission, distribution and retail sectors in each State and a competitive, wholesale market for electricity, the National Electricity Market (NEM) began operation in December 1998. The goal of deregulation was (and remains) increased competition in electricity supply, so that consumers may enjoy wider choice and lower prices. The first benefit has largely been delivered but it is arguable whether the second benefit of lower prices has been realised. Increased competition has come at the price of increased wholesale price volatility, which brings with it increased cost as market participants seek to trade profitably and manage the increase in price risk. In the NEM, generators compete to sell into a pool market and distributors purchase electricity from the pool at prices determined by demand and supply, on a half-hourly basis. These market-clearing prices can be extremely volatile. Electricity prices are generally characterised by significant seasonal patterns, on an intra-day, weekly and monthly basis, as demand and supply conditions vary. Prices are also characterised by strong mean-reversion and extremely high spikes in price. While long-run mean prices typically range between $30 and $45 per megawatt hour, prices can spike to levels above $9,000 or $10,000 per megawatt hour from time to time. These spikes tend to be sporadic and very short-lived, rarely lasting for more than an hour or two. Although infrequent, spikes are the major contributor to price volatility and their evolution and causes need to be investigated and understood. The purpose of this thesis is to investigate and model Australian electricity prices. The research work presented is mostly empirical, with the early analytical chapters focusing on investigating the presence and significance of seasonal factors and spikes in electricity price and demand. In subsequent chapters this work is extended into analysis of the underlying volatility processes and the interaction between extreme values in demand and price is specifically investigated. The findings of the thesis are that while the characteristics of strong seasonal patterns and spikes that are generally observed in similar electricity markets are present in the NEM in both price and demand, there is significant variation in their presence and effect between the regional pools. The study also finds that while time-varying volatility is evident in the price series there is again some variation in the way this is characterised between states. A further finding challenges the accepted wisdom that demand peaks drive price spikes at the extremes and shows empirically that price spikes are more likely to be caused by supply disruptions than extremes of demand. The findings provide useful insight into this highly idiosyncratic but economically important national market.
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Karakatsani, Nektaria. "Modelling the structural properties of high-frequency electricity prices." Thesis, London Business School (University of London), 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.428484.
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Heuberger, Clara Franziska. "Electricity system modelling for optimal planning and technology valuation." Thesis, Imperial College London, 2018. http://hdl.handle.net/10044/1/60646.
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This dissertation explores the field of electricity systems modelling and optimisation. We develop new tools, techniques, and concepts to advance systems and technology analysis. Based on a process systems engineering approach, we apply mixed-integer linear programming (MILP) to develop least-cost optimisation models of a national-scale power system in different temporal and complexity variations. The Electricity Systems Optimisation models integrate detailed power plant operation and long-term systems planning to overcome limitations of existing models for technology and system design. We present implementation strategies to include endogenous technology learning and myopic versus perfect foresight planning considering disruptive events. This is enabled through data processing and MILP reformulation techniques developed and applied in this work. We further introduce a new technology valuation metric, the System Value (SV), which quantifies the reduction in total system cost caused upon the deployment of a power generation or storage technology. Unlike purely cost-based metrics, the SV enables a fair comparison of different power technologies taking the whole-system impacts of deployment into account. We find that the SV of a given technology is a function of its penetration level and initial configuration of the system. In a future United Kingdom setting, grid-level energy storage provides the greatest value under a premise of decarbonisation and maintaining security of supply. Additionally, dispatchable and flexible low-carbon power generation, such as Carbon Capture and Storage equipped power plants prove particularly valuable in being able to accommodate higher levels of intermittent renewable power generation and providing ancillary services. On a systems level, we find that including endogenous technology learning in power systems planning emphasises the economic advantage of early investments in low-carbon technology. Myopic power systems planning can lead to sub-optimal capacity expansion. Even under the possibility of breakthrough technologies becoming available before mid-century, deploying existing low-carbon technologies early on proves advantageous from an economic and climate perspective.
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Davis, Stephen. "Mathematical modelling and risk management in deregulated electricity markets." Master's thesis, University of Cape Town, 2005. http://hdl.handle.net/11427/19139.
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In this thesis we aim to explore how electricity generation companies cope with the transition to a competitive environment in a newly deregulated electricity industry. Analyses and discussions are generally performed from the perspective of a Generator/Producer, otherwise they are undertaken with respect to the market as a whole. The techniques used for tackling the complex issues are diverse and wide-ranging as ascertained from the existing literature on the subject. The global ideology focuses on combining two streams of thought: the production optimisation and equilibrium techniques of the old monopolistic, cost-saving industry and; the new dynamic profit-maximising and risk-mitigating competitive industry. Financial engineering in a new and poorly understood market for electrical power must now take place in conjunction with - yet also constrained by - the physical production and distribution of the commodity.
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Bilton, Mark Julian. "Electricity demand : measurement, modelling and management of UK homes." Thesis, Imperial College London, 2011. http://hdl.handle.net/10044/1/8977.
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The need to achieve a transition to a low carbon economy has renewed interest in "energy efficiency" and what has become known as "demand side management". This thesis investigates the role of measurement and modelling in the management of domestic electricity demand. Practice and policy have, since the 1950s, tended to favour a "supply paradigm" centred on the imperative of increasing energy supply. Despite the upheaval of market liberalisation, and twenty years of climate change debate, the domestic electricity "culture" has changed very little. The first half of this thesis contributes to this subject by describing the complex development of the electricity system that we are familiar with today. Drawing upon technical, social and political themes, the current and emerging practices of measurement, modelling, and management are critiqued. It is argued that current practices require revaluation, if alternative, decentralised approaches are to receive a fair analysis. The thesis contributes in empirical terms by extending the evidence base and developing modelling tools for the analysis of domestic electricity use. Field data collected by the author concerning the power flow characteristics of domestic appliances are presented which identify the dynamic nature of domestic electrical loads. A modelling framework is then introduced that combines social and technical aspects of domestic energy demand, allowing synthesis of domestic load profiles and allowing comparison between localised interventions.
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Gamba, Anthony <1993>. "Modelling electricity price and determination of the futures price." Master's Degree Thesis, Università Ca' Foscari Venezia, 2020. http://hdl.handle.net/10579/16331.
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We discuss the characteristics of the electricity and its price in order to find suitable models for the specification of the fair futures price. The non-storability feature makes this commodity different from the others bringing several consequences in the determination of its price. Another difference with other commodities is that electricity has regional markets instead of global markets due to the fact that it is not simple to transport energy. It is also linked to other commodities such as natural gas because electricity can be produced from other sources of energy, and of course, this contributes to the formation of power prices. The consumption of electricity is also linked to the weather, so its usage is conditional to the seasons, implying evidence of seasonality in its time series. All these interesting features forced the researchers to find appropriate models to explain the behaviour of electricity spot prices because these models can be used for the determination of the forward prices. In this thesis we analyse the characteristics of electricity and its price, we discuss some of the models used in literature for the power price and the models to determine a fair futures price. The final part of the thesis is dedicated to the application of a model for the electricity spot price using real market data. Then, we want to determine if this model is a good choice for the determination of futures prices using futures contracts traded in the market.
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Dodds, Gordon Ivan. "Modelling and forecasting electricity demand using aggregate and disaggregate data." Thesis, Queen's University Belfast, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.306073.
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Donaghy, Brian George. "Object-oriented modelling for improved utilisation of electricity distribution networks." Thesis, Queen's University Belfast, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.388084.
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Jalkenäs, Frida, and Monika Mizgalewicz. "Modelling resources to supply Ethiopia with renewable electricity by 2030." Thesis, KTH, Industriell ekologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-213925.
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Energy is a crucial factor when it comes to development. Among other electricity is important when advancing the living standards of a society as it facilitates various actions and mechanisms. Through the past years social trends such as increased population have put energy and electricity systems under stress as they have often been based on limited and unsustainable fossil fuels. A need for a shift from the conventional fuels to renewable sources becomes more prominent and development needs to be performed in a sustainable way. Ethiopia is one of the countries who have expressed a desire to reach sustainable development by adapting United Nations’ Sustainable Development Goals. This project focuses and analyzes more specifically Ethiopia’s relation to, and possibility of reaching Goal 7 - sustainable energy for all. It attempts to find a future configuration of energy sources which will create an electricity system which will benefit the economy, the social aspect and the environment. The aim is to have a cost-efficient energy mix which supplies all of Ethiopia’s inhabitants with electricity without having to contribute with any carbon dioxide emissions. A literature review is performed to obtain country specific information such as geographical predispositions, and a field trip to Addis Ababa is conducted where data regarding the electricity system is collected. Modelling is then carried through by usage of tools MoManI and OnSSET and the obtained results show a continuous trend in all scenarios where solar and wind compromise the biggest part of electricity production in 2030 and after. Every scenario also allows all inhabitants access to electricity by year 2030. Further, four out of five scenarios ensures elimination of carbon dioxide emissions by 2022, and all five by 2030.
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Risquez, Martin Arnau. "Modelling of bidding strategies on the day-ahead electricity market." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-266113.
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Electricity generation coming from variable renewable energy sources is and has beenincreasing significantly. Because of the unpredictability attached to their behavior, fossil fuelpower plants and other renewables have to offer a higher degree of flexibility compared to thepast. In Germany, one of the countries with a greater involvement in renewable energygeneration, the share of renewable energy sources has grown from 14.6% in 2012 to a 29.2%in 2018. Consequently, fossil fuel power plants are forced into more start up and downoperations, making cycling costs higher.This thesis, under the project of improving the agent-based simulation of the DLR’s Instituteof Engineering Thermodynamics of Stuttgart, AMIRIS, contributes to the assessment ofcycling costs in the bidding of power point operators by creating new bidding strategies forAMIRIS that cover the aforementioned cycling cost. These strategies are designed with theoverall objective of maximizing the power plant operator’s profit.The new designed bidding strategies are first implemented in a Python simulation beforebeing introduced in the agent-based environment. Consequently, results of both simulationsare presented in this report, always paying close attention to the comparison between biddingwith these new strategies and bidding under short term marginal cost.In AMIRIS, when applying these new strategies to a very small part of the power plant park,the day-ahead electricity market clearing is almost identical, and these new bidding strategiesyield higher profit to the power plant operator than bidding under short term marginal cost.On the contrary, when applying these new designed bidding strategies to the whole powerplant park, the marginal clearing price suffers greatly from non-accounted interaction betweenthe operators’ bidding and its impact on the clearing of the market.Det har skett och pågår fortfarande en stor utbyggnad av elproduktion från kontinuerligtvarierande förnybara energikällor. På grund av prognososäkerheten i dessa kraftverksproduktion måste andra förnybara kraftverk eller fossileldade kraftverk tillhandahållaflexibilitet i högre utsträckning än tidigare. I Tyskland, som är ett av de länder som har detstörsta inslaget av varierande elproduktion, har andelen förnybar elproduktion ökat från14,6% 2012 till 29,2% 2018. Detta har medfört att fossileldade kraftverk måste startas ochstoppas oftare, vilket ökar kostaderna.Det här arbetet ingår i ett projekt för att förbättra den agent-baserade simuleringsmodellenAMIRIS från DLR Institute of Engineering Thermodynamics of Stuttgart. Arbetet bidrar tillatt inkludera kostnader för start och stopp i elproducenters budgivning genom att skapa nyabudstrategier i AMIRIS. Dessa strategier är utformade med det allmänna målet att maximeraelproducentens vinst.De nya budstrategierna implementeras först i en simulering i Python innan de introduceras iden agent-baserade simuleringsmiljön. Resultaten från båda simuleringarna presenteras i denhär rapporten och noggranna jämförelser görs mellan budgivning med dessa nya strategieroch budgivning baserad på kortsiktig marginalkostnad.Då dessa nya strategier tillämpades på en mycket liten andel av kraftverken i AMIRIS såförblev elpriserna mer eller mindre identiska, och de nya strategierna gav en högre vinst än dåelproducenten bjöd utifrån kortsiktig marginalkostnad. Å andra sidan, då alla producenteranvände de nya strategierna, så påverkades elpriserna kraftigt på grund av att samspeletmellan aktörernas bud och inverkan på elpriset inte hade beaktats tillräckligt.
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Do, Yen Thi Kim. "Data Modelling of Electricity Data in Sweden : Pre-study of the Envolve Project." Thesis, Högskolan i Skövde, Institutionen för kommunikation och information, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-5236.
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Electricity has always had a great impact on our daily life. It plays an important role in every aspect of society, economy, and technology of every nation. Sweden among other Nordic countries has always strived to improve its energy landscape. Currently, Nuclear power and Hydroelectricity are the main methods of energy generation in this country. Together with exploring new ways of generating energy without dependency on nuclear power, Sweden also expresses an interest in encouraging households and companies to use energy in an efficient way in order to reduce energy consumption and its associated costs. The scope of this thesis is to review and evaluate various state-of-the-art data analysis tools and algorithms to generate a meaningful consumer behaviour model based on the electricity usage data collected from households in several areas of Sweden. Understanding the demand characteristics for electricity would give electric suppliers more power in shaping their marketing strategies as well as setting appropriate electricity pricing.
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Bagnall, A. J. "Modelling the UK market in electricity generation with autonomous adaptive agents." Thesis, University of East Anglia, 2000. https://ueaeprints.uea.ac.uk/21583/.
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The modern trend in electricity industries around the world is towards privatisation. Increased competition, it is argued, will ultimately benefit the consumer. However, the particular nature of electricity generation and supply means strong regulation of a privatised market will always be necessary. In establishing a privatised industry, decisions need to be made about the mechanisms governing the requirements to meet demand, to maintain the viability of the network and to ensure generators are paid correctly for power generated. Unfortunately, it is unclear what processes to use to achieve these goals while still delivering some benefit to the consumer in the form of reduced electricity costs. This research, sponsored by the National Grid Company, examines whether the application of new ideas in artificial intelligence could offer the potential for gaining insights into the affects of certain market mechanisms on the competitors in the market. Our approach to gaining greater understanding into how the market operates is to adopt an evolutionary economics perspective. We have constructed autonomous adaptive agents to represent the generating companies in a simplified model of the UK market in electricity generation. The main body of the thesis contains a description of the process of developing the model and the agent architecture. Once we were satisfied that the model incorporated some key features of the real world market and that the agents, based on learning classifier systems, were able to perform well in simpler environments, we examined how multiple adaptive agents learn to interact in the simplified model. We conclude that the agents are able to learn how to behave in ways analogous to the observed behaviour of real world generating companies. We then illustrate the potential for this type of economic model by examining how alterations to market structure affect agent behaviour, and investigate to what extent the agents are able to learn how to cooperate for mutual long term benefit.
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Hinderks, Wieger Johan [Verfasser], and Ralf [Akademischer Betreuer] Korn. "Mathematical modelling of German electricity prices / Wieger Hinderks ; Betreuer: Ralf Korn." Kaiserslautern : Technische Universität Kaiserslautern, 2019. http://d-nb.info/1203633467/34.
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Schwarz, Daniel Christopher. "Price modelling and asset valuation in carbon emission and electricity markets." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:7de118d2-a61b-4125-a615-29ff82ac7316.
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This thesis is concerned with the mathematical analysis of electricity and carbon emission markets. We introduce a novel, versatile and tractable stochastic framework for the joint price formation of electricity spot prices and allowance certificates. In the proposed framework electricity and allowance prices are explained as functions of specific fundamental factors, such as the demand for electricity and the prices of the fuels used for its production. As a result, the proposed model very clearly captures the complex dependency of the modelled prices on the aforementioned fundamental factors. The allowance price is obtained as the solution to a coupled forward-backward stochastic differential equation. We provide a rigorous proof of the existence and uniqueness of a solution to this equation and analyse its behaviour using asymptotic techniques. The essence of the model for the electricity price is a carefully chosen and explicitly constructed function representing the supply curve in the electricity market. The model we propose accommodates most regulatory features that are commonly found in implementations of emissions trading systems and we analyse in detail the impact these features have on the prices of allowance certificates. Thereby we reveal a weakness in existing regulatory frameworks, which, in rare cases, can lead to allowance prices that do not conform with the conditions imposed by the regulator. We illustrate the applicability of our model to the pricing of derivative contracts, in particular clean spread options and numerically illustrate its ability to "see" relationships between the fundamental variables and the option contract, which are usually unobserved by other commonly used models in the literature. The results we obtain constitute flexible tools that help to efficiently evaluate the financial impact current or future implementations of emissions trading systems have on participants in these markets.
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Hinderks, Wieger [Verfasser], and Ralf [Akademischer Betreuer] Korn. "Mathematical modelling of German electricity prices / Wieger Hinderks ; Betreuer: Ralf Korn." Kaiserslautern : Technische Universität Kaiserslautern, 2019. http://d-nb.info/1203633467/34.
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Li, Ruomei. "Modelling of active filters for improving power quality." Thesis, University of Bath, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.323585.
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Boulaire, Fanny A. "Compositional agent-based models for electricity distribution networks." Thesis, Queensland University of Technology, 2015. https://eprints.qut.edu.au/90054/12/90054%28thesis%29.pdf.
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This thesis presents a novel approach to building large-scale agent-based models of networked physical systems using a compositional approach to provide extensibility and flexibility in building the models and simulations. A software framework (MODAM - MODular Agent-based Model) was implemented for this purpose, and validated through simulations. These simulations allow assessment of the impact of technological change on the electricity distribution network looking at the trajectories of electricity consumption at key locations over many years.
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Simmons, Daniel. "Hybrid methods for modelling advanced electromagnetic systems using unstructured meshes." Thesis, University of Nottingham, 2016. http://eprints.nottingham.ac.uk/33230/.
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The aim of this project is the conception, implementation, and application of a simulation tool for the accurate modeling of electromagnetic fields within inhomogeneous materials with complex shapes and the propagation of the resulting fields in the surrounding environment. There are many methods that can be used to model the scattering of an electromagnetic field, however one of the most promising for hybridisation is the Boundary Element Method (BEM), which is a surface technique, and the Unstructured Transmission Line Modeling (UTLM) method, which is a volume technique. The former allows accurate description of the scatterer's boundary and the field's radiation characteristics, but cannot model scattering by materials characterized by a non-uniform refraction index. The latter, on the contrary, can model a very broad range of materials, but is less accurate, since it has to rely on approximate absorbing boundary conditions. A method resulting in the hybridisation of BEM and UTLM can be used to construct a tool that takes into account both the interaction with non-uniform tissue and propagation in its environment. The project aims to describe in detail the implementation of the novel method, and deploy it in a heterogeneous distributed computing environment.
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Khashan, Lamia M. A. "Dispersion analysis of two-dimensional unstructured transmission line modelling (UTLM)." Thesis, University of Nottingham, 2015. http://eprints.nottingham.ac.uk/28509/.
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Numerical simulation techniques play an important role due to their flexibility in dealing with a broad range of complex geometries and material responses. This flexibility requires substantial computational time and memory. Most numerical methods use structured grid for graphical discretization, although this approach is straightforward it is not ideal for smoothly curved boundaries. In this thesis the two-dimensional Transmission Line Modelling (TLM) method based on unstructured meshes is adopted. TLM is an established numerical simulation technique that has been employed in a variety of applications area. Using unstructured meshes to discretize the problem domain permits smooth boundary presentation which provides significant enhancement in the flexibility and accuracy of the TLM simulations. An algorithm is developed to implement Unstructured Transmission Line Modelling (UTLM) which is carefully designed for simplicity and scalability of model size. Several examples are employed to test the accuracy and efficiency of the UTLM simulations. Delaunay meshes, as a type of unstructured meshes, provide good quality triangles but have the disadvantage of providing close to zero transmission line length which has impact on the maximum permissible time step for stable operation. In this thesis, a simple perturbation method for relaxing the minimum link length and clustering triangles in pairs is presented, which permits substantial increase in time step and hence computational runtime to be made without compromising the simulation stability or accuracy. Also, a new model for relaxing the short link lines that fall on the boundaries is presented. UTLM method is based on temporal and spatial sampling of electromagnetic fields which results in dispersion. In this thesis, dispersion characteristics of the unstructured TLM mesh are investigated and compared against structured TLM results for different mesh sizes and shapes. Unlike the structured TLM mesh, the unstructured mesh gives rise to spatial mode coupling. Intermodal coupling behaviour is investigated in a statistical manner upon the change of the mesh local characteristics.
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Qadrdan, Meysam. "Modelling of an integrated gas and electricity network with significant wind capacity." Thesis, Cardiff University, 2012. http://orca.cf.ac.uk/24178/.
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The large scale integration of wind generation capacity into an electricity network poses technical as well as economic challenges. In this research, three major challenges introduced by wind including non-correlated power output from geographically dispersed wind farms, wind variability and wind uncertainty were studied. In order to address each of the aforementioned challenges an appropriate modelling approach and case studies were used. The impacts of power output from dispersed wind farms on the Great Britain transmission reinforcement were studied using an optimal DC load flow combined with a power generation model. It was shown that Western and Eastern HVDC links play a crucial role to bypass the Scotland to England transmission bottleneck. The impacts of wind variability on the GB gas and electricity network were investigated through application of the Combined gas and Electricity Network (CGEN) Model. Additional gas storage capacity was shown to be an efficient option to compensate for wind variability. Two-stage and multi-stage stochastic programming models were developed to examine the impact of wind forecast uncertainty on the GB electricity and gas networks. Stochastic modelling approaches were shown to be efficient methods for scheduling and operating the system under wind uncertainty. The key contributions of this thesis are the investigation of the impacts of wind generation variability on the gas network, and development of twostage and multi-stage stochastic programming models of integrated gas and electricity network.
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Coulon, Michael. "Modelling price dynamics through fundamental relationships in electricity and other energy markets." Thesis, University of Oxford, 2009. http://ora.ox.ac.uk/objects/uuid:ddc11641-920f-461f-85cd-a9e6351d9104.
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Energy markets feature a wide range of unusual price behaviour along with a complicated dependence structure between electricity, natural gas, coal and carbon, as well as other variables. We approach this broad modelling challenge by firstly developing a structural framework to modelling spot electricity prices, through an analysis of the underlying supply and demand factors which drive power prices, and the relationship between them. We propose a stochastic model for fuel prices, power demand and generation capacity availability, as well as a parametric form for the bid stack function which maps these price drivers to the spot electricity price. Based on the intuition of cost-related bids from generators, the model describes mathematically how different fuel prices drive different portions of the bid stack (i.e., the merit order) and hence influence power prices at varying levels of demand. Using actual bid data, we find high correlations between the movements of bids and the corresponding fuel prices (coal and gas). We fit the model to the PJM and New England markets in the US, and assess the performance of the model, in terms of capturing key properties of simulated price trajectories, as well as comparing the model’s forward prices with observed data. We then discuss various mathematical techniques (explicit solutions, approximations, simulations and other numerical techniques) for calibrating to observed fuel and electricity forward curves, as well as for pricing of various single and multi-commodity options. The model reveals that natural gas prices are historically the primary driver of power prices over long horizons in both markets, with shorter term dynamics driven also by fluctuations in demand and reserve margin. However, the framework developed in this thesis is very flexible and able to adapt to different markets or changing conditions, as well as capturing automatically the possibility of changes in the merit order of fuels. In particular, it allows us to begin to understand price movements in the recently-formed carbon emissions markets, which add a new level of complexity to energy price modelling. Thus, the bid stack model can be viewed as more than just an original and elegant new approach to spot electricity prices, but also a convenient and intuitive tool for understanding risks and pricing contracts in the global energy markets, an important, rapidly-growing and fascinating area of research.
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Kobayashi, Yuki. "Analysis of Renewable Energy Installationwith Modelling of Electricity Supply System in Japan." Thesis, KTH, Energisystem, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-288913.
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The Great East Japan Earthquake and tremendous tsunami caused the accident of the Fukushima Daiichi Nuclear Power Plant in 2011. In response to this accident, the Japanese government stopped almost all nuclear power plants and shifted to an electricity supply system with slight nuclear power genration and mainly with renewable energies. As the result, the ratio of the electricity generation of fossil fuel power increased larger than 25 % to compensate the nuclear power genration although Japan almost totally depends on imports for fossil fuels. Nevertheless, renewable energy technologies have been slowly installed. Those energy conditions have required to immediately create a well-planned electricity supply system to construct an energy-secure and sustainable society. Therefore, the energy best mix with renewable energy technologies must be built to solve the problems. The process to realize the best mix is urgently required to propose with concrete policies. Policies should effectively give the electricity market incentive of enhancing renewable energy technologies, because private companies manage the electricity supply in the free market in Japan. The current carbon tax policy rules that the tax revenue from carbon tax is spent in the energy-oriented CO2 emissions restraint measures. However, the effects of this for the sustainable society are unclear for civilians. Some subsidies are currently provided to the renewable energy installation by both the government and private funds. However, the current installation capacity of renewable energy technologies indicates that they are not enough. Therefore, effects of the circulation of carbon tax and the subsidy for renewable energy technologies (tax-subsidy circulation) are analysed with actual and simple assumptions in this study.The amount of the subsidy depends on the carbon tax rate in this assumption. Therefore, six scenarios are assumed depending on tax rates and provision of the subsidy. The subsidy is assumed to be spent in capital costs and operation and management costs of renewable energy technologies. The electricity supply systems in each scenario are simulated using OSeMOSYS (Open Source Energy Modeling System). Changes in the electricity production, CO2 emission, cost, tax and the subsidy are analysed based on the simulation results.Although the policies without the subsidy can enhance the installation of renewable energy technologies, it costs the market expensive. On the other hand, spending the tax revenue in the subsidy for the renewable energies can make less monetary impacts on the market. Moreover, the renewable energy production is 10 % higher in HTS (High Tax and Subsidy)-Scenario than in LT (Low Tax)-Scenario. HTS-Scenario can restrict the cost less than LT-Scenario despite double increase of the tax rate, so that the impact on the industry and the impression for the customers seems relatively restricted. However, the tax-subsidy circulation does not suppose the CO2 emissions reduction. Furthermore, the intermittency risk tends to be high in the scenarios of high renewable energy ratio. Therefore, several scenarios are created to solve the problems. The first is to achieve the target of Paris Agreement. Although the simulation can be implemented to achieve the Paris agreement with slightly high cost, the policy is difficult to enforce to only limit the emission. The results of the scenarios above show that renewableenergy technologies in stalled in the beginning are not subsidised. Therefore, HPS (High Predicted Subsidy)-scenario assumes providing the subsidy beforehand as an advance investment. In addition that the renewable energy installation is promoted actively, the target of Paris Agreement can be achieved with slightly high costs. However, the decision of the price can lead economic problems such as the lack of financial resources. Therefore, the government should simultaneously promote to develop the storage technology to smooth the renewable energy generation. It also should promote to decrease the emission from the other sector like a transportation. Even if HPS-Scenario is too drastic to implement due to the extremely high tax, the tax-subsidy circulation with the advance investment is worth discussing as one option to create the sustainable society.Jordbävning med en efterföljande tsunamin orsakade stor förädelse vid kärnkraftverket i Fukushima Daiichi i Japan år 2011. Som svar på denna händelse stoppade den japanska regeringen nästan alla kärnkraftverk och övergick till ett elförsörjningssystem med endast en liten andel från kärnkraft och istället främst baserat på förnybara energikällor. Som ett resultat ökade andel elproduktion från fossilt bränsle med över 25% för att kompensera den minskade kärnkraftgenreringen. Trots att Japan nästan är helt beroroende på import av fossila bränslen så har andelen förnybara energikällor och teknik långsamt ökat.. Dessa omställningar i energibehov har krävt att introducera ett strategiskt elförsörjningssystem för att bygga ett energisäkert och hållbart samhälle.Med avseende på ovanstående behövs förnybara energikällor introducerar i energimixen för att kunna möta behovet. För att få igång denna process krävs konkreta policyer; politiker bör ge effektiva incitament för att förbättra de förnybara teknologierna, detta då privata företag är ansvariga för elförsörjningen på den fria marknaden i Japan. Den nuvarande koldioxidskattepolitiken reglerar att skatteintäkterna från kolskatt spenderas i de energiinriktade koldioxidutsläppsåtgärderna; effekterna av detta för at stöjda ett hållbart samhälle är dock oklart för samhället. Subventioner tillhandahålls för närvarande till förnybar energiinstallation av både regeringen och privata fonder. Den nuvarande installationskapaciteten för förnybar energiteknik indikerar dock att dessa incitament inte räcker. I denna studie studeras därför effekterna av cirkulationen av kolskatt och subventionen för förnybar energiteknikmed faktiska och till viss del enkla antaganden.Subventionens storlek beror på kolskattesatsen i detta antagande; således antas sex scenarier beroende på skattesatser och tillhandahållande av subventionen. Subventionen antas spenderas i kapitalkostnader samt drift och förvaltningskostnader för förnybar energiteknik. Elförsörjningssystemet i Japan i varje scenario simuleras med det långsiktiga energimodellerings verktyget OSeMOSYS (Open Source Energy Modeling System). Förändringar i elproduktion, koldioxidutsläpp, kostnad, skatt och subvention analyseras baserat på simuleringsresultatet.Även om en politik utan subvention kan förbättra installationen av förnybar energiteknik, kostar det marknaden dyrt. Å andra sidan kan utgifterna för skatteintäkterna i subventionen för förnybara energikällor få mindre monetära effekter på marknaden. Dessutom visar resultaten på att förnybar energiproduktion är 10% högre i ett HTS (High Tax and Subsidy) -Scenario än i LT (Low Tax) -Scenario. HTS-scenariot kan begränsa kostnaden till mindre grad än LT-scenariot trots en dubbel ökning av skattesatsen, därmed verkar påverkan på industrin och intrycket för kunderna relativt begränsad. Dock antas inte att skattesubventionen sänker koldioxidutsläppen. Vidare, en periodisk risk tenderar att vara hög i scenarierna vid den höga förnybara energikvoten. Därför utvecklas och utforskas flera scenarier för att lösa problemen. Det första är att uppnå målet för Parisavtalet. Även om simuleringen kan utföras för att uppnå Parisavtalet med något hög kostnad är det svårt att införa politiken för att endast begränsa utsläppet. Resultaten av ovanstående scenarier visar att förnybar energiteknik som introducerats i början inte subventioneras. Därför förutsätter HPS (High Predicted Subsidy) -scenario att subventionen ges i förskott. Förutom att introduktionen av förnybar energi främjas aktivt, så kan även målet för Parisavtal uppnås med något höga kostnader. Beslutet om priset kan dock leda till ekonomiska problem som brist på ekonomiska resurser. Därför bör regeringen samtidigt främja utvecklingen av lagringstekniken för att förenkla produktionen av förnybar energi. Vidare bör det även främjas att minska utsläppen från andra sektorer så som transportsektorn den andra sektorn som en transport. Även om HPS-scenariot är för drastiskt att genomföra på grund av den extremt höga skatten, är skattesubventionen med förskottsinvesteringen värd att diskutera som ett alternativ för att skapa ett hållbart samhälle.
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Liu, Long. "Modelling and Vulnerability Assessment of Intelligent Electricity Networks as Cyber-Physical Systems." Thesis, The University of Sydney, 2017. http://hdl.handle.net/2123/17846.
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The future grid is different from the current system, and requires more interactions between electrical network and data communication network from the end users to generators. The electrical network acts as a power supply for communication nodes, and in turn, the communication network transmits the control messages for the electrical components. Because of this interdependency, any problems exist in either of these networks may threaten the stability of the whole system. We focus on analysing the vulnerability of the interacted power network and communication network from perspectives of topologies and system operation. An interdiction model is proposed considering the security and operation of both power and communication networks to recognise the crucial set of power components. We solve the interdiction problem using a decomposition method with the consideration of the interdependency between power and communication components. We propose a practical smart grid model as two mutually dependent complex networks with improved interlinks allocation strategy. Moreover, we study the problem of intentional attacks targeting to interdependent networks generated with known degree distribution or distribution of interlinks. In both models, each node's degree is correlated with the number of its links that connect to the other network. Detecting the community structure of a power network can effectively improve the availability of the control actions, which can enhance power system's resilience. This work proposes a method to group the power components into overlapping communities based on the linear sensitivity of the electrical network and complex network theory. This work provides a guidance for the design of the distributed power control system and the power system operation planning.
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Eager, Daniel. "Dynamic modelling of generation capacity investment in electricity markets with high wind penetration." Thesis, University of Edinburgh, 2012. http://hdl.handle.net/1842/6264.
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The ability of liberalised electricity markets to trigger investment in the generation capacity required to maintain an acceptable level of security of supply risk has been - and will continue to be - a topic of much debate. Like many capital intensive industries, generation investment suffers from long lead and construction times, lumpiness of capacity change and high uncertainty. As a result, the ‘boom-and-bust’ investment cycle phenomenon, characterised by overcapacity and low prices, followed by power shortages and high prices, is a prominent feature in the debate. Modelling the dynamics of generation investment in market environments can provide insights into the complexities involved and address the challenges of market design. Further, many governments who preside over liberalised energy markets are developing policies aimed at promoting investment in renewable generation. Of particular interest is the mix and amount of generation investment over time in response to policies promoting high penetrations of variable output renewable power such as wind. Consequently, improved methods to calculate expected output, costs and revenue of thermal generation subject to varying load and random independent thermal outages in a power system with a high wind penetration are needed. In this interdisciplinary project engineering tools are applied to an economic problem together with knowledge from numerous other disciplines. A dynamic simulation model of the aggregated Great Britain (GB) generation investment market has been developed. Investment is viewed as a negative feedback control mechanism with current and future energy prices acting as the feedback signal. Other disciplines called upon include the use of stochastic processes to address uncertainties such as future fuel prices, and economic theory to gain insights into investor behaviour. An ‘energy-only’ market setting is used where generation companies use a classical NPV approach together with the Value at Risk criterion for investment decisions. Market price mark-ups due to market power are also accounted for. The model’s ability to simulate the market trends witnessed in GB since early 2001 is scrutinised with encouraging findings reported. A reasonably good agreement of the model with reality, gives a degree of confidence in the realism of future projections. An advancement to the dynamic model to account for expected high wind penetrations is also included. Building on the initial model iteration, the short-term energy market is simulated using probabilistic production costing based on theMix of Normals distribution technique with a residual load calculation (load net of wind output). Wind speed measurement data is combined with the outputs of atmospheric models to assess the availability of the GB wind resource and its relationship with aggregate load. Simulation results for 2010-40 suggest that the GB system may experience increased generation adequacy risk during the mid to late the 2020s. In addition, many new investments are unable to recover their fixed costs. This triggered an investigation into the design of a capacity mechanism within the context of the modelling environment. In light of the ongoing GB market electricity market reform debate, two mechanisms are tested; a strategic reserve tender and a marketwide capacity market. The goal of these mechanisms is to mitigate generation adequacy risk concerns by achieving a target winter peak de-rated capacity margin.
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McDonald, James R. "On spot-pricing based electricity tariffs and the modelling of consumer load response." Thesis, University of Strathclyde, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.506615.
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Prepic, Asmir. "Modelling and Forecast Swedish Electricity Consumption: A Comparison With Vector Error Correction Models." Thesis, Uppsala universitet, Statistiska institutionen, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-256875.
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Kashyap, Poonam. "Modelling least-cost technology and low carbon scenarios for Northern Ireland Electricity market." Thesis, Ulster University, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.603543.
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Northern Ireland is facing significant challenge in terms of carbon emissions reduction targets and energy security concerns over rising prices of fossil fuel. The UK Climate Change Act, 2008 requires net reduction in carbon emissions at least 80% lower than 1990 levels by 2050. Northern Ireland has set regional target to meet the national commitment to reduce carbon emissions by 25% below 1990 levels by 2025. Renewable energy particularly on-shore and off-shore wind will play an important role in the electricity generation mix in order to achieve the national and regional targets. The aim of this thesis is to generate and analyse techno-economic and low-carbon senarios that dictate the future electricity generation and fuel mix for Northern Ireland up to 2050 using TIMES model and identify challenges arising from integrating large amounts of non-dispatchable renewable energy onto an existing electricity network. The TIMES model analyses the future long-term electricity generation technology options while meeting the overall projected electricity demand based on macroeconomic indicators of gross domestic product and population growth trends - high, medium and low growth. The TIMES model utilises a bottom up optimisation approach subject to policy and implementation constraints to identify least-cost technologies and resources mix to meet the electricity demand in an integrated electricity market. The base case scenario results considers that the existing traditional fossil fuel based power plants will run up to 2050 on the same level of installed capacity. However, the additional demand will be met with by more carbon efficient generation technologies such as tidal, wind, and hydro power plants. It also predicts that there is overall drop in carbon emission levels under base case scenario as a result of steady penetration of renewable energy technologies. The NI TIMES model predicts that the exploration of shale gas in Northern Ireland provides energy security but serve a limited purpose in reducing carbon emissions by 29% in 2050 compared with 2010 levels. The modelling results provide credence to the argument that in order to achieve the 80% carbon emissions reduction, 73% share (2801 MW) of renewable energy technologies capacity is required in the Northern Ireland electricity generation portfolio. The renewable technologies for Northern Ireland electricity system will mainly comprise onshore wind, offshore wind and tidal energy in 2050 to achieve national and regional policy targets.
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Jin, Zehui. "Approaches to modelling functional time series with an application to electricity generation data." Thesis, University of Manchester, 2018. https://www.research.manchester.ac.uk/portal/en/theses/approaches-to-modelling-functional-time-series-with-an-application-to-electricity-generation-data(7d430c80-0db4-4657-896b-b5a3802b0072).html.
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We study the half-hourly electricity generation by coal and by gas in the UK over a period of three years from 2012 to 2014. As a highly frequent time series, daily cycles along with seasonality and trend across days can be seen in the data for each fuel. Taylor (2003), Taylor et al. (2006), and Taylor (2008) studied time series of the similar features by introducing double seasonality into the methods for a single univariate time series. As we are interested in the continuous variation in the generation within a day, the half-hourly observations within a day are considered as a continuous function. In this way, a time series of half-hourly discrete observations is transformed into a time series of daily functions. The idea of a time series of functions can also seen in Shang (2013), Shang and Hyndman (2011) and Hyndman and Ullah (2007). We improve their methods in a few ways. Firstly, we identify the systematic effect due to the factors that take effect in a long term, such as weather and prices of fuels, and the intrinsic differences between the days of the week. The systematic effect is modeled and removed before we study the day-by-day random variation in the functions. Secondly, we extend functional principal component analysis (PCA), which was applied on one group of functions in Shang (2013), Shang and Hyndman (2011) and Hyndman and Ullah (2007), into partial common PCA, in order to consider the covariance structures of two groups of functions and their similarities. A test on the goodness of the approximation to the functions given by the common eigenfunctions is also proposed. The idea of bootstrapping residuals from the approximation seen in Shang (2014) is employed but is improved with non-overlapping blocks and moving blocks of residuals. Thirdly, we use a vector autoregressive (VAR) model, which is a multivariate approach, to model the scores on common eigenfunctions of a group such that the cross-correlation between the scores can be considered. We include Lasso penalties in the VAR model to select the significant covariates and refit the selection with ordinary least squares to reduce the bias. Our method is compared with the stepwise procedure by Pfaff (2007), and is proved to be less variable and more accurate on estimation and prediction. Finally, we propose the method to give the point forecasts of the daily functions. It is more complicated than the methods of Shang (2013), Shang and Hyndman (2011) and Hyndman and Ullah (2007) as the systematic effect needs to be included. An adjustment interval is also given along with a point forecast, which represents the range within which the true function might vary. Our methods to give the point forecast and the adjustment interval include the information updating after the training period, which is not considered in the classical predicting equations of VAR and GARCH seen in Tsay (2013) and Engle and Bollerslev (1986).
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Pule, Sarah. "Mixed media modelling of technological concepts in electricity, methods for supporting learning styles." Thesis, Loughborough University, 2014. https://dspace.lboro.ac.uk/2134/14637.
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The overarching objective of this research is to recognize the learning styles of engineering and technology students and to propose pedagogical methods for the comprehension of technological concepts in electricity. The topic of electrical resistor-capacitor (RC) circuits has been chosen because it is fundamental to engineering and technology courses. There is substantial evidence to suggest that students find such a concept difficult to grasp. The focus of the research lies in explicating undergraduate students cognitive structures about RC circuits, and proposing a method related to students learning styles of how these cognitive structures may be enhanced. The main thesis argument claims that the transfer of knowledge from familiar RC circuit configurations to unfamiliar RC circuit configurations does not occur easily even if the problem-space is kept identical. The methodology used in this research is a mixed-method approach employing qualitative and quantitative data-gathering and analysis processes. This research concludes that the reasons for lack of transfer of knowledge stem from conceptual and perceptual constraints. Constraints involve: (a) which analogical models are employed in relation to the RC circuit, (b) how the circuit schematic diagram is drawn, and (c) relations between analogy, circuit schematic diagram, voltage-time graphs and verbal jargon used to describe circuit behaviour. The research presents a variety of novel, custom-designed learning aids which are employed within the research methodology to rectify the lack of transfer of knowledge for the RC circuits considered in the study. The design of these learning aids is based on the concept of embodied cognition and mainly makes use of visual and kinaesthetic means to appeal to students who may have different learning styles. The use of such learning aids is proposed as a complementary teaching strategy. The approach taken in this research and its outcomes are significant because they continue to inform the research and educational communities about how human development may be fostered through engineering and technology education (Barak and Hacker, 2011).
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Ebertsohn, Nolan Wade. "Cable trays and EMC : modelling and measurement." Thesis, Stellenbosch : Stellenbosch University, 2005. http://hdl.handle.net/10019.1/50293.
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Thesis (MScEng)--University of Stellenbosch, 2005.ENGLISH ABSTRACT: Common mode currents are a major source of interference in electrical and electronic systems. A universal solution to counteract common mode interference is to introduce an electromagnetic shield with known characteristics. Cable trays are often used to shield cables from unwanted electromagnetic interference (EM!) and its shielding characteristics are defined in terms of its transfer impedance. This thesis pursues the modelling and measurement of the transfer impedance and mutual inductance of non-magnetic cable trays. Theoretical analysis is firstly employed by means of Maxwell's equations after which method of moments (MoM) simulations are performed in order to determine the transfer impedance and mutual inductance within the interior region of a cable tray. The results obtained through simulation are then validated with measurements conducted with an automatic network analyser (ANA). The computational and measured data are in good agreement and the developed model can be used to predict the transfer impedance in the cross-section of non-magnetic cable trays.
AFRIKAANSE OPSOMMING: Gemenernodus strome is 'n bron van interferensie in elektriese en elektroniese stelsels. 'n Universele oplossing om hierdie gemenernodus interferensie teen werk is om 'n elektromagnetiese skerm met bekende eienskappe te implementeer. Geleier leikanale word dikwels gebruik om kabels teen elektromagnetiese interferensie te beskerm en die afskermings eienskappe word in terme van die kanaal se oordragsimpedansie gedefinieer. Hierdie tesis ondersoek die modelering en meting van die wedersydse induktansie en oordragsimpedansie van nie-magnetiese geleier leikanale. 'n Teoretiese analise word eers uitgevoer deur middel van Maxwell se vergelykings waarna metode van momente (MvM) simulasies uitgevoer word om die oordragsimpedansie en wedersydse induktansie in die interne gebied van 'n leikanaal te bepaal. Die resultate verkry deur simulasie word dan bevestig deur meting wat uitgevoer word met behulp van 'n automatiese netwerk analiseerder (ANA). Die numeriese en gemete data stem goed ooreen en die ontwikkelde model kan deurgaans gebruik word om die oordragsimpedansie in die deursnit area van nie-magnetiese geleier leikanale te voorspel.
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Issaeva, Natalia. "Quantifying the system balancing cost when wind energy is incorporated into electricity generation system." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/3804.
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Incorporation of wind energy into the electricity generation system requires a detailed analysis of wind speed in order to minimize system balancing cost and avoid a significant mismatch between supply and demand. Power generation and consumption in the electricity networks have to be balanced every minute, therefore it is necessary to study wind speed on a one-minute time scale. In this thesis, we examine the statistical characteristics of one-minute average values of wind speed. One-minute wind speed is available from a single site in Great Britain while there are records of ten-minute wind speed available. We apply a modified Gibbs sampling algorithm to generate one-minute wind speed required for optimization modelling from the available ten-minute wind speed. System balancing costs are estimated through optimization modelling of the short-term electricity generation with wind energy contributing to the total supply. Two main drivers of additional system cost caused by wind energy are variability and unpredictability of one-minute wind speed. Further, a linear mathematical optimization model for a problem of short-term electricity generation is presented to calculate an additional balancing cost that appears as a result of wind energy variability. It is then shown that this additional balancing cost can be estimated using the statistical characteristics of wind energy present in the system. The unpredictable characteristic of wind speed is analysed with the techniques of stochastic programming. Uncertainty of the expected wind speed is represented through scenario trees and stochastic linear optimization models are used to calculate the extra cost due to uncertainty. Alternative optimization models are compared by calculating the additional balancing cost and the extent of imbalance between power generation and consumption in the system.
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Babajide, Nathaniel Akinrinde. "The electricity crisis in Nigeria : building a new future to accommodate 20% renewable electricity generation by 2030." Thesis, University of Dundee, 2017. https://discovery.dundee.ac.uk/en/studentTheses/7c6df776-e790-4afc-8970-3877d91a2663.
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As part of efforts to curb the protracted electricity problem in Nigeria, the government enacted the National Renewable Energy and Energy Efficiency Policy (NREEEP) in 2014. Through this policy, the country plans to increase its electricity generation from renewables to 20% by 2030. This thesis investigates the economic feasibility of this lofty goal, and as well determine the best hybrid configuration for off-grid rural/remote power generation across the six geopolitical zones of Nigeria The economic feasibility results, using Long-range Energy Alternative Planning (LEAP) tool, show that the 20% renewables goal in the Nigerian power generation mix by 2030 is economically feasible but will require vast investment, appropriate supportive mechanisms, both fiscal and non-fiscal (especially for solar PV) and unalloyed commitment on the part of the government. Moreover, the techno-economic results with Hybrid Optimization Model for Electric Renewable (HOMER) reveal Small hydro/Solar PV/Diesel generator/Battery design as the most cost-effective combination for power supply in remote/rural areas of Nigeria. Findings also highlight the better performance of this system in terms of fuel consumption and GHGs emission reduction. Lastly, the study identifies factors influencing RE development, and offers strategic and policy suggestions to advance RE deployment in Nigeria.
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Dahlan, Nofri Yenita. "Valuation model for generation investment in liberalised electricity market." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/valuation-model-for-generation-investment-in-liberalised-electricity-market(d7e0e8d1-2bd8-4906-8aa5-c61cb5f46893).html.
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The introduction of a liberalised electricity market has brought a new challenge to generating companies as well as system regulators. Under this more competitive environment, generating companies are exposed to various risks that might compromise their investment return. Moreover, the various risks in the market affect each type of generation technology in a different way; hence influence the technology choice. Furthermore, it is not yet clear whether the investment cycles in a liberalised electricity market will take place in an orderly fashion or whether 'boom and bust' cycles may arise. As a consequence various market designs, investment incentives and policies have been implemented by system regulators to try to ensure the security of supply. Investment decisions under a market with incentive mechanism are even more complicated to model because the generating company needs to forecast the revenue that the new investment will make from both the energy market and the mechanism. This thesis develops some models that could be used by system regulators to study the performance of market designs and by generating companies to assess a new investment under a liberalised electricity market. Three main models have been developed to serve these purposes. A generation expansion model has been developed using Agent-based modelling approach. In this model each generating company makes investment decision taking into account their competitors' investment strategies and the interactions between them. Several incentive mechanisms are also modelled to study their impacts on the generating companies' investment decision and the dynamic of the investments. A more comprehensive investment framework for a generating company to evaluate an investment in a new power plant has also been developed. The framework consists of two stages: 1) it first models the expected future investments and retirements from all the companies in the market and 2) then calculates the market prices and revenues of the new investment against the future system expansion obtained in the first stage. Two investment models have been developed using this framework. The first model is a probabilistic valuation model to assess investment considering risks and uncertainties. The second model is developed to evaluate investment in an oligopoly electricity market taking into account various risk characteristics of different technologies. The investment framework for a generating company to evaluate an investment is also extended so that the generating company can evaluate investments in a market with an incentive mechanism.
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Uhorakeye, Théoneste [Verfasser]. "Modelling electricity supply options for Rwanda in the face of climate change / Théoneste Uhorakeye." Flensburg : Zentrale Hochschulbibliothek Flensburg, 2016. http://d-nb.info/1126984949/34.
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Barton, John P. "A probabilistic method of modelling energy storage in electricity systems with intermittent renewable energy." Thesis, Loughborough University, 2007. https://dspace.lboro.ac.uk/2134/9727.
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A novel probabilistic method has been developed for modelling the operation of energy storage in electricity systems with significant amounts of wind and solar powered generation. This method is based on a spectral analysis of the variations of wind speed and solar irradiance together with profiles of electrical demand. The method has been embodied in two Matlab computer programs: Wind power only: This program models wind power on any time scale from seconds to years, with limited modelling of demand profiles. This program is only capable of modelling stand-alone systems, or systems in which the electrical demand is replaced by a weak grid connection with limited export capacity. 24-hours: This program models wind power, solar PV power and electrical demand, including seasonal and diurnal effects of each. However, this program only models store cycle times (variations within a time scale) of 24 hours. This program is capable of modelling local electrical demand at the same time as a grid connection with import or export capacity and a backup generator. Each of these programs has been validated by comparing its results with those from a time step program, making four Matlab programs in total. All four programs calculate the power flows to and from the store, satisfied demand, unsatisfied demand and curtailed power. The programs also predict the fractions of time that the store spends full, empty, filling or emptying. The results obtained are promising. Probabilistic program results agree well with time step results over a wide range of input data and time scales. The probabilistic method needs further refinement, but can be used to perform initial modelling and feasibility studies for renewable energy systems. The probabilistic method has the advantage that the required input data is less, and the computer run time is reduced, compared to the time step method.
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Doherty, Prince Samuel. "Cost modelling of electricity producing hot dry rock (HDR) geothermal systems in the UK." Thesis, University of Sunderland, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.303214.
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Ye, Yujian. "Modelling and analysing the integration of flexible demand and energy storage in electricity markets." Thesis, Imperial College London, 2016. http://hdl.handle.net/10044/1/58240.
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The emerging Smart Grid paradigm has paved the way for the wide introduction of flexible demand (FD) and energy storage (ES) technologies in power systems, with significant economic, technical, and environmental benefits that will facilitate efficient transition to the low-carbon future. In the deregulated energy sector, the realization of the significant FD and ES flexibility potential should be coupled with their suitable integration in electricity markets. Previous studies have proposed market clearing mechanisms considering FD and ES participation and demonstrated their impact on the system operation. However, these studies have neglected fundamental market complexities, such as modelling and pricing FD non-convexities as well as modelling and analysing the role of FD and ES in imperfect markets. This thesis aims at addressing the above challenges. First of all, a wide literature has demonstrated that uniform marginal pricing cannot generally support competitive equilibrium solutions in markets with non-convexities, yielding surplus sub-optimality effects. Previous work has identified non-convexities associated with the generation side of electricity markets and proposed different approaches to address surplus sub-optimality. This thesis extends this concept to incorporate the demand side. Detailed operational models of different types of FDs capturing their distinct flexibility potentials are proposed. Non-convexities of FD are identified, including options to forgo demand activities as well as discrete and minimum power levels, and resulting surplus sub-optimality effects are demonstrated through simple examples and a larger case study on a test market with day-ahead horizon and hourly resolution. Generalized uplift and convex hull pricing approaches addressing these effects are extended to account for FD non-convexities. Concerning the former, generalized uplift functions for FD participants are proposed, and a new rule is introduced for equitable distribution of the total surplus loss compensation among market participants. Regarding the latter, it is demonstrated that convex hull prices are flattened at periods when FD is scheduled to eliminate surplus sub-optimality associated with the FD ability to redistribute energy requirements across time. Regarding markets with imperfect competition, this thesis provides for the first time theoretical and quantitative evidence of the beneficial impact of FD and ES in limiting market power by the generation side. Quantitative analysis is supported by an equilibrium programming model of the oligopolistic market setting, accounting for the time-coupling characteristics of FD and ES. The decision making process of each strategic electricity producer is modelled through a bi-level optimization problem, which is solved after converting it to a Mathematical Program with Equilibrium Constraints (MPEC) and linearizing the latter through suitable techniques. The oligopolistic market equilibria resulting from the interaction of multiple independent producers are determined by employing an iterative diagonalization method. Case studies on a test market reflecting the general generation and demand characteristics of the GB system quantitatively demonstrate the benefits of FD and ES in limiting generation market power for different scenarios regarding the time-shifting flexibility and location of FD, the size and location of ES, and network congestion, by employing relevant market power metrics from the literature. Furthermore, this thesis explores the market power potential of the FD and ES. Regarding the former, its ability to exercise market power by strategically revealing less time-shifting flexibility to the market is qualitatively analysed through a price-quantity graph in a simplified two-period market. Concerning the latter, although previous studies have demonstrated the ability of large ES units to exercise market power by withholding their capacity, some have adopted modelling approaches exhibiting certain limitations and have not properly analysed the dependency of the extent of exercised market power on ES and system parameters. In this thesis, the decision making process of strategic ES is modelled through a bi-level optimization problem; the upper level determines the optimal extent of capacity withholding at different time periods, maximizing the ES profit, while the lower level represents the market clearing process. This problem is solved after converting it to an MPEC and linearizing the latter through suitable techniques. Case studies on a test market displaying the major generation and demand properties of the GB system quantitatively analyse the extent of capacity withholding and its impact on ES profit and social welfare for different scenarios regarding the size of ES, the characteristics of the generation and demand sides of the market, as well as the location of ES in the presence of network congestion, resorting to relevant market power indexes from the literature.
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Dejvises, Jackravut. "Modelling of flexible heat demand and assessing its value in low carbon electricity systems." Thesis, Imperial College London, 2012. http://hdl.handle.net/10044/1/10144.
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This thesis presents a thermo-electrical modelling approach for demand response services through Heating Ventilation and Air Conditioning (HVAC) systems. The starting point of the approach is to gain insights on the heating and cooling energy required to keep a building at predefined temperature settings. These studies are supported by the simulation engine EnergyPlus, which is used to generate base-case (uncontrolled) consumption scenarios. Then, a number of different control actions are simulated to study how the energy demand and the indoor temperature profile of different buildings react to such control actions. The relations between user’s comfort levels and temperature setting point variations and durations of the control are explored for different types of buildings. In order to map thermal loads to electrical loads, synthetic and general models of reversible HVAC devices are developed through a so-called black-box approach, whereby input-output functions are generated to link the equipment performance to indoor and outdoor temperatures in both heating and cooling operation. A mathematical formulation of these performance functions is developed from real data. A flexible demand strategy algorithm that maximises the benefits of flexible heat demand is finally presented. It allows selection of an optimal combination of control strategies for the different devices involved in the analysis. The algorithm is able to select type, number, and duration of operation of the HVAC systems so as to maximise the sought benefits, e.g., support of system balancing task, network constraint management. This can ultimately lead to facilitate efficient integration of intermittent generation and enhance the utilization of existing network assets in future low carbon electricity systems. The present heating and domestic hot water demands of UK residential buildings have been modelled and validated with the national gas consumption. The model is used to predict future HVAC demand of the UK residential building in year 2050.
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Riaz, Shariq. "Generic Market Modelling for Future Grid Scenario Analysis." Thesis, The University of Sydney, 2017. http://hdl.handle.net/2123/18121.
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Power systems worldwide are moving away from being dominated by large-scale synchronous generation and passive consumers. Instead, in the future, new actors on both the generation and the load side will play an increasingly significant role. On the generation side, there are renewable energy resources (RES) such as wind generation (WG), photovoltaic (PV) and concentrated solar thermal (CST). On the load side, there are demand response (DR), energy storage and price responsive users equipped with a small-scale PV-battery system (called prosumers). The two sides will together shape future grids. However, if connected at a large scale without proper consideration of their effect, they can also jeopardise the reliability and security of electricity supply. For example, the addition of non-synchronous RES will jeopardise the frequency response of the future grids, while the intermittency and variability of RES threats the existing model of electricity supply (supply following demand), complicating balancing and stressing future grids’ ramping capabilities. On the other hand, the inclusion of DR, prosumers and storage without proper consideration of the implications can cause significant changes to the demand profiles and may result in new stresses such as secondary peaks or excessive ramps. In summary, balancing, stability (frequency, voltage, transient) and ultimately reliability are affected by the changes introduced to the future grids’ technology mix. Given that the lifespan of power system assets is well over fifty years, laying out a roadmap to future grid development in an economical fashion without risking its security is a challenging task. The uncertainty of cost, availability and quality of new technologies requires power system planners and policy-makers to evaluate the feasibility and viability of future grids for a diverse range of technology options. To this end, a rigorous and systematic approach is developed in this dissertation to analyse the implications of prosumers, storage and CST on the balancing and stability of future grids. The best features of all these approaches are combined and presented in a single coherent framework. Computation time improvement techniques are then deployed to improve the computational efficiency and solution accuracy. Taken as a whole, the tool will fill the gap to explore the validity of emerging technologies to tackle balancing, stability, security and reliability issues, over a diverse scope of uncertain premises. The tool is developed for an approach to future grids studies called scenario analysis. Traditionally, power systems are planned based on a handful of the most critical scenarios with an aim to find an optimal generation and/or transmission plan. In contradistinction, scenario analysis involves analysing possible evolutionary pathways to facilitate informed decision making by policy-makers and system planners. Specifically, the primary aim of future grids studies is to deal with the uncertainty of long-term decision making and providing outcomes that are technically possible, although explicit costing might be considered. To this end, for any future grids stability framework, the market model is a critical bottleneck. Existing future grids studies mostly look at simple balancing, ignore network constraints and include most of the emerging technologies in an ad hoc fashion. These simplifications are made to combat the high computation time requirement of accurate approaches. Against this backdrop, this dissertation presents: i) a novel optimisation-based models to capture the effects of prosumers (Chapter 2, 3); ii) co-optimise dispatch of PV and CST aggregation to reduce ramping stress on the conventional generators (Chapter 4); iii) efficiently implemented market-based dispatch (Chapter 5); iv) framework for frequency performance assessment of future grids (Chapter 6). In more detail, first, Chapter 2 and 3 develop a novel approach to explicitly model prosumers’ demand in market dispatch (production cost) models. The key novelty of the method is its ability to capture the impact of prosumers without going into specific market structure or control mechanisms, which are computationally expensive. The model is formulated as a bi-level program in which the upper-level unit commitment (UC) problem minimises the total generation cost and the lower-level problem maximises prosumers’ aggregate self-consumption. Unlike the existing bi-level optimisation frameworks that focus on the interaction between the wholesale market and an aggregator, the coupling is through the prosumers’ demand, not through the electricity price. That renders the proposed model market structure agnostic, making it suitable for future grids studies where the market structure is potentially unknown. This model addresses some critical questions such as, How much flexibility can prosumer provide to help with large-scale RES integration? Flexibility is the key to achieve a high RES penetration. One of the major problem in the integration of RES is their intermittent and variable nature. Concentrated solar thermal (CST) presents an excellent resource with inherent flexibility. In contrast to Chapter 2 and 3 (exploring flexibility through DSM), Chapter 4 examines flexibility options from a generation end. In particular, it proposes an RES aggregation (REA) scheme aiming to co-optimise the dispatch of intermittent and dispatchable RES. The principal aim is to keep in check the ramping stress imposed on the conventional generators due to the RES integration. A Stackelberg game is used to capture the interaction between an independent system operator (ISO) and the REA when the ISO tries to minimise the generation cost, while REA seeks to maximise its revenue. This approach also highlights the potential of a ramping market, as proposed by some US studies. In Chapter 5, the utility storage proposed in Chapter 2, prosumers model proposed in Chapter 3, the dispatch model of CST developed in Chapter 4 and inertia constraint detailed in Chapter 6 are combined into a single coherent framework. The addition of these emerging technologies in the energy market model significantly increases the computation burden. Also, to allow for a subsequent stability assessment, an accurate representation of the number of online generation units is required, which affects the power system inertia and the reactive power support capability. This renders a fully-fledged market model computationally intractable, so in Chapter 5 we deploy unit clustering, a rolling-horizon optimisation approach and constraint clipping to improve the computational efficiency. Together, these comprise a computationally efficient market simulation tool (MST) suitable for future grid stability analysis. Finally, developed MST is used in Chapter 6 for a comprehensive frequency performance assessment of the Australian National Electricity Market (NEM). First, an assessment of minimum inertia requirements is presented, followed by a framework for frequency performance assessment of future grids. The maximum non-synchronous instantaneous range from a frequency performance point of view is established for the NEM. Also, to alleviate the deteriorating effects of the high RES penetration on frequency performance, different technical solutions are proposed and discussed. These efforts will empower policy-makers and system planners with the information on safe penetration levels of different technologies while ensuring reliability and security of future grids.
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Gyamfi, Samuel. "Demand Response Assessment and Modelling of Peak Electricity Demand in the Residential Sector: Information and Communcation Requirements." Thesis, University of Canterbury. Mechanical Engineering Department, 2010. http://hdl.handle.net/10092/5063.
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Peak demand is an issue in power supply system when demand exceeds the available capacity. Continuous growth in peak demand increases the risk of power failures, and increases the marginal cost of supply. The contribution of the residential sector to the system peak is quite substantial and has been a subject of discussion internationally. For example, a study done in New Zealand in 2007 attributed about half of system peak load to the residential sector. International research has attributed a significant influence of human behaviour on households energy use. “Demand Response” is a demand side management tool aimed at achieving peak energy demand reduction by eliciting behaviour change. It encompasses energy needs analysis, information provision to customers, behaviour induction, smart metering, and new signalling and feedback concepts. Demand response is far advanced in the industrial and commercial demand sectors. In the residential sector, information barriers and a lack of proper understanding of consumers’ behaviour have impeded the development of effective response strategies and new enabling technologies in the sector. To date, efforts to understanding residential sector behaviour for the purpose of peak demand analysis has been based on pricing mechanism. However, not much is known about the significance of other factors in influencing household customers’ peak electricity demand behaviour. There is a tremendous amount of data that can be analyzed and fed back to the user to influence behaviour. These may include information about energy shortages, supply security and environmental concerns during the peak hours.
This research is intended to begin the process of understanding the importance of some of these factors in the arena of peak energy consumption behaviour.
Using stated preference survey and focus group discussions, information about household customers’ energy use activities during winter morning and evening peak hours was collected. Data about how customers would modify their usage behaviour when they receive enhanced supply constraint information was also collected. The thesis further explores households’ customer demand response motivation with respect to three factors: cost (price), environment (CO2-intensity) and security (risk of black-outs). Householders were first informed about the relationship between these factors and peak demand. Their responses were analyzed as multi-mode motivation to energy use behaviour change.
Overall, the findings suggest that, household customers would be willing to reduce their peak electricity demand when they are given clear and enhanced information. In terms of motivation to reduce demand the results show customers response to the security factor to be on par with the price factor. The Environmental factor also produced a strong response; nearly two-thirds of that of price or security.
A generic modelling methodology was developed to estimate the impact of households’ activity demand response on the load curve of the utility using a combination of published literature reviews and resources, and own research work. This modelling methodology was applied in a case study in Halswell, a small neighbourhood in Christchurch, New Zealand, with approximately 400 households. The results show that a program to develop the necessary technology and provide credible information and understandable signals about risks and consequences of peak demand could provide up to about 13% voluntary demand reduction during the morning peak hours and 8% during the evening peak hours.