Готові списки джерел за темами / Urban Energy Modelling (UEM)

Добірка наукової літератури з теми "Urban Energy Modelling (UEM)"

Автор: Grafiati
Опубліковано: 14 березня 2023

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Статті в журналах з теми "Urban Energy Modelling (UEM)"

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Bukovszki, Viktor, Ábel Magyari, Marina Kristina Braun, Kitti Párdi, and András Reith. "Energy Modelling as a Trigger for Energy Communities: A Joint Socio-Technical Perspective." Energies 13, no. 9 (May 5, 2020): 2274. http://dx.doi.org/10.3390/en13092274.

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Анотація:
Mainstreaming energy communities has been one of the main challenges in the low-carbon transition of cities. In this sense, urban building energy modelling (UBEM) has an untapped role in enabling energy communities, as simulations on urban models provide evidence-based decision support to reduce risks, engage, motivate and guide actors, assert wider policy goals and regulatory requirements. This accelerating role and the potential of UBEM is not sufficiently understood, as research into energy community focuses on its barriers and impacts, while the research of UBEM is mainly technologically oriented. This review takes a sociotechnical approach to explore whether UBEM is a technological trigger for energy communities, furthering the conceptual framework of transition management. factors influencing energy community progression in different use-cases and stages of their lifecycle are compiled to assess the affordances of distinct capabilities of prevalent UBEM tools. The study provides a guide for energy community planners to UBEM. It matches different tool capabilities to the various stages of the project lifecycle for the different use-cases, equipping them with the means to accelerate the low-carbon transition of cities from the bottom-up. Finally, the study defines a development trajectory oriented towards application in urban sustainability to a rather new UBEM field.
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2

Zygmunt, Marcin, and Dariusz Gawin. "Application of the Renewable Energy Sources at District Scale—A Case Study of the Suburban Area." Energies 15, no. 2 (January 10, 2022): 473. http://dx.doi.org/10.3390/en15020473.

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The protection of the natural environment and countering global warming are crucial worldwide issues. The residential sector has a significant impact on overall energy consumption and associated greenhouse gas emissions. Therefore, it is extremely important to focus on all of the activities that can result in more energy efficient and sustainable city scale areas, preventing global warming. The highest improvement in the energy efficiency of existing buildings is possible by combining their deep refurbishment and the use of renewable energy sources (RES), where solar energy appears to be the best for application in buildings. Modernizations that provide full electrification seem to be a trend towards providing modern, energy efficient and environmentally friendly, smart buildings. Moreover, switching from an analysis at the single building level to the district scale allows us to develop more sustainable neighborhoods, following the urban energy modelling (UEM) paradigm. Then, it is possible to use the energy cluster (EC) concept, focusing on energy-, environmental- and economic-related aspects of an examined region. In this paper, an actual Polish suburban district is examined using the home-developed TEAC software. The software is briefly described and compared with other computer codes applied for UEM. In this study, the examined suburban area is modernized, assuming buildings’ deep retrofitting, the application of RES and energy storage systems, as well as usage of smart metering techniques. The proposed modernizations assumed full electrification of the cluster. Moreover, the examined scenarios show potential electricity savings up to approximately 60%, as well as GHG emission reduction by 90% on average. It is demonstrated that the proposed approach is a valid method to estimate various energy- and environment-related issues of modernization for actual residential clusters.
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Zygmunt, Marcin, and Dariusz Gawin. "Application of Artificial Neural Networks in the Urban Building Energy Modelling of Polish Residential Building Stock." Energies 14, no. 24 (December 9, 2021): 8285. http://dx.doi.org/10.3390/en14248285.

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Анотація:
The development of energy-efficient buildings and sustainable energy supply systems is an obligatory undertaking towards a more sustainable future. To protect the natural environment, the modernization of urban infrastructure is indisputably important, possible to achieve considering numerous buildings as a group, i.e., Building Energy Cluster (BEC). The urban planning process evaluates multiple complex criteria to select the most profitable scenario in terms of energy consumption, environmental protection, or financial profitability. Thus, Urban Building Energy Modelling (UBEM) is presently a popular approach applied for studies towards the development of sustainable cities. Today’s UBEM tools use various calculation methods and approaches, as well as include different assumptions and limitations. While there are several popular and valuable software for UBEM, there is still no such tool for analyses of the Polish residential stock. In this work an overview on the home-developed tool called TEAC, focusing on its’ mathematical model and use of Artificial Neural Networks (ANN). An exemplary application of the TEAC software is also presented.
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4

Nageler, P., A. Koch, F. Mauthner, I. Leusbrock, T. Mach, C. Hochenauer, and R. Heimrath. "Comparison of dynamic urban building energy models (UBEM): Sigmoid energy signature and physical modelling approach." Energy and Buildings 179 (November 2018): 333–43. http://dx.doi.org/10.1016/j.enbuild.2018.09.034.

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5

Faure, Xavier, Tim Johansson, and Oleksii Pasichnyi. "The Impact of Detail, Shadowing and Thermal Zoning Levels on Urban Building Energy Modelling (UBEM) on a District Scale." Energies 15, no. 4 (February 18, 2022): 1525. http://dx.doi.org/10.3390/en15041525.

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Анотація:
New modelling tools are required to accelerate the decarbonisation of the building sector. Urban building energy modelling (UBEM) has recently emerged as an attractive paradigm for analysing building energy performance at district and urban scales. The balance between the fidelity and accuracy of created UBEMs is known to be the cornerstone of the model’s applicability. This study aimed to analyse the impact of traditionally implicit modeller choices that can greatly affect the overall UBEM performance, namely, (1) the level of detail (LoD) of the buildings’ geometry; (2) thermal zoning; and (3) the surrounding shadowing environment. The analysis was conducted for two urban areas in Stockholm (Sweden) using MUBES—the newly developed UBEM. It is a bottom-up physics-based open-source tool based on Python and EnergyPlus, allowing for calibration and co-simulation. At the building scale, significant impact was detected for all three factors. At the district scale, smaller effects (<2%) were observed for the level of detail and thermal zoning. However, up to 10% difference may be due to the surrounding shadowing environment, so it is recommended that this is considered when using UBEMs even for district scale analyses. Hence, assumptions embedded in UBEMs and the scale of analysis make a difference.
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Tsirantonakis, Dimitris, and Nektarios Chrysoulakis. "Earth Observation Data Exploitation in Urban Surface Modelling: The Urban Energy Balance Response to a Suburban Park Development." Remote Sensing 14, no. 6 (March 18, 2022): 1473. http://dx.doi.org/10.3390/rs14061473.

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Cities are developing rapidly as an increasing percentage of the global population resides in urban areas. In the face of climate change, the sustainable development of cities is crucial for the well-being and safety of urban populations. The potential of planning interventions towards improving of urban resilience can be evaluated based on methodological approaches used in the domain of urban climate. In this study, we present how Earth Observation (EO) can be systematically used to evaluate urban planning interventions, based on Urban Surface Models (USM) simulations. More specifically, the impact of a suburban park development in Heraklion, Crete, was assessed based on simulations of the USM SUEWS (Surface Urban Energy and Water Balance Scheme), which was forced by EO data. Multi-source satellite data were analyzed to provide information on urban form, highlighting the importance of EO data in evaluating the environmental sustainability potential of urban planning interventions. The modifications caused by this planning intervention to surface energy fluxes were simulated. The scale (102 m) and the type (no-use vegetated area changed to recreational vegetated) of the intervention triggered minor responses in the Urban Energy Balance (UEB) at neighborhood scale, since the change of the relevant surface fluxes was not greater than 10 W m−2, on average, assuming no irrigation and no important changes in soil moisture. However, the planned substitution of grass and bare soil with paved surfaces and trees was found to increase the overall net change in heat storage, therefore contributing to the urban heat island development.
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Buckley, Niall, Gerald Mills, Samuel Letellier-Duchesne, and Khadija Benis. "Designing an Energy-Resilient Neighbourhood Using an Urban Building Energy Model." Energies 14, no. 15 (July 23, 2021): 4445. http://dx.doi.org/10.3390/en14154445.

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A climate resilient city, perforce, has an efficient and robust energy infrastructure that can harvest local energy resources and match energy sources and sinks that vary over space and time. This paper explores the use of an urban building energy model (UBEM) to examine the potential for creating a near-zero carbon neighbourhood in Dublin (Ireland) that is characterised by diverse land-uses and old and new building stock. UBEMs are a relatively new tool that allows the simulation of building energy demand across an urbanised landscape and can account for building layout, including the effects of overshadowing and the potential for facade retrofits and energy generation. In this research, a novel geographic database of buildings is created using archetypes, and the associated information on dimensions, fabric and energy systems is integrated into the Urban Modelling Interface (UMI). The model is used to simulate current and future energy demand based on climate change projections and to test scenarios that apply retrofits to the existing stock and that link proximate land-uses and land-covers. The latter allows a significant decoupling of the neighbourhood from an offsite electricity generation station with a high carbon output. The findings of this paper demonstrate that treating neighbourhoods as single energy entities rather than collections of individual sectors allows the development of bespoke carbon reducing scenarios that are geographically situated. The work shows the value of a neighbourhood-based approach to energy management using UBEMs.
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Bhavana, M., K. Gupta, and P. K. Pal. "URBAN MICRO CLIMATE MODELLING USING DIFFERENT URBAN PHYISCS SCHEMES AND HIGH RESOLUTION LULC WITH WRF MODEL." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-5 (November 19, 2018): 491–98. http://dx.doi.org/10.5194/isprs-archives-xlii-5-491-2018.

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<p><strong>Abstract.</strong> Urban areas are treated as a single entity by mesoscale urban canopy models (UCM) for assessing the influence of urban morphology on climate. Weather Research and Forecasting Model (WRF) coupled with UCM along with urban physics options to describe the urban features such as Single Layer Urban Canopy Model (SLUCM), Building Energy Parameterization (BEP) and Building Energy Model (BEM) which enumerates the influence of urban features on the local scale other than the bulk parameterization (no urban physics option), which is generally used in most of the operational forecasting models. Besides, WRF model also enables to integrate multi-class Urban Land Use Land Cover (LULC) whereas most of the globally available LULC depict urban area as single urban built-up class. This study aims to analyze performance of high resolution urban LULC and urban physics options for Chandigarh area by downscaling climatic variables up to 1km and its validation with the ground observation data. The inner domain (1<span class="thinspace"></span>km resolution) was configured with default LULC for one set of simulations and multi-class urban LULC for other set of simulations. All the simulations were carried out for 3 days (August 19&amp;ndash;21, 2017) due to computational restrictions by employing all the four urban physics options. It has been found that multi-class urban LULC yielded better results than single class urban built –up simulation when validated with respect to ground observation. The RMSE values for multi-class urban LULC provided less RMSE than single class urban LULC, those are in terms of temperature at 2<span class="thinspace"></span>m, relative humidity and wind speed are 0.91<span class="thinspace"></span>&amp;deg;C, 2.63% and 1.82<span class="thinspace"></span>m/s respectively. Similarly, BEP+BEM urban physics option provided reduced RMSE values than the SLUCM and BEP scheme. The RMSE values in terms of temperature at 2<span class="thinspace"></span>m, relative humidity and wind speed are 1.11<span class="thinspace"></span>&amp;deg;C, 4.39% and 2.62<span class="thinspace"></span>m/s respectively.</p>
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Malhotra, Avichal, Simon Raming, Jérôme Frisch, and Christoph van Treeck. "Open-Source Tool for Transforming CityGML Levels of Detail." Energies 14, no. 24 (December 8, 2021): 8250. http://dx.doi.org/10.3390/en14248250.

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Анотація:
Urban Building Energy Modelling (UBEM) requires adequate geometrical information to represent buildings in a 3D digital form. However, open data models usually lack essential information, such as building geometries, due to a lower granularity in available data. For heating demand simulations, this scarcity impacts the energy predictions and, thereby, questioning existing simulation workflows. In this paper, the authors present an open-source CityGML LoD Transformation (CityLDT) tool for upscaling or downscaling geometries of 3D spatial CityGML building models. With the current support of LoD0–2, this paper presents the adapted methodology and developed algorithms for transformations. Using the presented tool, the authors transform open CityGML datasets and conduct heating demand simulations in Modelica to validate the geometric processing of transformed building models.
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Buckley, Niall, Gerald Mills, Christoph Reinhart, and Zachary Michael Berzolla. "Using urban building energy modelling (UBEM) to support the new European Union’s Green Deal: Case study of Dublin Ireland." Energy and Buildings 247 (September 2021): 111115. http://dx.doi.org/10.1016/j.enbuild.2021.111115.

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Дисертації з теми "Urban Energy Modelling (UEM)"

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TORABI, MOGHADAM SARA. "A New Integrated Multi-Criteria Spatial Decision Support System for urban energy planning in the built environment." Doctoral thesis, Politecnico di Torino, 2018. http://hdl.handle.net/11583/2706337.

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Анотація:
Sustainability contests represent a fundamental challenge to traditional urban development practices and concepts. Reducing energy consumption and greenhouse gas emissions from urban infrastructure and building stock, towards low-carbon cities requires a supportive planning process. In this regard, the use of appropriate tools and methods for addressing complex interactions of Urban Energy Planning (UEP) processes is needed. In particular, the problem of building stock energy consumption in the urban environment is crucial. A major aim of this research is to model energy consumption patterns based on bottom-up statistical-engineering combination methods. These methods evaluate the current status of energy consumption and different future energy saving scenarios to promote sustainable urban planning. However, the choice among urban energy planning scenarios is extensively based on multi-actors and multi-criteria aspects. Therefore, to anchor such a sustainable urban planning, a wider societal consensus building with an earnest and active engagement of relevant stakeholders in the city is essential. For this purpose, stakeholder-oriented approach plays a key role in implementing the effective strategies for urban and regional adaptation. The research, therefore, is also dealing with the integration of participative decisional processes of urban energy planning by organizing different focus groups involving real stakeholders. This fact can help to assess, over a short/long term period, the mix of measures by analyzing meaningful scenarios focused on energy consumptions, environmental impacts, economic and social aspects. The result is the development of a new Multi-Criteria Spatial Decision Support System (MC-SDSS), which is an interactive energetic plug-in in GIS environment using CommunityViz. This tool has been applied to a demonstrator case-study, related to a medium-sized city of the metropolitan area of Turin. However, the methodology used for delivering the tool can be applied to other contexts due to its flexibility. The new MC-SDSS is intended to facilitate the decisional process for stakeholders who can ask “what-if” questions and visualize “if-then” scenarios in a real-time. Moreover, it can explore a range of possible futures for assisting urban planners, policymakers and built environment stakeholders in their efforts to plan, design and manage low-carbon cities. This thesis is part of a national Smart City & Communities project, named “EEB-Zero Energy Buildings in Smart Urban Districts” (www.smartcommunitiestech.it).
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2

Muñoz, Novoa David. "Adaptive urban modelling for solar energy simulations." Doctoral thesis, Universitat de Girona, 2019. http://hdl.handle.net/10803/668194.

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Анотація:
In summary, this thesis proposes to address the problem of simulating physical effects in large urban environments through the use of procedural rules and Level-of-Detail techniques, in order to reduce the computational complexity of these simulations, but at the same time trying to maintain an acceptable accuracy in the results for decision-making. The final results show that it is possible to obtain credible results in different study cases, all with reasonable calculation times, with the user being able to adjust the parameters to obtain the desired balance between accuracy and calculation time.
En resum, aquesta tesi proposa abordar el problema de simular els efectes físics en grans entorns urbans mitjançant l'ús de regles procedimentals i tècniques de nivell de detall, per tal de reduir la complexitat computacional d'aquestes simulacions, però tractant alhora de mantenir una precisió acceptable en els resultats per a la presa de decisions. Els resultats finals mostren que és possible obtenir resultats creïbles en diferents casos d'estudi, tots amb temps de càlcul raonables, amb l'usuari ajustant els paràmetres per obtenir l'equilibri desitjat entre precisió i temps de càlcul.
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3

Cowan, David. "Understanding and modelling thermal energy demand and emissions in urban environments." Thesis, London South Bank University, 2017. http://researchopen.lsbu.ac.uk/1863/.

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Refrigeration, air conditioning and heat pump (RACHP) systems currently account for nearly 20% of UK grid electricity use and over 7% of all UK greenhouse gas emissions. This research project has investigated the sources and levels of emissions from RACHP systems and how the cooling (and heating) energy and emissions from buildings might be reduced by optimizing the building’s design, construction and operation. Analysis of data from site surveys and maintenance logs confirmed that leakage of refrigerant can be a significant contributor to total RACHP emissions. TEWI (total equivalent warming impact) analyses showed that for RACHP systems with high GWP (global warming potential) refrigerants and annual leak rates of 10% or more, direct emissions from refrigerant leakage can exceed the indirect emissions associated with energy use. However, for heat pump and air conditioning systems, with typical leak rates of below 3%, using low GWP refrigerants (GWP = 500 or less), the direct emissions do not make a significant contribution to building emissions. A new dynamic energy balance model and Excel based tool were developed to help improve the understanding of building energy use and emissions. The tool can be used to predict the sensitivity to different building design concepts, features and operation and the parameters of the installed RACHP plant. Results for an office building suggest that the building fabric (with the exception of the glazing) is not necessarily a key factor influencing the total energy use and emissions. However, relatively simple measures to reduce electricity use and to reduce solar gain could each reduce building emissions by 10% or more. Results for a dwelling built to 2006 Building Regulations demonstrated an overheating risk in summer, even with mechanical ventilation, but adding a 2 kW air conditioning unit could prevent overheating, with lower energy use and emissions than a similar dwelling incorporating mechanical ventilation. Climate change simulations for the year 2080 predicted a net increase in energy demand and emissions of about 5% for the office building (mainly associated with the use of grid electricity), implying that the grid carbon factor is likely to be a key determinant of future emissions from such buildings. For dwellings without mechanical ventilation or air conditioning, internal temperatures might rise as high as 40°C in summer months, but a small air conditioning unit could maintain temperatures below 25°C with no increase in total energy use and emissions compared with the present day. For a grid electricity carbon factor reduction of 80%, total emissions for the simulated office building would fall by about 70% and for the dwelling by about 50%.
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4

Sarralde, Tassara Juan José. "Urban modelling for resource performance analysis : evaluating the solar energy potential of cities." Thesis, University of Cambridge, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.648867.

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5

Flower, David Jonathan Mark. "An integrated approach to modelling urban water systems." Monash University. Faculty of Engineering. Department of Civil Engineering, 2009. http://arrow.monash.edu.au/hdl/1959.1/73160.

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Анотація:
The energy consumption and greenhouse gas (GHG) emissions associated with urban water systems have come under scrutiny in recent times, as a result of increasing interest in climate change, to which urban water systems are particularly vulnerable. The approach most commonly taken previously to modelling these results has been to consider various urban water system components in great detail, but in isolation from the rest of the system. This piecewise approach is suboptimal, since it systematically fails to reveal the relative importance of the energy consumption and GHG emissions associated with each system component in the context of the entire urban water system. Hence, it was determined that a new approach to modelling the energy consumption and GHG emissions associated with urban water systems was necessary. It was further determined that the value derived from such a model would be greatly enhanced if it could also model the water consumption and wastewater generation associated with each system component, such that integrated policies could be developed, aimed at minimising water consumption, wastewater generation, energy consumption and GHG emissions concurrently. Hence, the following research question was posed: How should the relationships between the water consumption, wastewater generation, energy consumption and GHG emissions associated with the operation of urban water systems be modelled such that the impact of various changes to the system configuration made at different spatial scales can be determined within the context of the entire system? In this research project, life cycle assessment ideas were employed to develop such a new modelling methodology. Initially, the approach was developed at the building-scale, such that the end uses of water present in a selected building and any associated appliances could be modelled, along with the fraction of the citywide water supply and wastewater systems directly associated with providing services to that building. This vast breadth of scope was delivered by considering only the operational life cycle stage of each urban water system component, excluding both the pre- and post-operational life cycle stages of the associated infrastructure. The value of this pilot model was illustrated by several case studies, focused on residential buildings connected to the centralised water supply and wastewater systems in Melbourne, Australia. Later, the approach was extended to the city-scale by using probabilistic distributions of each input parameter, such that all of the end uses of water present in a city, and all of the associated building-scale appliances could be modelled, along with the associated complete water supply and wastewater systems. The value of this city-scale model was illustrated by applying it to model a hypothetical case study city, resembling Melbourne, Australia in many ways. Due to a lack of data, this application was limited to the residential sector of the case study city, along with the fraction of the citywide water supply and wastewater systems directly associated with providing services to that sector. The results generated by the pilot and city-scale models showed that the new modelling methodology could be employed at a wide range of scales to assess the relative importance of each modelled urban water system component in terms of the specified results. Importantly, the high resolution of those results enabled the identification of the underlying causes of the relative importance of each urban water system component, such that efficient and effective approaches to reducing each result for each system component could be developed. Interestingly, for the specific case studies investigated, it was revealed that some commonly neglected system components were actually extremely important, such as domestic hot water services, a trend found to be largely driven by hot water consumption in showers.
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BOTTACCIOLI, LORENZO. "Modelling and simulation infrastructure for smart energy and renewable technologies integration in urban districts." Doctoral thesis, Politecnico di Torino, 2018. http://hdl.handle.net/11583/2705630.

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Анотація:
The 196 parties attending the conference on climate changes (COP21) in Paris highlighted the need of reducing greenhouse gas emissions [1]. In this regard, in the last years, many countries are providing incentives to promote the deployment of low-carbon and sustainable energy production technologies [2], generation such as Photovoltaic (PV) Systems. The International Energy Agency reports that [3] installation of Renewable Energy Sources (RES), Distributed Generation (DG) and an optimization of consumption with a smart use of energy is required in our cities in order to achieve the goal of reducing green house emissions. ICT technologies, in particular the Internet of Things, enable the possibility of controlling and optimizing consumption [4] hence increasing energy efficiency. The transition from centralized production system to a distributed generation, that can be based on renewable or on conventional sources, substantially modifies the operation of electricity networks: the direction of power flows in the MV lines and even in high voltage/medium voltage (HV/MV) transformers can be reversed, voltage profiles are modified, fault management is affected [5, 6], etc. For all these reasons, distribution networks need to become Smart and new control strategies, algorithms and technologies need to be tested and validated before their implementation and installation in real systems. In this context, ICT play a crucial role in both planning expansion and monitoring operation of distributed energy sources. The crucial roles of ICT and the emerging Internet-of-Things (IoT) are highlighted by the spread diffusion of heterogeneous and pervasive sensors in our houses, district and cities. IoT devices and sensors allow to collect large amounts of energy related data capable of describing the consumption behaviours of the citizens. Hence, the increasing presence of sensors calls for the development of distributed software infrastructure for exploiting such IoT devices for data management and collection. Furthermore, IoT devices enables the possibility of monitoring devices and system in order to develop models for the simulation and optimization on energy process. This Thesis presents a distributed infrastructure, called SMIRSE, for modelling and simulating renewable energy sources and smart policies integration in urban districts. SMIRSE is implemented as a modular infrastructure build with a micro-services approach that exploits Internet of Things communication protocols. This approach enabled interoperability between hardware and software components of the SMIRSE platform and at the mean time its modularity, extendability and scalability. Its modularity allowed the interfacing and integration between dedicated Real-time Grid Simulator, software simulation modules and real-time data in order to model the grid behavior. New modeling and simulation tools for i) Solar energy simulation, with a focus on Photovoltaic systems; ii) Integration of RES and smart policies with the distribution grid; iii) Characterization of thermal performance of Buildings and power consumption prediction; and iv) Buildings indoor temperature simulation and monitoring, have been designed, developed and integrated upon the backbone of the microservices-based infrastructure. The main advantage of the SMIRSE infrastructure is its capability in creating different scenarios for Multi-Energy-System simulation with a minimum effort. Examples of scenarios were SMIRSE can be used are: i) Installation of Renewable Energy Sources, ii) Grid reconfiguration, iii) Demand Response and iv) Demand Side Management. In addition, the proposed infrastructure enables to study the interoperability among different use-cases in a plug-play fashion. Finally, the proposed solution can integrate Smart Metering Architecture to exploit (near-) real-time data collected from the field to co-simulate different smart energy strategies with real information. The main contribution of this study is the design and development of a distributed infrastructure for energy system simulation that exploits state of the art ICT technology. Its worthnothing to say that such ICT technology have been customized for the purpose of developing energy system co-simulation infrastructure.
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7

Bustos, Turu Gonzalo. "Integrated modelling framework for the analysis of demand side management strategies in urban energy systems." Thesis, Imperial College London, 2018. http://hdl.handle.net/10044/1/64780.

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Influenced by environmental concerns and rapid urbanisation, cities are changing the way they historically have produced, distributed and consumed energy. In the next decades, cities will have to increasingly adapt their energy infrastructure if new low carbon and smart technologies are to be effectively integrated. In this context, advanced planning tools can become crucial to successfully design these future urban energy systems. However, it is not only important to analyse how urban energy infrastructure will look like in the future, but also how they will be operated. Advanced energy management strategies can increase the operational efficiency, therefore reducing energy consumption, CO2 emissions, operational costs and network investments. However, the design and analysis of these energy management strategies are difficult to perform at an urban scale considering the spatial and temporal resolution and the diversity in users energy requirements. This thesis proposes a novel integrated modelling framework to analyse flexible transport and heating energy demand and assess different demand-side management strategies in urban energy systems. With a combination of agent-based simulation and multi-objective optimisation models, this framework is tested using two case studies. The first one focuses on transport electrification and the integration of electric vehicles through smart charging strategies in an urban area in London, UK. The results of this analysis show that final consumer costs and carbon emissions reductions (compared to a base case) are in the range of 4.3-45.0% and 2.8-3.9% respectively in a daily basis, depending on the type of tariff and electricity generation mix considered. These reductions consider a control strategy where the peak demand is constrained so the capacity of the system is not affected. In the second case study, focused on heat electrification, the coordination of a group of heat pumps is analysed, using different scheduling strategies. In this case, final consumer costs and carbon emissions can be reduced in the range of 4-41% and 0.02-0.7% respectively on a daily basis. In this case, peak demand can be reduced in the range of 51-62% with respect to the baseline. These case studies highlight the importance of the spatial and temporal characterisation of the energy demand, and the level of flexibility users can provide to the system when considering a heterogeneous set of users with different technologies, energy requirements and behaviours. In both studies, trade-offs between the environmental and economic performance of demand-side management strategies are assessed using a multi-objective optimisation approach. Finally, further applications of the integrated modelling framework are described to highlight its potential as a decision-making support tool in sustainable and smart urban energy systems.
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Elfving, Gustav, and Emil Jansson. "Modelling extensive solar power production in urban and rural areas." Thesis, Uppsala universitet, Fasta tillståndets fysik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-325004.

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Renewable energy sources, in form of solar power, is a growing source of energy. Not only at an industry level but also at a commercial level. Grid-connected, building-applied solar power has increased rapidly and as the implementation of solar energy grows, so does the importance of being able to evaluate locations that are of interest of installations with respect to its potential production and its impact on the electrical grid. In this thesis the energy production for different future scenarios is modelled for BAPV (Building Applied Photovoltaics) in Uppsala and Herrljunga. This is done by using calculation and simulation programs called MATLAB and ArcGIS. The results regarding Uppsala, are used in a report by BEESG (Built Environment Energy Systems Group) at Uppsala University to the Swedish energy agency. The grid impact of installing extensive solar power as concentrated and dispersed in Herrljunga are simulated and evaluated. Both authors has during the process been equally involved in all parts of the thesis in order to get a thorough understanding of the project as a whole. This due to the fact that the different parts of the thesis were dependent of each other (the second part could not be finished until the first were completed etc).
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Skelhorn, Cynthia. "A fine scale assessment of urban greenspace impacts on microclimate and building energy in Manchester." Thesis, University of Manchester, 2014. https://www.research.manchester.ac.uk/portal/en/theses/a-fine-scale-assessment-of-urban-greenspace-impacts-on-microclimate-and-building-energyin-manchester(472ed55f-d66c-440f-acb1-1312880bbc20).html.

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Climate change projections estimate a rise of approximately 3 °C by the 2080‘s for most of the UK (under a medium emissions scenario at 50% probability level, 1961-1990 baseline). Warming is of particular concern for urban areas due to the issues of urban densification and the Urban Heat Island (UHI) effect. To combat warming, one adaptation strategy that has been suggested for urban areas is increasing the proportion of greenspace, such as parks, gardens, street tree plantings, and green roofs. While a number of studies have investigated the cooling effect of greenspace in terms of park size, proximity to a park, or area covered by tree canopy, little is yet known about the specific types of greenspace that contribute to its cooling effectiveness and how this relates to building energy demand. This thesis employs an interdisciplinary approach to model fine-scale changes to greenspace for a temperate northern UK city, linking the resulting microclimate changes to building energy consumption in commercial buildings. Using the urban microclimate model ENVI-met, two study areas (one urban one suburban) were modelled with seven different greenspace scenarios (a base case representing current field conditions, +5% new trees, +5% mature trees, +5% hedges, addition of a green roof on the largest building, changing all current greenspace to grass only, and changing all current greenspace to asphalt only) for a summer day in July 2010. The models were calibrated based on measured air temperature data and then analysed for microclimate changes due to each greenspace scenario. Both the modelled and measured microclimate data were then used to inform a series of building energy models using IES-VE 2012 for three commercial building types, estimating summer cooling and winter heating trade-offs due to greenspace effects. For the most effective scenario of adding 5% mature trees to the urban case study, the microclimate modelling estimates a maximum hourly air temperature reduction of nearly 0.7 °C at 5 pm and surface temperature reductions up to 1.7 °C at 3 pm. In the suburban case study, a 5% increase in mature deciduous trees can reduce mean hourly surface temperatures by 1 °C between 10 am and 5 pm, while the worst case scenario of replacing all current vegetation (20% of the study area) with asphalt results in increased air temperature of 3.2 °C at mid-day. The building energy modelling estimates a reduction of 2.7% in July chiller energy due to the combination of reduced UHI peak hours and eight additional trees (four on the north side and four on the south side) of a three-storey shallow plan building. These energy savings increase to 4.8% under a three-day period of peak UHI conditions. While winter boiler energy usage shows large reductions for a building in an urban location with a low proportion of greenspace (as compared to a suburban location), this benefit is marginal when analysed in terms of carbon trade-offs between summer cooling and winter heating requirements.
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10

Sajjad, Sajjad Hussain. "Observational and modelling approaches to study urban climate : application on Pakistan." Phd thesis, Université de Strasbourg, 2013. http://tel.archives-ouvertes.fr/tel-01044727.

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The objective of this work is to study the urban climate, mainly by focusing on urban temperature trends. The specific focus is to understand the reasons of increase in minimum temperature through observational and modelling techniques. For this purpose, the temperatures data from 1950 to 2004 measured on several meteorological stations of Pakistan is studied and analyzed. Daily averaged annual and seasonal minimum (Tmin) and maximum (Tmax) temperature data of 37 meteorological observatories of Pakistan (17 urban, 7 town and 13 rural) from 1950 to 2004 is first homogenized and then analyzed. The results show that after 1980s Tmin and Tmax increase faster than the period before 1980s at urban areas. During 1980-2004, the increase in Tmin at major urban stations is observed higher than the smaller towns and rural stations. To understand, the effect of the size of the city, changing land use and the building height on the evolution of minimum and maximum temperatures in urban areas has been studied by using the FVM (Finite Volume Model) model and the simulations are run for three days starting at 00:00 (GMT) on 19th day of each month and ending at 00:00 (GMT) on 22nd day of each month. For each month, 48 possible combinations of simulation scenarios are run (4*4*3) and in total, 576 simulations (48*12) are run for a year. The main results show that Tmin and Tmax increase when urban fraction u, city size r and building height h increase. But it is noticed that Tmax increases more than the Tmin when u increases, Tmin increases more than the Tmax when r increases and Tmin increases more than the Tmax when h increases. Among all urban factors (urban fraction u, city size r and building's height h), city size is the major factor that mainly contributes to increase the minimum temperature more than the maximum temperature in urban areas.
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Книги з теми "Urban Energy Modelling (UEM)"

1

Palme, Massimo, and Agnese Salvati, eds. Urban Microclimate Modelling for Comfort and Energy Studies. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65421-4.

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Palme, Massimo, and Agnese Salvati. Urban Microclimate Modelling for Comfort and Energy Studies. Springer International Publishing AG, 2022.

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Palme, Massimo, and Agnese Salvati. Urban Microclimate Modelling for Comfort and Energy Studies. Springer International Publishing AG, 2021.

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Ye, Liu, Jose Porro, and Ingmar Nopens, eds. Quantification and Modelling of Fugitive Greenhouse Gas Emissions from Urban Water Systems. IWA Publishing, 2022. http://dx.doi.org/10.2166/9781789060461.

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Abstract With increased commitment from the international community to reduce greenhouse gas (GHG) emissions from all sectors in accordance with the Paris Agreement, the water sector has never felt the pressure it is now under to transition to a low-carbon water management model. This requires reducing GHG emissions from grid-energy consumption (Scope 2 emissions), which is straightforward; however, it also requires reducing Scope 1 emissions, which include nitrous oxide and methane emissions, predominantly from wastewater handling and treatment. The pathways and factors leading to biological nitrous oxide and methane formation and emissions from wastewater are highly complex and site-specific. Good emission factors for estimating the Scope 1 emissions are lacking, water utilities have little experience in directly measuring these emissions, and the mathematical modelling of these emissions is challenging. Therefore, this book aims to help the water sector address the Scope 1 emissions by breaking down their pathways and influencing factors, and providing guidance on both the use of emission factors, and performing direct measurements of nitrous oxide and methane emissions from sewers and wastewater treatment plants. The book also dives into the mathematical modelling for predicting these emissions and provides guidance on the use of different mathematical models based upon your conditions, as well as an introduction to alternative modelling methods, including metabolic, data-driven, and AI methods. Finally, the book includes guidance on using the modelling tools for assessing different operating strategies and identifying promising mitigation actions. A must-have book for anyone needing to understand, account for, and reduce water utility Scope 1 emissions. ISBN: 9781789060454 (Paperback) ISBN: 9781789060461 (eBook) ISBN: 9781789060478 (ePub)
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Частини книг з теми "Urban Energy Modelling (UEM)"

1

Steemers, Koen, Nick Baker, and Dean Hawkes. "Parametric Energy Modelling for Urban Situations." In 1989 2nd European Conference on Architecture, 282–85. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-017-0556-1_81.

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Kavgic, Miroslava. "Different approaches to urban energy modelling." In Urban Heat Stress and Mitigation Solutions, 162–87. London: Routledge, 2021. http://dx.doi.org/10.1201/9781003045922-9-11.

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Mackey, Hamish R., Saad Hafiz, and Sami G. Al Ghamdi. "Energy Assessment of Seawater Toilet Flushing in Qatar." In New Trends in Urban Drainage Modelling, 963–68. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99867-1_166.

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Fouladvand, Javanshir, Deline Verkerk, Igor Nikolic, and Amineh Ghorbani. "Modelling Energy Security: The Case of Dutch Urban Energy Communities." In Springer Proceedings in Complexity, 393–407. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92843-8_30.

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5

Mao, Jiachen, and Leslie K. Norford. "Urban Weather Generator: Physics-Based Microclimate Simulation for Performance-Oriented Urban Planning." In Urban Microclimate Modelling for Comfort and Energy Studies, 241–63. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65421-4_12.

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6

Nikolopoulou, Marialena. "Thermal Comfort in Urban Spaces." In Urban Microclimate Modelling for Comfort and Energy Studies, 55–77. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65421-4_4.

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7

Di Bernardino, Annalisa, Olga Palusci, Agnese Pini, Giovanni Leuzzi, Marco Cacciani, Armando Pelliccioni, and Paolo Monti. "Air Circulation in Urban Areas." In Urban Microclimate Modelling for Comfort and Energy Studies, 195–221. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65421-4_10.

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Perez, Diane, and Darren Robinson. "Urban Energy Flow Modelling: A Data-Aware Approach." In Communications in Computer and Information Science, 200–220. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29758-8_11.

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9

Marincic, Irene, and Jose Manuel Ochoa. "Urban Microclimatic Conditions in Arid Climates." In Urban Microclimate Modelling for Comfort and Energy Studies, 163–81. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65421-4_8.

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Gupta, Rajat, and Matt Gregg. "Local Energy Mapping Using Publicly Available Data for Urban Energy Retrofit." In Building Information Modelling, Building Performance, Design and Smart Construction, 207–19. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-50346-2_15.

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Тези доповідей конференцій з теми "Urban Energy Modelling (UEM)"

1

FORSBERG, JONAS, and ANNA KROOK-RIEKKOLA. "SUPPORTING CITIES’ EMISSION MITIGATION STRATEGIES: MODELLING URBAN TRANSPORT IN A TIMES ENERGY SYSTEM MODELLING FRAMEWORK." In URBAN TRANSPORT 2017. Southampton UK: WIT Press, 2017. http://dx.doi.org/10.2495/ut170021.

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TRÖNDLE, TIM, and RUCHI CHOUDHARY. "OCCUPANCY BASED THERMAL ENERGY MODELLING IN THE URBAN RESIDENTIAL SECTOR." In ENERGY AND SUSTAINABILITY 2017. Southampton UK: WIT Press, 2017. http://dx.doi.org/10.2495/esus170041.

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Zheng, X. Y., X. Y. Zhan, W. B. Zhang, N. Li, C. Meng, and Y. R. Zhao. "A modelling and optimization toolkit for integrated urban energy system." In 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2). IEEE, 2017. http://dx.doi.org/10.1109/ei2.2017.8245265.

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MATSUOKA, Akiko, Yohei YAMAGUCHI, Yusuke SUZUKI, and Yoshiyuki SHIMODA. "Urban Scale Modelling Of Energy Demand Of Retail Facilities." In 2017 Building Simulation Conference. IBPSA, 2013. http://dx.doi.org/10.26868/25222708.2013.1308.

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YAMAGUCHI, Yohei, Ruchi CHOUDHARY, Adam BOOTH, Yusuke SUZUKI, and Yoshiyuki SHIMODA. "Urban-scale Energy Modelling Of Food Supermarket Considering Uncertainty." In 2017 Building Simulation Conference. IBPSA, 2013. http://dx.doi.org/10.26868/25222708.2013.1172.

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Ghiassi, Neda, Kristopher Hammerberg, Mahnameh Taheri, Ulrich Pont, Owat Sunanta, and Ardeshir Mahdavi. "An Enhanced Sampling-Based Approach to Urban Energy Modelling." In 2015 Building Simulation Conference. IBPSA, 2015. http://dx.doi.org/10.26868/25222708.2015.2161.

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Georgescu, Andrei-Mugur, Sanda-Carmen Georgescu, Luigi Berardi, Daniele B. Laucelli, and Orazio Giustolisi. "Modelling an Urban Groundwater Well Field with WDNetXL/WDNetGIS." In 2019 International Conference on ENERGY and ENVIRONMENT (CIEM). IEEE, 2019. http://dx.doi.org/10.1109/ciem46456.2019.8937595.

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"Governance supporting distributed energy systems for low carbon urban development." In 19th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2011. http://dx.doi.org/10.36334/modsim.2011.h2.bunning.

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"Addressing Pathways to Energy Modelling Through Non-Manifold Topology." In 2018 Symposium on Simulation for Architecture and Urban Design. Society for Modeling and Simulation International (SCS), 2018. http://dx.doi.org/10.22360/simaud.2018.simaud.005.

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Dardanelli, Andrea, Mara Tanelli, Bruno Picasso, Sergio M. Savaresi, Onorino di Tanna, and Mario Santucci. "Control-oriented energy-profiling and modelling of urban electric vehicles." In Control (MSC). IEEE, 2011. http://dx.doi.org/10.1109/cca.2011.6044443.

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