The role of distributed energy systems in European energy transition

Silvia Coccolo, Louis Marc Bruno Delannoy, Dasaraden Mauree, Amarasinghage Tharindu Dasun Perera, Salil Puri, Jean-Louis Scartezzini
ELSEVIER SCIENCE BV, 2019
Article de conférence

Résumé

This study presents a comprehensive analysis on the energy demand and supply of typical European city centers for present time and 2050 horizon according to the Intergovernmental Panel for Climate Change (IPCC) climatic scenario A1B. Building and urban archetypes are modelled to represent the building stock considering thermal characteristics and local climatic conditions of typical city centres in European cities in order to understand the demand. Subsequently, present and future heating and cooling demands for these urban architypes are computed considering present and future climate as well as renovation scenarios. Microgrid systems are designed for the urban archetypes to evaluate the potential for renewable energy integration. Results of the study reveal that a notable reduction in energy demand can be anticipated due to the building renovation. Furthermore, the study reveals that the average renewable energy generation within the micro-grid can be reached up to 52% using solar PV and wind energy after considering grid curtailments for 2050 scenario considering lower grid curtailments. (C) 2019 The Authors. Published by Elsevier Ltd.

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https://infoscience.epfl.ch/record/267711?ln=fr

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Silvia Coccolo, Louis Marc Bruno Delannoy, Dasaraden Mauree, Amarasinghage Tharindu Dasun Perera, Salil Puri, Jean-Louis Scartezzini
ELSEVIER SCIENCE BV, 2019
Article de conférence

Résumé

Official source

https://infoscience.epfl.ch/record/267711?ln=fr

À propos de ce résultat

Concepts associés (22)

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This study presents a comprehensive analysis of typical European city centers energy demand and supply for present time and 2050, according to the Intergovernmental Panel for Climate Change (IPCC) climatic scenario A1B. Two multi-family houses are modeled, adapted and simulated considering local thermal characteristics and climate conditions of twenty-two European countries. An energy hub system is optimized in order to investigate how the micro-grid responds to the renewable energy integration for ten countries. The European heating demand is evaluated to be reduced by half by 2050 (49%) due to the climate change (6%) and refurbishment (43%) effects. Integration of renewable energy sources in most European countries is set to surpass the EU renewable energy targets given proper implementation of appropriate governmental polices coupled with emerging technological advancements in the renewable energy sector.

2019

Chargement

Improving the energy sustainability of a Swiss village through building renovation and renewable energy integration

Silvia Coccolo, Morgane Le Guen, Nahid Mohajeri Pour Rayeni, Lucas Mosca, Amarasinghage Tharindu Dasun Perera, Jean-Louis Scartezzini

The integration of renewable energy technologies and building renovation are the two main procedures for improving energy sustainability of buildings at neighborhood scale. It is difficult, however, to optimize these procedures simultaneously. This study focuses on improving energy sustainability of Hemberg, a Swiss village with a population of about 900, through optimizing these two procedures. For this purpose a computational platform was developed, combining software CitySim, HOMER Pro, QGIS and Rhinoceros. The energy demand on hourly basis for the buildings in the village was analyzed through comparing the current demand with that after retrofitting according to the Swiss energy labels (i) Minergie and (ii) Minergie-P. Swiss energy maps were used to identify the most promising renewable energy sources while three scenarios were considered for solar PV integration and energy system improvements. The first scenario presents the current condition in the village, while the second scenario explores improvements in electricity generation and the third in both electricity and heat generation. The results show that retrofitting of all buildings according to Minergie reduces the space heating demand by 70–85% and reduces the fluctuations in energy demand, thereby allowing the integration of more renewable energy. According to the simulations, building-integrated solar PV panels can cover the total annual energy demand of the village when considering the Minergie and Minergie-P scenarios. However, the energy system assessment shows that it is difficult to reach beyond 60% when integrating non-dispatchable renewable energy technologies. Finally, and more importantly, integration of wind energy at system level has an important impact in the hub.

Elsevier2018

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Improving the energy sustainability of our cities involves the integration of multiple renewable energy technologies into existing energy infrastructure, stretching the capabilities of traditional energy systems to the limit. To consider the transition take place in distributed energy system sector, complex cyber physical interactions need to be adequately modelled, which is not possible with currently used white box models. Furthermore, the volatility of climate conditions and frequent extreme climate events due to climate change as well as climate phenomena at urban scale make it essential to improve the robustness and resilience of energy systems. Again, white box models do not allow sufficient flexibility in the modelling approach. To address these limitations, thesis seeks to optimize distributed energy system design with the help of grey- and black-box techniques. A grey box model based on fuzzy logic is introduced to consider the dispatch strategy when designing electrical hubs. The grey box model shows better performance when optimizing electrical hubs. It has been shown that the method can achieve a renewable energy integration level of up to 80%. However, the grey box model fails to handle complex energy flows within the energy system. Therefore, a black-box method based on reinforcement learning is introduced to consider complex energy systems catering multi-energy services. Reinforcement learning based on a fully connected neural network (FNN), outperforms the grey box model by improving the objective function values by 60%. A convolution neural network improves the objective function values further (by up to 20% compared to FNN). The results reveal that black box models are competent when conducting optimization for complex energy systems. Distributed optimization is introduced to move from a single energy system to an energy internet consisting of several interacting energy systems. The energy internet is optimized considering fully cooperative and non-cooperative scenarios. The optimization algorithm shows a good capability to reach the Epsilon-Nash equilibrium when conducting the optimization. Finally, supervised and transfer learning methods have been introduced when conducting energy system optimization at the regional and national scale, which reduced the computation time by 84%. Stochastic and robust programing methods are introduced to improve the climate flexibility of energy systems. A hybrid stochastic-robust optimization algorithm is developed by extending the novel approach to consider both climate uncertainty and extreme events. A regional climate model provides climate scenarios for the stochastic optimization. The results of the study show that renewable energy technologies such as solar PV and wind can be used to cater 50% of the annual energy demand while guaranteeing a robust operation of the energy system during extreme climate events. The model is then further extended by integrating computational models for urban energy simulation considering urban climate. Results of the analysis show that a performance gap of up to 40 % can be observed when neglecting the influences of urban climate in the design of urban energy systems. In the final part of this thesis, a multi-criterion decision making technique is introduced into the energy system optimization model. This helps decision makers to weight a number of conflicting objectives and to consider impacts at the urban scale.

EPFL2019

Chargement

Improving the energy sustainability of a Swiss village through building renovation and renewable energy integration

Silvia Coccolo, Morgane Le Guen, Nahid Mohajeri Pour Rayeni, Lucas Mosca, Amarasinghage Tharindu Dasun Perera, Jean-Louis Scartezzini

Elsevier2018

EPFL2019