Simulation of energy scenarios for the transition of an urban neighborhood into a renewable energy community

The design of renewable energy communities requires multi-disciplinary approaches to identify the most promising solutions from technical, economic, and environmental perspectives. Indeed, different simulations tools can be adopted, ranging from urban modelling to energy planning methods. In this framework, this research focused on the Santa Chiara district in Trento, Italy, to assess the performance of different decarbonization strategies, encompassing fossil and renewable energy systems. To achieve this goal, the district energy balance, CO2 emissions, total costs, and impact of incentives for energy communities were analyzed for each scenario. Furthermore, the effects of current and future hot climatic conditions were investigated, coupling urban building energy modelling (umi) and energy planning codes (EnergyPLAN).Results highlighted major modifications to the energy balance of the district due to climate change, with an important increase of space cooling needs. Heat pumps coupled with photovoltaic and solar thermal panels were identified as the most suitable solution, effectively contributing to the transformation of the considered district into an energy community. Finally, the adopted methodology pointed out the relevant role played by different calculation tools when used in an integrated workflow, allowing for a more comprehensive understanding of the available urban decarbonization strategies and more robust design choices.

Authors

Publication Details

Journal
International Journal of Sustainable Energy Planning and Management
Published
2024-10-21
DOI
https://doi.org/10.54337/ijsepm.8235
Citations
5
Primary Topic
Building Energy and Comfort Optimization
Type
article
Field-Weighted Citation Impact
1.33

Funders

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article

Simulation of energy scenarios for the transition of an urban neighborhood into a renewable energy community

Federico Battini, Andrea Gasparella, Diego Viesi, Giovanni Pernigotto et al.
5 citations
International Journal of Sustainable Energy Planning and Management
Building Energy and Comfort Optimization
1.33
article

Simulation of energy scenarios for the transition of an urban neighborhood into a renewable energy community

Federico Battini, Andrea Gasparella, Diego Viesi, Giovanni Pernigotto, Md Shahriar Mahbub, Silvia Ricciuti, A. Sartori, Gregorio Borelli
article en
5 citations

Abstract

The design of renewable energy communities requires multi-disciplinary approaches to identify the most promising solutions from technical, economic, and environmental perspectives. Indeed, different simulations tools can be adopted, ranging from urban modelling to energy planning methods. In this framework, this research focused on the Santa Chiara district in Trento, Italy, to assess the performance of different decarbonization strategies, encompassing fossil and renewable energy systems. To achieve this goal, the district energy balance, CO2 emissions, total costs, and impact of incentives for energy communities were analyzed for each scenario. Furthermore, the effects of current and future hot climatic conditions were investigated, coupling urban building energy modelling (umi) and energy planning codes (EnergyPLAN).Results highlighted major modifications to the energy balance of the district due to climate change, with an important increase of space cooling needs. Heat pumps coupled with photovoltaic and solar thermal panels were identified as the most suitable solution, effectively contributing to the transformation of the considered district into an energy community. Finally, the adopted methodology pointed out the relevant role played by different calculation tools when used in an integrated workflow, allowing for a more comprehensive understanding of the available urban decarbonization strategies and more robust design choices.

International Journal of Sustainable Energy Planning and ManagementVol. 42
European Commission, HORIZON EUROPE Framework Programme
Openalex Percentile: Top 20%
Building Energy and Comfort Optimization
1.33
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