The expansion of renewable energy sources (RESs) in European Union countries has given rise to the development of Renewable Energy Communities (RECs), which are made up of locally generated energy by these RESs controlled by individuals, businesses, enterprises, and public administrations. There are several advantages for creating these RECs and participating in them, which include social, environmental, and financial. Nonetheless, according to the Renewable Energy Directive (RED II), the idea of RECs has given opportunities for researchers to investigate the behavior from all aspects. These RECs are characterized by energy fluxes corresponding to self-consumption, energy sales, and energy sharing. Our work focuses on a mathematical time-dependent model on an hourly basis that considers the optimization of photovoltaic-based RECs to maximize profit based on the number of prosumers and consumers, as well as the impact of load profiles on the community’s technical and financial aspects using MATLAB software. In this work, REC’s users can install their plant and become prosumers or vice versa, and users could change their consumption habits until the optimum configuration of REC is obtained. Moreover, this work also focuses on the financial analysis of the plant by comparing the Net Present Value (NPV) as a function of plant size, highlighting the advantage of creating a REC. Numerical results have been obtained investigating the case studies of RECs as per the Italian framework, which shows an optimal distribution of prosumers and consumers and an optimal load profile in which the maximum profitability is obtained. Optimization has been performed by considering different load profiles. Moreover, starting from the optimized configurations, an analysis based on the plant size is also made to maximize the NPV. This work has shown positive outcomes and would be helpful for the researchers and stakeholders while designing the RECs.

The Role of Participant Distribution and Consumption Habits in the Optimization of PV Based Renewable Energy Communities / Sassone, A.; Ahmed, S.; Ciocia, A.; Malgaroli, G.; D'Angola, A.. - In: ENERGY ENGINEERING. - ISSN 0199-8595. - ELETTRONICO. - 122:5(2025), pp. 1715-1733. [10.32604/ee.2025.058781]

The Role of Participant Distribution and Consumption Habits in the Optimization of PV Based Renewable Energy Communities

Ciocia A.;Malgaroli G.;
2025

Abstract

The expansion of renewable energy sources (RESs) in European Union countries has given rise to the development of Renewable Energy Communities (RECs), which are made up of locally generated energy by these RESs controlled by individuals, businesses, enterprises, and public administrations. There are several advantages for creating these RECs and participating in them, which include social, environmental, and financial. Nonetheless, according to the Renewable Energy Directive (RED II), the idea of RECs has given opportunities for researchers to investigate the behavior from all aspects. These RECs are characterized by energy fluxes corresponding to self-consumption, energy sales, and energy sharing. Our work focuses on a mathematical time-dependent model on an hourly basis that considers the optimization of photovoltaic-based RECs to maximize profit based on the number of prosumers and consumers, as well as the impact of load profiles on the community’s technical and financial aspects using MATLAB software. In this work, REC’s users can install their plant and become prosumers or vice versa, and users could change their consumption habits until the optimum configuration of REC is obtained. Moreover, this work also focuses on the financial analysis of the plant by comparing the Net Present Value (NPV) as a function of plant size, highlighting the advantage of creating a REC. Numerical results have been obtained investigating the case studies of RECs as per the Italian framework, which shows an optimal distribution of prosumers and consumers and an optimal load profile in which the maximum profitability is obtained. Optimization has been performed by considering different load profiles. Moreover, starting from the optimized configurations, an analysis based on the plant size is also made to maximize the NPV. This work has shown positive outcomes and would be helpful for the researchers and stakeholders while designing the RECs.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/3001236