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Main Authors: Kachhad, Vishal, Joshi, Amit, Glielmo, Luigi
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2511.15321
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author Kachhad, Vishal
Joshi, Amit
Glielmo, Luigi
author_facet Kachhad, Vishal
Joshi, Amit
Glielmo, Luigi
contents This article proposes an optimization problem formulation to find the optimal sizes of Photovoltaics (PV) and Battery Energy Storage Systems (BESS) for individual participants within the context of the Renewable Energy Community (REC). An optimization problem considered the dynamic nature of electricity pricing, solar irradiation levels, financial aspects such as capital investment, and operational and maintenance expenditures of PV and BESS. The analysis also considered replacement costs and the efficiency of charging and discharging the BESS unit. We employed Mixed-Integer Non-Linear Programming (MINLP) to determine the optimal system size that maximizes the Net Present Value (NPV) of individual participants. Furthermore, in this study, we used daily representative signals for each season of the year to reduce simulation runtime. The Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) was used to extract these signals. Then, these representative signals obtained were used in the optimization problem formulation to reduce simulation time and extend our analysis to a wider planning horizon. In addition, the study introduced fairness by applying the individual marginal contribution method to distribute incentives equitably among REC participants, ensuring that each member benefited from their contribution. A simulation study was conducted using a real demand dataset of five houses located in Roseto Valfortore, a small town and commune in the Foggia Province of the Apulia region in southern Italy, to demonstrate the practical relevance and usefulness of the ideas discussed. Ultimately, the goal of the article was to empower the REC with the knowledge necessary to make informed decisions and shape the future of sustainable energy.
format Preprint
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institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Techno-Economic Modelling and Component Sizing in Renewable Energy Communities: A Participant Perspective
Kachhad, Vishal
Joshi, Amit
Glielmo, Luigi
Systems and Control
This article proposes an optimization problem formulation to find the optimal sizes of Photovoltaics (PV) and Battery Energy Storage Systems (BESS) for individual participants within the context of the Renewable Energy Community (REC). An optimization problem considered the dynamic nature of electricity pricing, solar irradiation levels, financial aspects such as capital investment, and operational and maintenance expenditures of PV and BESS. The analysis also considered replacement costs and the efficiency of charging and discharging the BESS unit. We employed Mixed-Integer Non-Linear Programming (MINLP) to determine the optimal system size that maximizes the Net Present Value (NPV) of individual participants. Furthermore, in this study, we used daily representative signals for each season of the year to reduce simulation runtime. The Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) was used to extract these signals. Then, these representative signals obtained were used in the optimization problem formulation to reduce simulation time and extend our analysis to a wider planning horizon. In addition, the study introduced fairness by applying the individual marginal contribution method to distribute incentives equitably among REC participants, ensuring that each member benefited from their contribution. A simulation study was conducted using a real demand dataset of five houses located in Roseto Valfortore, a small town and commune in the Foggia Province of the Apulia region in southern Italy, to demonstrate the practical relevance and usefulness of the ideas discussed. Ultimately, the goal of the article was to empower the REC with the knowledge necessary to make informed decisions and shape the future of sustainable energy.
title Techno-Economic Modelling and Component Sizing in Renewable Energy Communities: A Participant Perspective
topic Systems and Control
url https://arxiv.org/abs/2511.15321