A Techno-Economic Analysis of Renewable Energy Community With Pv Integration in Southern Italy

Research on Renewable Energy Communities (RECs) in Europe has increased recently because of numerous advantages following the expansion of decentralized systems in the energy sector. RECs are characterized by locally generated electricity from renewable energy sources (RESs) controlled by individuals, businesses, and public administrations. This article focuses on the development of a mathematical model to investigate the time dependent behavior of renewable energy communities having an overlook on the technical and economic scenario. Three major technical quantities are computed on hourly basis for the evaluation of energy fluxes and for the economic analysis: self-consumption, excess energy, and shared energy. Load data are taken from the electricity bills for the year-2023 and a mathematical model is developed to obtain hourly data starting from monthly consumptions, while PV generation hourly data are taken from the PVGIS tool. Moreover, the work includes economic analysis using the net present value (NPV) method. A case study, in which a REC Model is considered, and the location is taken in southern Italy with different prosumers and consumers having different load profiles. Considering the economic analysis, the profitability with and without PNRR benefits has been calculated with different configurations and one configuration is selected with high profitability. After finding profitability, optimal PV power capacity has been evaluated considering the constraint of greater self-consumed energy and shared energy than the sold energy. Moreover, the analysis is carried out by varying the PV cost and selling price for further investigation.

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Published
2024-11-20
DOI
https://doi.org/10.1109/icetas62372.2024.11120301
Primary Topic
Integrated Energy Systems Optimization
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article
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article

A Techno-Economic Analysis of Renewable Energy Community With Pv Integration in Southern Italy

Shoaib Ahmed Shaikh, Antonio D’Angola, Amjad Ali
Integrated Energy Systems Optimization
article

A Techno-Economic Analysis of Renewable Energy Community With Pv Integration in Southern Italy

Shoaib Ahmed Shaikh, Antonio D’Angola, Amjad Ali
article en

Abstract

Research on Renewable Energy Communities (RECs) in Europe has increased recently because of numerous advantages following the expansion of decentralized systems in the energy sector. RECs are characterized by locally generated electricity from renewable energy sources (RESs) controlled by individuals, businesses, and public administrations. This article focuses on the development of a mathematical model to investigate the time dependent behavior of renewable energy communities having an overlook on the technical and economic scenario. Three major technical quantities are computed on hourly basis for the evaluation of energy fluxes and for the economic analysis: self-consumption, excess energy, and shared energy. Load data are taken from the electricity bills for the year-2023 and a mathematical model is developed to obtain hourly data starting from monthly consumptions, while PV generation hourly data are taken from the PVGIS tool. Moreover, the work includes economic analysis using the net present value (NPV) method. A case study, in which a REC Model is considered, and the location is taken in southern Italy with different prosumers and consumers having different load profiles. Considering the economic analysis, the profitability with and without PNRR benefits has been calculated with different configurations and one configuration is selected with high profitability. After finding profitability, optimal PV power capacity has been evaluated considering the constraint of greater self-consumed energy and shared energy than the sold energy. Moreover, the analysis is carried out by varying the PV cost and selling price for further investigation.

King Fahd University of Petroleum and Minerals (SA), University of Basilicata (IT)
Affordable and clean energy
Openalex Percentile: Top 72%
Integrated Energy Systems Optimization
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