LAPSE:2023.31168
Published Article
LAPSE:2023.31168
Configuration Selection for Renewable Energy Community Using MCDM Methods
Hamza Gribiss, Mohammad Mohsen Aghelinejad, Farouk Yalaoui
April 18, 2023
By 2050, the European Union plans to make Europe the first carbon-neutral continent and a global leader in climate-green industries. Recently, many decisions have been taken in the world to ensure the energy transition from fossil fuel to renewable energy. The creation of renewable energy communities (REC) is among the solutions used to increase this transition. This study presents 16 different configurations for energy self-consumption in RECs containing different industrial factories. One mathematical model is proposed for each configuration, and they have been solved according to different criteria. The comparisons are made between these configurations according to economic, environmental, technical, and social criteria. Then, four multi-criteria decision-making (MCDM) methods are used to choose the best configurations considering all the criteria. For this purpose, the achieved results from the mathematical models are used as input for the MCDM methods. The findings demonstrate that the most effective configurations combine both individual and collective self-consumption. Furthermore, the inclusion of collective production results in multiple advantages, including a 64.71% rise in economic gains, a 26.95% decrease in CO2 emissions, a 21.39% improvement in self-sufficiency, and a significant increase in job creation by 175.24%. In addition, incorporating storage enables a substantial rise in the degree of self-sufficiency, leading to reduced reliance on the power grid and consequent reduction in CO2 emissions.
Keywords
energy self-consumption, mathematical modeling, multi-criteria decision-making (MCDM), Optimization, renewable energy community
Suggested Citation
Gribiss H, Aghelinejad MM, Yalaoui F. Configuration Selection for Renewable Energy Community Using MCDM Methods. (2023). LAPSE:2023.31168
Author Affiliations
Gribiss H: Laboratory of Computer Science and Digital Society (LIST3N), University of Technology of Troyes, 10000 Troyes, France [ORCID]
Aghelinejad MM: Laboratory of Computer Science and Digital Society (LIST3N), University of Technology of Troyes, 10000 Troyes, France
Yalaoui F: Laboratory of Computer Science and Digital Society (LIST3N), University of Technology of Troyes, 10000 Troyes, France
Journal Name
Energies
Volume
16
Issue
6
First Page
2632
Year
2023
Publication Date
2023-03-10
Published Version
ISSN
1996-1073
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Original Submission
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PII: en16062632, Publication Type: Journal Article
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LAPSE:2023.31168
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doi:10.3390/en16062632
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Apr 18, 2023
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