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Web-based tool for the decision making in photovoltaic/wind farms planning with multiple objectives

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  • Garcia Marrero, Luis Enrique
  • Arzola Ruíz, José

Abstract

Decision-making in energy planning implies a compromise between several criteria. Technical, economic and environmental criteria, have been the most adopted. The lack of a system that, taking into account technical, economic and environmental criteria, proposes to the decision makers detailed and efficient solutions that satisfy their preferences system, in energy planning, based on the projection of photovoltaic/wind farms at national level, motivated the present study. Conceptual mathematical model and detailed mathematical model of the task were elaborated. The criteria taken into account by the model determined four objective functions: the maximization of the generated energy, the minimization of costs, the minimization of the impacted area by photovoltaic farms and the minimization of the impacted area by wind farms. NSGA-II algorithm was selected to serve as a solution method to the multi-objective problem obtained. A web-based tool was developed, which constitutes a decision-making support system in the planning of photovoltaic/wind farms at national level. The integration with geographic information systems allowed the estimation of the energy parameters of the model and led to the complete automation of the tool.

Suggested Citation

  • Garcia Marrero, Luis Enrique & Arzola Ruíz, José, 2021. "Web-based tool for the decision making in photovoltaic/wind farms planning with multiple objectives," Renewable Energy, Elsevier, vol. 179(C), pages 2224-2234.
    • Handle: RePEc:eee:renene:v:179:y:2021:i:c:p:2224-2234
    DOI: 10.1016/j.renene.2021.08.022
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    2. Oliveira, Augusto Cesar Laviola de & Renato, Natalia dos Santos & Martins, Marcio Arêdes & Mendonça, Isabela Miranda de & Moraes, Camile Arêdes & Lago, Lucas Fernandes Rocha, 2023. "Renewable energy solutions based on artificial intelligence for farms in the state of Minas Gerais, Brazil: Analysis and proposition," Renewable Energy, Elsevier, vol. 204(C), pages 24-38.

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