Allocation and smart inverter setting of ground-mounted photovoltaic power plants for the maximization of hosting capacity in distribution networks

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Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD)-
Autor(es): dc.contributorCENTROSUR Electric Distribution Utility-
Autor(es): dc.creatorJaramillo-Leon, Brian-
Autor(es): dc.creatorZambrano-Asanza, Sergio-
Autor(es): dc.creatorFranco, John F.-
Autor(es): dc.creatorSoares, João-
Autor(es): dc.creatorLeite, Jonatas B.-
Data de aceite: dc.date.accessioned2025-08-21T18:02:12Z-
Data de disponibilização: dc.date.available2025-08-21T18:02:12Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2024-03-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1016/j.renene.2024.119968-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/308359-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/308359-
Descrição: dc.descriptionAs the integration of solar photovoltaic (PV) power plants into distribution networks grows, quantifying the amount of PV power that distribution networks can host without harmfully impacting power quality becomes critical. This work aims to determine the best number, location, and size of PV systems to be installed on a distribution feeder, as well as the best control set-points of the PV inverters, to maximize the PV hosting capacity (HC). Therefore, a simulation-optimization framework is proposed for siting and sizing ground-mounted PV power plants equipped with smart inverters (SIs). Single (decentralized) and multiple (distributed) allocations are analyzed by considering the connection of one, two, and three PV systems. Genetic algorithm (GA) and particle swarm optimization (PSO) metaheuristics are employed to solve the optimization problem. The simulation-optimization framework is tested on a real-world feeder model from an Ecuadorian utility. Installing two PV systems with their SIs operating with the Volt-VAr control function yields maximum PV HC, which is increased by 32.1 % compared to a single PV power plant operating at a unity power factor. Moreover, a comparative analysis of the two metaheuristic algorithms reveals that the PSO method provides better results than GA.-
Descrição: dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
Descrição: dc.descriptionDepartment of Electrical Engineering São Paulo State University – UNESP, SP-
Descrição: dc.descriptionResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD), Polytechnic of Porto-
Descrição: dc.descriptionDepartment of Planning CENTROSUR Electric Distribution Utility-
Descrição: dc.descriptionDepartment of Electrical Engineering São Paulo State University – UNESP, SP-
Descrição: dc.descriptionFAPESP: 2015/21972-6-
Descrição: dc.descriptionFAPESP: 2019/07436-5-
Descrição: dc.descriptionCAPES: 88887.817660/2023-00-
Idioma: dc.languageen-
Relação: dc.relationRenewable Energy-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectDistribution network-
Palavras-chave: dc.subjectHosting capacity-
Palavras-chave: dc.subjectMetaheuristic algorithm-
Palavras-chave: dc.subjectPhotovoltaic allocation-
Palavras-chave: dc.subjectPhotovoltaic power plant-
Título: dc.titleAllocation and smart inverter setting of ground-mounted photovoltaic power plants for the maximization of hosting capacity in distribution networks-
Tipo de arquivo: dc.typelivro digital-
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