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An improved GA-based approach for reduced non-discriminatory renewable energy curtailment

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Detalhes bibliográficos
Resumo:The active management of the networks with high penetration of renewable energy sources faces several challenges. To maximize the utilization of low carbon electricity, the curtailment of generator units using renewables should be limited and fair among units. In this work, an attempt has been made to solve the optimal power flow using an improved Genetic Algorithm. The optimal flow formulation is oriented to the efficiency of the network, under the boundary restrictions of limited curtailment of the output of distributed generators based on renewables and non-discriminatory behaviour. The results obtained from a IEEE 14-bus test system have demonstrated the feasibility of this approach.
Autores principais:Pedroso, André Felipe Pereira
Outros Autores:Zanatta, Giuseppe; Ferreira, Ângela P.; Pereira, Ana I.; Amoura, Yahia; Lopes, Rui Pedro; Angelos, Eduardo Werley S. dos; Vasconcelos, Fillipe Matos de; Lemos, Manuel; Pino, Gabriel
Assunto:Solar energy conversion Active distribution network Voltage control
Ano:2023
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso restrito
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB
Descrição
Resumo:The active management of the networks with high penetration of renewable energy sources faces several challenges. To maximize the utilization of low carbon electricity, the curtailment of generator units using renewables should be limited and fair among units. In this work, an attempt has been made to solve the optimal power flow using an improved Genetic Algorithm. The optimal flow formulation is oriented to the efficiency of the network, under the boundary restrictions of limited curtailment of the output of distributed generators based on renewables and non-discriminatory behaviour. The results obtained from a IEEE 14-bus test system have demonstrated the feasibility of this approach.