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Capacity Management in Smart Grids Using Greedy Randomized Adaptive Search Procedure and Tabu Search

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Autor(es):
Serrano, Hugo de Oliveira Motta ; Reiz, Cleberton ; Leite, Jonatas Boas
Número total de Autores: 3
Tipo de documento: Artigo Científico
Fonte: PROCESSES; v. 11, n. 8, p. 16-pg., 2023-08-01.
Resumo

Over time, distribution systems have progressed from small-scale systems to complex networks, requiring modernization to adapt to these increasing levels of active loads and devices. It is essential to manage the capacity of distribution networks to support all these new technologies. This work, therefore, presents a method for evaluating the impact of optimal allocation and sizing of DGs and load shedding for response demand programs on distribution networks to improve the reliability and financial performance of electric power systems. The proposed optimization tool uses the Greedy Randomized Adaptive Search Procedure and Tabu Search algorithms. The combined optimization of DG allocation simultaneously with load shedding, reliability indices, load transference, and the possibility of islanded operation significantly improves the quality of the planning proposals obtained by the developed method. The results demonstrate the efficiency and robustness of the proposed method, improving the voltage profile by up to 2.02%, relieving the network capacity, and increasing the load restoration capability and reliability. Statistical analysis is also carried out to highlight the performance of the proposed methodology. (AU)

Processo FAPESP: 15/21972-6 - Otimização do planejamento e da operação de sistemas de transmissão e de distribuição de energia elétrica
Beneficiário:Rubén Augusto Romero Lázaro
Modalidade de apoio: Auxílio à Pesquisa - Temático
Processo FAPESP: 19/07436-5 - Desenvolvimento de técnicas de reconhecimento situacional e controle proativo na melhoria da confiabilidade em redes de distribuição de energia elétrica
Beneficiário:Jonatas Boas Leite
Modalidade de apoio: Auxílio à Pesquisa - Regular