Reconfiguration of distribution networks with simultaneous allocation of distributed generation using the whale optimization algorithm

• Ano de defesa: 2023
• Autor(a) principal: Mahdavi, Elham
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Estadual Paulista (Unesp)
• Palavras-chave em Português: Whale optimization algorithm; Distribution network; Reconfiguration; Power losses; Distributed generation; MATLAB; Algoritmo de otimização de baleias; Rede de distribuição; Reconfiguração; Perdas de potência; Geração distribuída
• Link de acesso: http://hdl.handle.net/11449/250251

Due to the economic interest of the reduction of the power losses and the regulatory requirements regarding voltage levels in steady state, this study offers a computational methodology to assist in the optimization of the power losses and voltage profile in steady state through the distribution network reconfiguration (DNR) and distributed generations (DGs). The power flow execution and the methods of the sophisticated optimization are able to investigate the big combinative problems required to study DNR. The optimization procedure kind utilized in the distribution network is determined based on the size of the network. Approaches that are expensive in terms of computation or prohibitive include direct approaches, but approaches that have acceptable results with less computational expense include heuristic or metaheuristic approaches. In this research, the load flow that is implemented, is the backward-forward sweep method and we intend to use IEEE 33-bus, IEEE 69-bus, 136-bus, and 415-bus systems. Therefore, we consider the simulation of all the systems according to the network layout and proper placement of DGs in the network using the whale optimization algorithm (WOA). The objective function is to reduce power losses by the DNR and the optimal location and size of DG units, but the voltage profile also improves in this problem. Due to the nonlinear, nonconvex and large nature of the problem, the WOA is used to optimize the problem under MATLAB software. The results indicate that the WOA algorithm performs better in terms of power loss reduction and voltage profile improvement when compared with other metaheuristics shown in the chapter of the tests and results.