Multi-objective distributed generation hierarchical optimal planning in distribution network: Improved beluga whale optimization algorithm

This study constructs a distributed generation (DG) multi-objective hierarchical optimal planning model. A solution method is proposed based on an improved beluga whale optimization algorithm (IBWO). Reasonable planning of the location and capacity of DG access to the distribution network plays an i...

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Vydáno v:Expert systems with applications Ročník 237; s. 121406
Hlavní autoři: Li, Ling-Ling, Fan, Xing-Da, Wu, Kuo-Jui, Sethanan, Kanchana, Tseng, Ming-Lang
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.03.2024
Témata:
Demand respond
Distributed generation
Distribution network
Improved beluga whale optimization algorithm
Multi-objective hierarchical optimal planning model
Multi-objective hierarchical optimal planning model
Improved beluga whale optimization algorithm
Distributed generation
Distribution network
Demand respond
ISSN:0957-4174, 1873-6793
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Shrnutí:This study constructs a distributed generation (DG) multi-objective hierarchical optimal planning model. A solution method is proposed based on an improved beluga whale optimization algorithm (IBWO). Reasonable planning of the location and capacity of DG access to the distribution network plays an important role in minimizing actual power losses, reducing grid operating costs, and improving voltage distribution. The output power of DG has uncertainties and the demand response on the load side can also affect the DG planning; however, previous studies have ignored these two critical factors. This study aims to determine the optimal location and capacity of DG access to distribution network considering the demand response and the uncertainty of DG output power to improve the economic benefit, power quality and energy utilization efficiency. This study proposes an IBWO algorithm with better performance, aiming at the multi-objective, multi-constrained and nonlinear DG planning problem and a DG multi-objective hierarchical optimal planning model is established. The results show that proposed method can reduce the annual comprehensive cost, total voltage deviation and power loss of system by 11.66%, 40.55% and 38.61%.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2023.121406