A multi-objective differential evolution algorithm and a constraint handling mechanism based on variables proportion for dynamic economic emission dispatch problems

Dynamic economic emission dispatch (DEED) problems have become an important research issue in power system operations. It is a multi-objective optimization problem (MOP) with high dimensional, nonlinear, nonsmooth, and nonconvex, considering the power balance constraints, valve point effects, prohib...

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Vydáno v:Applied soft computing Ročník 108; s. 107419
Hlavní autoři: Qiao, Baihao, Liu, Jing, Hao, Xingxing
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.09.2021
Témata:
Constraint handling mechanism
Differential evolution
Dynamic economic emission dispatch
Multi-objective optimization
Differential evolution
Constraint handling mechanism
Multi-objective optimization
Dynamic economic emission dispatch
ISSN:1568-4946, 1872-9681
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Shrnutí:Dynamic economic emission dispatch (DEED) problems have become an important research issue in power system operations. It is a multi-objective optimization problem (MOP) with high dimensional, nonlinear, nonsmooth, and nonconvex, considering the power balance constraints, valve point effects, prohibited operating zones, and ramp rate limits. Therefore, an efficient multi-objective optimization technology is needed to solve conflicting objectives in the DEED problems. Besides, an efficient constraint handling mechanism is the key step in solving real-world problems. In this paper, a proportional dynamic adjustment decision (PDAD) variables method is proposed to deal with the constraints in the DEED problems by considering the difference in the power generation range of the unit. While, the constraint handling mechanism of the slack variable method is improved, and a dynamic slack variable (DSL) method is proposed. Besides, a non-dominant sorting differential evolution algorithm with a self-adaptive parameter operator and a local search operator (NSDESa_LS) is developed to solve the DEED problems. Finally, the performance of the proposed method is compared with state-of-the-art methods on 5-, 10-, and 40-unit systems. The results show that the proposed NSDESa_LS-PDAD method has a superior performance. •A proportional dynamic adjustment decision (PDAD) variable method is proposed.•The constraint handling mechanism of the slack variable method is improved.•An NSDE with self-adaptive parameters and local search operators is developed.•The performance of the proposed method is verified by 5-, 10-, and 40-unit systems.
ISSN:1568-4946
1872-9681
DOI:10.1016/j.asoc.2021.107419