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A multi-objective differential evolution algorithm and a constraint handling mechanism based on variables proportion for dynamic economic emission dispatch problems
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DOI：10.1016/j.asoc.2021.107419.png)
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Abstract
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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. (C) 2021 Elsevier B.V. All rights reserved.
Keywords:
Dynamic economic emission dispatch
Multi-objective optimization
Differential evolution
Constraint handling mechanism
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