期刊
ENERGY
卷 172, 期 -, 页码 945-957出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2019.02.009
关键词
Ma-OPF problem; Improved NSGA-III; Adaptive elimination; Boundary and closer point
资金
- National Natural Science Foundation of China [61403321]
- Natural Science Foundation of Fujian Province of China [2018J01098]
- Natural Science Foundation of Guangdong Province of China [2014A030310003, 2017A010101003]
This paper formulates the OPF problem as a many-objective OPF (Ma-OPF) problem with consideration of minimizing many objective functions including the total fuel cost (TFC), total emissions (TE), voltage magnitude deviation (VMD), active power loss (APL) and Line-index (L-index) and multiple complicated constraints. An improved NSGA-III (I-NSGA-III) in which an elimination mechanism instead of the original selection mechanism is employed to reduce selection efforts in environment selection operation is proposed to solve this Ma-OPF problem. An adaptive elimination strategy is also introduced to determine which individuals should be eliminated. In addition, I-NSGA-III integrates a boundary and closer point preservation strategy to get better extreme solutions and obtain population diversity. Furthermore, a mixed multi-constraints handling mechanism is used to enhance the feasibility of solutions. The proposed I-NSGA-III and original NSGA-III are compared and tested on IEEE 30-bus, IEEE 57-bus and IEEE 118-bus test systems with different cases and the experimental results demonstrate the competitiveness and effectiveness of the proposed algorithm. (C) 2019 Elsevier Ltd. All rights reserved.
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