期刊
IEEE ACCESS
卷 8, 期 -, 页码 16584-16594出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.2965725
关键词
Economic emission dispatch; Kernel search optimization; meta-heuristic algorithm; swarm intelligence
资金
- Science and Technology Development Project of Jilin Province, China [20190302117GX, 20180101334JC]
- Innovation Capacity Construction Project of Jilin Province Development and Reform Commission [2019C053-3]
With the increasing concern over environment protection, Economic Emission Dispatch (EED) problem has received much attention. It is essentially a Multi-objective Optimization Problem, which minimizes both fuel cost and emission pollution simultaneously, as well as meets some system limits. This study transforms EED problem to a single-objective problem with weighted sum method, and then use Newton method to solve the equality constraint iteratively and introduce a common penalty function to deal with the inequality constraint. Moreover, this study tries to propose a new meta-heuristic algorithm inspired by kernel tricks to solve EED problem with no hyper parameters to be tuned. The new algorithm can map a non-linear objective function into a linear one with higher-dimension. Thus the optimization process could be transformed into a linear process, which is more likely to get the optimum solution. When applied in the 3 real-world EED cases with valve point, the new algorithm achieved a better performance compared with other algorithms in the literature.
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