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Multi-objective economic emission dispatch based on an extended crisscross search optimization algorithm
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DOI：10.1016/j.energy.2021.122715.png)
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Abstract
En 中文
In recent years, a novel algorithm named crisscross search optimization (CSO) algorithm has been successfully applied in the conventional energy economic emission dispatch (EED) problems of pure thermal power system (PTPS) and hydrothermal generation system (HTGS). However, there still have some problems, such as slow convergence speed and low stability. To address these issues, an extended crisscross search optimization (ECSO) algorithm is proposed in this paper. The performances of the CSO algorithm are improved by an adaptive choice procedure of the extension coefficient. And a weakening equality constraint method is used in the MOEED problems for ECSO. To test the performance of the proposed algorithm, the IEEE-30 bus System (Test System-I), the 40 generators System (Test System-II) and the hydrothermal generation system (HTGS) (Test System-III) are adopted. Experimental results show that the cost of economic operation and the pollutant emission with the proposed ECSO are minimum in these test systems. Further, the simulation and comparison results show the robustness of the ECSO is superior to the CSO and the other algorithms.
Keywords:
18 September 2021
Multi-objective economic emission dispatch
Crisscross optimization
Adaptive choice procedure of the extension
coef ficient
Weakening equality constraint
Journal
IF:
9.4
Papers:
4.2W
Citations:
20.2W