Adaptive Differential Crisscross Optimization Algorithm for Dynamic Economic Emission Dispatch Considering Wind Power

doi:10.16182/j.issn1004731x.joss.18-0647

Abstract

Abstract: Because of the randomness and fluctuation of the wind power, the large scale wind power integration makes the economic emission dispatch of power systems more complicated. By fusing the advantages of the differential evolution algorithm with the parameter self-adaption and crisscross optimization, a hybrid intelligent optimization algorithm called ADE-CSO is proposed to solve the dynamic economic emission dispatch considering wind power integration. A constraint handling technology is introduced to satisfy the feasibility of the power balance and ramp limits. To demonstrate the effectiveness of the proposed algorithm, a typical test case of five generator bus system is conducted and compared with four other intelligent optimization algorithms. The experiment results show that the proposed ADE-CSO has good optimization performance and global convergence ability, and is an effective algorithm to the dynamic economic emission dispatch.

Key words: wind power, dynamic economic dispatch, differential evolution algorithm, crisscross optimization algorithm

CLC Number:

TP13

Mei Panpan, Wu Lianghong, Zhang Hongqiang, Wang Huiying. Adaptive Differential Crisscross Optimization Algorithm for Dynamic Economic Emission Dispatch Considering Wind Power[J]. Journal of System Simulation, 2020, 32(6): 1179-1187.

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