Multi-Objective Dynamic Economic Emission Dispatch with Electric Vehicle–Wind Power Interaction Based on a Self-Adaptive Multiple-Learning Harmony-Search Algorithm

Li Yan, Zhengyu Zhu, Xiaopeng Kang, Boyang Qu, Baihao Qiao, Jiajia Huan and Xuzhao Chai
Additional contact information
Li Yan: School of Electronic and Information Engineering, Zhongyuan University of Technology, Zhengzhou 450007, China
Zhengyu Zhu: School of Electronic and Information Engineering, Zhongyuan University of Technology, Zhengzhou 450007, China
Xiaopeng Kang: School of Electronic and Information Engineering, Zhongyuan University of Technology, Zhengzhou 450007, China
Boyang Qu: School of Electronic and Information Engineering, Zhongyuan University of Technology, Zhengzhou 450007, China
Baihao Qiao: Guangzhou Institute of Technology, Xidian University, Xi’an 710071, China
Jiajia Huan: Guangdong Power Grid Co., Ltd., Guangzhou 510000, China
Xuzhao Chai: School of Electronic and Information Engineering, Zhongyuan University of Technology, Zhengzhou 450007, China

Energies, 2022, vol. 15, issue 14, 1-22

Abstract: Dynamic economic emission dispatch (DEED) in combination with renewable energy has recently attracted much attention. However, when wind power is considered in DEED, due to its generation uncertainty, some additional costs will be introduced and the stability of the dispatch system will be affected. To address this problem, in this paper, the energy-storage characteristic of electric vehicles (EVs) is utilized to smooth the uncertainty of wind power and reduce its impact on the system. As a result, an interaction model between wind power and EV (IWEv) is proposed to effectively reduce the impact of wind power uncertainty. Further, a DEED model based on the IWEv system ( DEED IWEv ) is proposed. For solving the complex model, a self-adaptive multiple-learning multi-objective harmony-search algorithm is proposed. Both elite-learning and experience-learning operators are introduced into the algorithm to enhance its learning ability. Meanwhile, a self-adaptive parameter adjustment mechanism is proposed to adaptively select the two operators to improve search efficiency. Experimental results demonstrate the effectiveness of the proposed model and the superiority of the proposed method in solving the DEED IWEv model.

Keywords: dynamic economic and emission dispatch; electric vehicles; wind power; harmony search (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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