基于分解的多目标进化算法的含MMC-HVDC交直流混合系统最优潮流研究

doi:10.19595/j.cnki.1000-6753.tces.191235

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Abstract To coordinate system economy and voltage quality, a new multi-objective optimal power flow algorithm based on multi-objective evolutionary algorithm based on decomposition (MOEA/D) was proposed for AC/DC hybrid system incorporating MMC-HVDC. Firstly, based on the general model of MMC converter stations that consider the losses of the converter, the optimal power flow mathematical model of DC power flow controller(DCPFC) containing AC/DC hybrid system with the target functions for network losses and voltage deviations was established. The calculation formula of the Jacobian matrix at the droop control of the DC grid MMC converter stations with DCPFC was derived. Next, the MOEA/D was used to optimize the AC/DC model to obtain the optimal solution set of Pareto and compared with non-dominated sorting genetic algorithm-2(NSGA-2). Finally, according to the entropy weight method (EWM), the optimization results were supported in decision and the best compromise solution was selected. The IEEE multi-node systems were used to compare the calculation results of the two-terminal and three-terminal MMC converter stations under different control modes, which verifies the effectiveness of the method.

Key words： Multi-objective evolutionary algorithm (MOEA) optimal power flow DC power flow controller(DCPFC) AC/DC system droop control entropy weight method (EWM)

Received: 27 September 2019

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TM74

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	Wang Haoxiang
	Zhao Dongmei
	Tao Ran
	Du Gang
	Tan Long

Cite this article:

Wang Haoxiang,Zhao Dongmei,Tao Ran等. Study on Optimal Power Flow for AC/DC Hybrid System Incorporating MMC-HVDC Based on MOEA/D[J]. Transactions of China Electrotechnical Society, 2020, 35(17): 3691-3702.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.191235 OR https://dgjsxb.ces-transaction.com/EN/Y2020/V35/I17/3691

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