一种机组恢复决策的多时段协调优化方法

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Abstract To accelerate the restoration speed of a power system after a blackout,it is necessary to restore as many thermal units as possible within their hot-start intervals by determining a reasonable unit restoration sequence.By analyzing the serial and parallel restoration patterns of units and considering the effects of the hot-start interval on the restoration sequence,a multiple time-step coordinative optimization approach for decision making of the unit restoration sequences is proposed in the paper.Adopting the global optimization strategy based on multiple time-step modeling and coordinative optimization,a bi-level optimization model based on time-step is established,in which the total capacity of the hot-started units and the total units’ MWh output in the overall process are treated as the upper-level and the lower-level objective functions respectively.The multiple population genetic algorithm(MPGA) based on optimal choice of states is employed to solve the model.So the global optimization for unit-restoration decision making is achieved.By reasonably controlling the number of the reserved solutions for each time step,the diversity of solutions is remained to avoid the local traps.At the same time,the limit for the number of states in every stage is added,and the computation complexity is well controlled in an acceptable degree.The effectiveness of the proposed method is validated by the optimization results from the New England 10-unit 39-bus power system and the southern power system of Hebei.

Key words： Network reconfiguration sequence of unit restoration multiple time-step coordinative optimization optimal choice of state global optimization

Received: 30 December 2015 Published: 21 November 2016

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TM76

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	Gu Xueping
	Liu Wenxuan
	Wang Jiayu
	Jia Jinghua

Cite this article:

Gu Xueping,Liu Wenxuan,Wang Jiayu等. An Optimization Approach Based on Multiple Time-Step Coordination for Decision Making of Unit Restoration[J]. Transactions of China Electrotechnical Society, 2016, 31(21): 114-124.

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https://dgjsxb.ces-transaction.com/EN/ OR https://dgjsxb.ces-transaction.com/EN/Y2016/V31/I21/114

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