Multi-objective Optimization And Decision Making Of Extended Black-start Schemes Of Power Systems

Black-start restoration after power system blackout is an effective measure of powersystem security defense. Reasonable black-start scheme can guarantee the black-startsystem to restore more output safely and reliably, and speed up the restoration process.The extended black-start strategy that a black-start power plant starts more than onepower plant at the same time is a new exploration for power system black-startrestoration research. The extended black start system can provide greater power supportfor the subsequent restoration and speed up the restoration process. However, in thecurrent restoration methods of extended black-start, only profitability indexes aremaximized without comprehensively considering the restoration effect of the subsequentrestoration stage and restoration security margin.In this paper, an extended black-start multi-objective optimization methodconsidering continuity of recovery time and recovery comprehensive effect is proposed.Firstly，the indices that reflect subsequent restoration influence and the restorationsecurity margin of the black-start scheme are extracted and incorporated into target set tocompletely optimize the recovery effect. The optimization goals are designed tomaximize the total weighted power generation output (MWh) of the black-start system,to extend the subsequent skeleton network as soon as possible and to retain appropriaterestoration security margin, with the constraints of the unit start-up time and systemoperation. Secondly, the biological virus mechanism and the infection-based operationare introduced into the chromosome of the fast and elitist non-dominated sorting geneticalgorithm(NSGA-II). Horizontal infection of the virus is applied to improve local searchcapability in solution space and avoid the frontier degradation. The virus evolutionimproved NSGA-II algorithm and the Dijkstra algorithm are employed to solve thePareto-optimal solutions of the extended black-start schemes. Thirdly, by using the Vaguesets multiple attributes decision-making method based on fuzzy entropy weight andconsidering the preference factors of decision makers and objective information ofdecision matrix, the most satisfactory solution was identified. The effectiveness of theproposed method was validated by the optimization results on the New England10-unit39-bus power system and the southern power system of Hebei province.