电力系统保护与控制Issue(2)：35-42,8.
基于病毒进化改进NSGA-II算法的扩展黑启动多目标优化
Multi-objective extended black-start schemes optimization based on virus evolution improved NSGA-II algorithm
摘要
Abstract
To ensure the safe recovery of the black-start system and well synthesize the quick search and local search of multi-objective optimization method, an extended black-start multi-objective optimization method based on virus evolution improved NSGA-II algorithm considering power support and restoration security margin comprehensively is proposed. The optimization goals are designed to maximize the total weighted power generation output (MWh) of the black-start system, to maximize voltage stability margin and to maintain bus voltage at a satisfactory level. Biological virus mechanism and the infection-based operation are introduced into the chromosome of the fast and elitist non-dominated sorting genetic algorithm (NSGA-II). Horizontal infection of the virus is applied to improve local search capability in solution space and avoid the frontier degradation. The virus evolution improved NSGA-II algorithm and the Dijkstra algorithm are employed to solve the Pareto-optimal solutions of the extended black-start schemes. The effectiveness of the proposed method is validated by the optimization results on the New England 10-unit 39-bus power system and the southern power system of Hebei province. The method can provide decision-makers with greater choice of space and guarantee the extended initial black-start power system to recover more power generation output safely and reliably.关键词
电力系统恢复/扩展黑启动/恢复安全裕度/多目标优化/快速非支配排序遗传算法/病毒进化Key words
power system restoration/extended black-start/restoration security margin/multi-objective optimization/fast and elitist non-dominated sorting genetic algorithm (NSGA-II)/virus evolution分类
信息技术与安全科学引用本文复制引用
陈亮,顾雪平,贾京华..基于病毒进化改进NSGA-II算法的扩展黑启动多目标优化[J].电力系统保护与控制,2014,(2):35-42,8.基金项目
高等学校博士学科点专项科研基金资助课题（20110036110007）；河北省自然科学基金项目（E2011502025）This work is supported by Natural Science Foundation of Hebei Province (No. E2011502025) （No. E2011502025）
