考虑后续恢复的扩展黑启动方案多目标优化  

Multi-objective Extended Black-start Schemes Optimization Considering Subsequent Restoration Influence

作　　者：陈亮[1] 顾雪平[1] 贾京华[2] 

机构地区：[1]华北电力大学电气与电子工程学院,保定071003 [2]河北电力调度通信中心,石家庄050021

出　　处：《电力系统及其自动化学报》2014年第2期21-26,共6页Proceedings of the CSU-EPSA

基　　金：高等学校博士学科点专项科研基金资助项目(20110036110007);河北省自然科学基金资助项目(E2011502025)

摘　　要：目前黑启动阶段的恢复策略制定只考虑了初期恢复效果的优劣,而未将系统后续恢复的效果纳入策略目标集。文中综合考虑初期阶段和系统后续恢复效果,以初期阶段内发电量加权和最大化、尽快搭建系统的骨架网络和选择运行性能尽可能利于后续系统电压调整的被启动机组为优化目标,综合考虑机组启动约束和系统运行约束,建立扩展黑启动方案的多目标优化模型;然后结合快速非支配排序遗传算法NSGA-II(fast and elitist non-dominated sorting genetic algorithm)与最短路径法对扩展黑启动方案求解出Pareto最优解集。该方法避免了求解的目标偏好性,决策者可根据大停电恢复的实际要求选择出最终的满意解。最后以新英格兰10机39节点系统和河北南网实际系统为算例验证所提方法的有效性。The current restoration methods only consider the effect of the initial black-start stage without considering the restoration effect of the subsequent restoration stage.In this paper,a multi-objective optimization method considering the effects of the early restoration and the subsequent restoration comprehensively is proposed,where the optimization goals are designed to maximize the total weighted power generation output （MW· h） over the initial period,to extend the subsequent skeleton network as soon as possible and to restore units with good performances for voltage regulation of the subsequent system,with the constraints of the unit start-up time limitation and system operation.Then the fast and elitist non-dominated sorting genetic algorithm（NSGA-Ⅱ） based on greedy and the Dijkstra algorithm are employed to solve the Pareto-optimal solutions of the extended black-start schemes.The proposed method avoids artificially balanced solutions,and decision-maker can select the satisfactory solution according to system restoration requirement.The effectiveness of the proposed method is validated by the optimal results on the New England 10-unit 39-bus power system and the southern power system of Hebei Province.

关 键 词：电力系统恢复 扩展黑启动 后续恢复影响 多目标优化 快速非支配排序遗传算法 

分 类 号：TM76[电气工程—电力系统及自动化]