| 引用本文: | 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,2014,42(2):35-42.[点击复制] |
| CHEN Liang,GU Xue-ping,JIA Jing-hua.Multi-objective extended black-start schemes optimization based on virus evolution improved NSGA-II algorithm[J].Power System Protection and Control,2014,42(2):35-42[点击复制] |
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| 摘要: |
| 为了保证黑启动小系统的安全恢复和合理兼顾多目标优化方法的快速搜索与局部搜索，提出基于病毒进化改进NSGA-II算法的综合功率支持和恢复安全裕度的扩展黑启动方案多目标优化方法。以初期阶段内发电量加权和最大化、电压稳定裕度最大化和维持节点电压在满意水平为目标建立多目标优化模型。在快速非支配排序遗传算法（NSGA-II）的染色体中引入生物病毒机制和病毒感染操作，利用病毒的横向感染对解空间进行局部搜索，避免强化全局寻优时的前沿退化。然后结合基于病毒进化改进NSGA-II算法与最短路径法对扩展黑启动方案求解出Pareto最优解集。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，该方法为决策者提供了更全局性的选择空间，从而保证扩展黑启动小系统安全可靠地恢复更多出力。 |
| 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 |
| DOI：10.7667/j.issn.1674-3415.2014.02.006 |
| 投稿时间：2013-04-21修订日期：2013-05-25 |
| 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） |
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| Multi-objective extended black-start schemes optimization based on virus evolution improved NSGA-II algorithm |
| CHEN Liang,GU Xue-ping,JIA Jing-hua |
| (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China;Hebei Power Dispatch and Communication Center, Shijiazhuang 050021, China) |
| 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. |
| 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 |
