| 引用本文: | 符杨,顾吉平,田书欣,米阳,刘舒.基于地震灾害场景的主动配电网多维韧性评估方法[J].电力自动化设备,2023,43(3): |
| FU Yang,GU Jiping,TIAN Shuxin,MI Yang,LIU Shu.Multidimensional resilience evaluation method of active distribution network based on earthquake disaster scene[J].Electric Power Automation Equipment,2023,43(3): |
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| 摘要: |
| 为了分析主动配电网承受破坏性扰动事件以及快速恢复重要负荷的韧性支撑能力，融合相量测量单元(PMU)高精度动态感知能力提出了一种新的以地震灾害场景为背景的主动配电网多维韧性评估方法。阐述了配电网韧性的基本概念及特征，并将地震作为极端事件代表，构建了反映配电线路故障率与地震动峰值加速度加权均值的模型，继而采用非序贯蒙特卡罗抽样和K-means++聚类算法筛选出代表性的地震场景；基于系统配置的PMU的强感知力建立反映韧性电网应变力、防御力、恢复力和协同力的评估指标，形成韧性多维特征空间，进而利用事件集点簇中心与最优韧性点的加权欧氏距离评估系统多维综合韧性；分析增强电力线路强度、提高联合系统中分布式电源可供容量这2种措施对系统韧性提升的影响，挖掘韧性电网对抗震防灾的学习力。最后，通过改进的PG&E69系统验证所提方法的有效性和准确性。 |
| 关键词: 主动配电网 地震灾害 韧性评估 K-means++聚类 韧性多维特征空间 |
| DOI：10.16081/j.epae.202208024 |
| 分类号:TM727;TM712 |
| 基金项目:国家重点研发计划项目(2017YFB0902800)；国家自然科学基金资助项目(52007112)；国家电网有限公司科技项目(52094019006X) |
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| Multidimensional resilience evaluation method of active distribution network based on earthquake disaster scene |
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FU Yang1, GU Jiping1, TIAN Shuxin1, MI Yang1, LIU Shu2
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1.Department of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China;2.State Grid Shanghai Electric Power Research Institute, Shanghai 200437, China
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| Abstract: |
| In order to analyze the resilience support ability of active distribution network to withstand destructive disturbance events and quickly recover important loads, a new multidimensional resilience evaluation method of active distribution network that integrated with the high-precision dynamic perception ability of phasor measurement unit(PMU) on the background of earthquake disaster scenario is proposed. The basic concepts and characteristics of distribution network resilience are described. And taking earthquake as the representative of extreme events, the model reflecting the weighted mean of distribution line failure rate and ground vibration peak acceleration is constructed, and then the representative earthquake scenes are selected by non sequential Monte Carlo sampling and K-means++ clustering algorithm. Based on the strong perception of PMU configured by the system, the evaluation indexes reflecting the abilities of strain, defense, recovery and synergy of the resilient power grid are established to form a resilience multidimensional feature space, and then the weighted Euclidean distance between the center of the event clusters and the optimal resilience point is used to evaluate the multidimensional comprehensive resilience of system. Furthermore, the impacts of two measures to enhance the strength of power lines and improve the distribution generation available capacity in the joint system on the improvement of system resilience are analyzed, and the learning ability about earthquake resistance and disaster prevention of resilient power grid is excavated. Finally, the effectiveness and accuracy of the proposed method are verified by the improved PG&E69 system. |
| Key words: active distribution network earthquake disaster resilience evaluation K-means++ clustering resilience multidimensional feature space |
