基于典型故障与环境场景关联识别的城市配电网运行风险预警方法  

A Risk Warning Method for Urban Distribution Network Based on Associated Recognition of Typical Fault and Environment Scenario

作　　者：徐特威 鲁宗相[1] 乔颖[1] 邹俭[2] 何维国[2] 郭睿[2] 

机构地区：[1]电力系统及发电设备控制和仿真国家重点实验室(清华大学电机系),北京市海淀区100084 [2]上海市电力公司,上海市浦东新区200122

出　　处：《电网技术》2017年第8期2577-2584,共8页Power System Technology

基　　金：国家电网公司科技项目(SGSHPD00ZSJS1406054)~~

摘　　要：随着城市电网逐步迈入高供电可靠性水平,配电网运行风险评估和预警成为进一步提升可靠性水平的关键。配电网故障具有随机性强、因果性弱的特征,常规方法难以寻找其规律。论文引入数据挖掘思想,基于对故障各类型数据的分析,提出了故障环境场景的概念,并对运行风险指标进行了定义,然后分析了Apriori算法在配电网运行风险评估中的适用性,并提出了若干改进措施,在此基础上建立了基于典型故障与环境场景关联识别的配电网运行风险预警算法。算例分析验证了所提方法的可行性。As urban power grids gradually enter high reliability level, the operation risk assessment and early warning of distribution network faults have become the key technology to further enhancing the system reliability. Distribution network faults have the salient features of strong randomness and weak causality, and it is hard to find its root cause by conventional methods. The idea of data mining is introduced in this paper. Based on the analysis of various types of fault data, the concept of fault environment scenario is proposed and the operational risk index is defined. Then, the applicability of Apriori algorithm in distribution network operation risk assessment is analyzed and several improvement measures are put forward. Using this model, a risk warning method for urban distribution network based on associated recognition of typical fault and ,environment scenario is established. Case study based on practical operating data is given to illustrate the feasibility of the proposed method.

关 键 词：城市配电网 运行风险 环境场景 APRIORI算法 

分 类 号：TM721[电气工程—电力系统及自动化]