引用本文:林梅芬,陈婷,王秋杰,等.一种配电网基于模型诊断的最小碰集改进算法[J].电力系统保护与控制,2020,48(8):25-33.
LIN Meifen,CHEN Ting,WANG Qiujie,et al.An improved minimum set algorithm for model-based diagnosis of a distribution network[J].Power System Protection and Control,2020,48(8):25-33
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一种配电网基于模型诊断的最小碰集改进算法
林梅芬1,3,陈 婷2,3,王秋杰2,朱文强3
(1.河海大学能源与电气学院，江苏 南京 210098;2.福州大学电气工程及自动化学院，福建 福州 350116; 3.福建水利电力职业技术学院，福建 永安 366000)
摘要:
在配电网故障的基于模型诊断方法中，最小碰集计算对整个诊断过程具有较大影响。为了进一步提高基于模型诊断的效率和准确率，提出一种适合配电网拓扑结构的最小碰集改进算法。利用新的适应度函数保证粒子直接朝着最小碰集迭代，提高对有解空间的搜索效率。利用“特征学习”搜索策略减少对无解空间的搜索。在分析配电网各元件解析冗余关系之间联系的基础上，提出算法分层的理论依据和实现方法。算例表明，改进后最小碰集算法具有更短的求解时间和更高的准确率。将改进后的最小碰集算法应用到基于模型诊断中，故障诊断的效率和准确率得到一定提高。
关键词:  配电网  基于模型诊断  最小碰集计算  拓扑结构  特征学习
DOI：10.19783/j.cnki.pspc.190621
分类号:
基金项目:国家自然科学基金项目资助(51377047);福建省中青年教师教育科研项目资助(JZ180466)
An improved minimum set algorithm for model-based diagnosis of a distribution network
LIN Meifen1,,3,CHEN Ting2,3,WANG Qiujie2,ZHU Wenqiang3
(1. School of Energy and Electricity, Hohai University, Nanjing 210098, China;2. School of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350116, China;3. Fujian Vocational and Technical College of Water Conservancy and Electricity, Yong’an 366000, China)
Abstract:
In the model-based diagnosis method of distribution network faults, the minimum hitting set calculation has a great impact on the whole diagnostic process. A new minimum hitting set algorithm suitable for the distribution network topology is proposed to improve the efficiency and accuracy rate of model-based diagnosis. The new fitness function in the algorithm allows the particle iterating towards the minimum hitting set directly. As a result, the search efficiency for the solution space is improved correspondingly. A search strategy of "feature learning" is used to reduce the search for unsolved space. Analyzing the relation between analytic redundancy relations of distribution network components, the theoretical basis and implementation method of algorithm stratification are put forward. The example shows that the improved minimum hitting set algorithm has shorter solution time and higher accuracy. Applying the improved minimum hitting set algorithm to model-based diagnosis, the efficiency and accuracy of fault diagnosis are improved. This work is supported by National Natural Science Foundation of China (No. 51377047).
Key words:  distribution network  model-based diagnosis  minimum hit set calculation  topology structure  feature learning
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