基于树形贝叶斯网络的配电网快速灾情推断A Quick Disaster Inference in Power Distribution Network Based on Tree-like Bayesian Network
熊宇峰;周刚;陈颖;陈来军;张明龙;李博达;
摘要(Abstract):
近年来,极端灾害已经成为导致配电网大规模停电的重要原因之一。快速地对关键负荷的受灾情况进行推断,对于指导恢复抢修方案具有重要意义。传统的贝叶斯网络推断方法计算复杂度随网络节点增加呈指数上升,难以满足配电网灾情实时推断的需要。为此,结合配网开环运行的特点,建立树形的贝叶斯网络。在此基础上,提出快速灾情推断的流程和方法。对于任意选取的关键节点,该方法的计算复杂度均为节点数的一次多项式,克服了传统推断方法造成的维数灾难,可实现对大规模配电网的灾情实时推断。通过理论分析和算例仿真,验证了所提快速灾情推断方法的准确性和快速性,并论证了其在实际灾情推断中的作用。
关键词(KeyWords): 极端灾害;配电网灾情推断;树形贝叶斯网络;快速推断算法;停运概率计算;关键节点
基金项目(Foundation): 国家电网公司科技项目:提升极端灾害下配电网动态恢复和现场指挥关键技术研究项目(52130418000L)~~
作者(Author): 熊宇峰;周刚;陈颖;陈来军;张明龙;李博达;
Email:
DOI: 10.13335/j.1000-3673.pst.2020.0146
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