电力系统最小驱动节点集筛选算法OA
Minimum Driver Node Sets Selection Algorithm for Power Systems
电力系统中的某些节点的故障可能会导致级联故障,需要选择一组节点进行人为控制以减少损失,考虑了电力网络的能控性与拓扑结构之间的关系,提出了基于节点能控中心性和电气介数的节点EC指数.首先,确定网络所需的最小驱动节点数量;然后,基于PBH判据和网络的精确可控性理论筛选网络中的有效信号输入;最后,在最优驱动节点集上输入信号使网络达到完全能控.以修正的拉普拉斯矩阵的最小非零特征值作为评价指标,对比其他五种筛选策略,提出的方法能够得到最优驱动节点集.
In electrical power systems,failure of certain nodes may lead to cascading failures,and a set of nodes needs to be selected for human control in order to reduce losses.Considering the relationship between controllability and topology of the power network,this paper proposes an EC index based on node controllability centrality and electrical betweenness for node selection.Firstly,the minimum number of driving nodes required for the network is determined.Then,effective signal inputs in the network are screened based on the PBH criterion and the theory of precise controllability of the network.Finally,input signals are provided on the optimal set of driving nodes to achieve complete controllability of the network.By using the minimum non-zero eigenvalue of the modified Laplacian matrix as the evaluation index,the proposed method can obtain the optimal set of driving nodes compared with five other screening strategies.
葛耀东;李琰;宋晴;徐天奇
湖北黄冈应急管理职业技术学院 黄冈 438000云南民族大学电气信息工程学院 昆明 650500山东省济宁供电公司 济宁 272113云南民族大学电气信息工程学院 昆明 650500
信息技术与安全科学
最小驱动节点集网络能控性电气介数节点控制能力
minimum driver node setnetwork controllabilityelectrical betweennessnode control capability
《计算机与数字工程》 2026 (3)
617-622,6
国家自然科学基金项目(编号:62062068)云南民族大学2022年硕士研究生科研创新基金项目(编号:2022SKY007)云南省教育厅科学研究基金项目(编号:2023Y0501)资助.
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