Yi Wang, Luzian Lebovitz, Kedi Zheng, 等. Consensus Clustering for Bi-objective Power Network Partition[J]. 中国电机工程学会电力与能源系统学报(英文), 2022,8(4):973-982.
Yi Wang, Luzian Lebovitz, Kedi Zheng, et al. Consensus Clustering for Bi-objective Power Network Partition[J]. CSEE Journal of Power and Energy Systems, 2022, 8(4): 973-982.
Yi Wang, Luzian Lebovitz, Kedi Zheng, 等. Consensus Clustering for Bi-objective Power Network Partition[J]. 中国电机工程学会电力与能源系统学报(英文), 2022,8(4):973-982.DOI: 10.17775/CSEEJPES.2020.06390.
Yi Wang, Luzian Lebovitz, Kedi Zheng, et al. Consensus Clustering for Bi-objective Power Network Partition[J]. CSEE Journal of Power and Energy Systems, 2022, 8(4): 973-982.DOI: 10.17775/CSEEJPES.2020.06390.
Consensus Clustering for Bi-objective Power Network Partition
Partitioning a complex power network into a number of sub-zones can help realize a “divide-and-conquer” management structure for the whole system
such as voltage and reactive power control
coherency identification
power system restoration
etc. Extensive partitioning methods have been proposed by defining various distances
applying different clustering methods
or formulating varying optimization models for one specific objective. However
a power network partition may serve two or more objectives
where a trade-off among these objectives is required. This paper proposes a novel weighted consensus clustering-based approach for bi-objective power network partition. By varying the weights of different partitions for different objectives
Pareto improvement can be explored based on the node-based and subset-based consensus clustering methods. Case studies on the IEEE 300-bus test system are conducted to verify the effectiveness and superiority of our proposed method.