Abstract
Based on the community discovery method in complex network theory, a power grid partition method considering generator nodes and network weightings is proposed. Firstly, the weighted network model of a power system is established, an improved Fast-Newman hierarchical algorithm and a weighted modular Q function index are introduced, and the partitioning algorithm process is practically improved combined with the characteristics of the actual power grid. Then, the partition results of several IEEE test systems with the improved algorithm and with the Fast-Newman algorithm are compared to demonstrate its effectiveness and correctness. Subsequently, on the basis of subnet partition, two kinds of network attack strategies are proposed. One is attacking the maximum degree node of each subnet, and the other is attacking the maximum betweenness node of each subnet. Meanwhile, considering the two traditional intentional attack strategies, that is, attacking the maximum degree nodes or attacking the maximum betweenness nodes of the whole network, the cascading fault survivability of different types of networks under four attack strategies is simulated and analyzed. It was found that the proposed two attack strategies based on subnet partition are better than the two traditional intentional attack strategies.
Highlights
With the construction of ultra-high voltage grids, smart grids, and clean energy-based energy Internet, the gradual interconnection of large grids has taken shape and continues to develop and improve on this basis
In order to ensure the normal work of each subnet after power grid partition, this paper proposes an improved Fast-Newman algorithm based on the Fast-Newman algorithm
Based on community discovery in complex network theory, this paper proposes a power grid partitioning method considering generator nodes and connection weight
Summary
With the construction of ultra-high voltage grids, smart grids, and clean energy-based energy Internet, the gradual interconnection of large grids has taken shape and continues to develop and improve on this basis. The community detection method of the model is mainly based on the pure topological structure of an undirected and unweighted network, without considering the function of a community. It cannot fully reflect the electrical characteristics of a power grid. It was noticed that previous studies on network attack strategies mainly applied random attack or deliberate attack to attack the node with the largest degree value or the node with the largest betweenness in a network These attack strategies may not make full use of the network structure information, look too simple, and lack effective data mining in the early stage [20,21,22].on the basis of subnet partition, this paper proposes a new network attack strategy. It was found that the attack effect of our attack strategy is better than that of traditional attack strategies
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
