Keywords
network planning; invulnerability; dual-layer model; regional division; Steiner tree
Abstract
Energy security is related to the overall situation of economic and social development.In recent years, deliberate attacks and disasters against the power grid have occurred frequently, and the power system has become an important target of attacks in international conflicts.In order to enhance the ability of the power grid to resist deliberate attacks and disasters and ensure the safe operation of the national energy infrastructure, a Steiner minimum tree planning method is proposed for the power supply network topology to the improvement of invulnerability.Firstly, the grid structure strength index and operation vulnerability index are designed for the grid planning problem.A dual-layer planning model is constructed with the grid structure strength, network connectivity, and network operation status as the upper targets, and the line investment cost, node construction cost, and network loss cost as the lower targets.Secondly, based on the complex network theory, the topology mapping model of the power grid is built.The important areas and nodes of the power grid are divided according to the load demand and capacity demand of nodes.Then, the problem of power grid planning is transformed into a regional Steiner tree problem, and nodes are added in the region to re-plan the grid structure in important areas.Finally, the heuristic algorithm is combined with the mathematical programming problem.The artificial fish swarm algorithm is used to optimize the solution.The 39-node grid structure is applied for simulation verification.The calculation results show that the proposed method can improve the strength of the grid structure by 64.60% and reduce the operation risk by 71.38 %.
DOI
10.19781/j.issn.1673-9140.2025.05.001
First Page
1
Last Page
13
Recommended Citation
ZHAI, Yunpeng; LIU, Dongqi; LIANG, Haolan; and LI, Wei
(2025)
"Optimal planning strategies for power grid topology Steiner minimum tree to enhance resilience capability,"
Journal of Electric Power Science and Technology: Vol. 40:
Iss.
5, Article 1.
DOI: 10.19781/j.issn.1673-9140.2025.05.001
Available at:
https://jepst.researchcommons.org/journal/vol40/iss5/1
