Real-Time Reactive Power Optimization for New Power Systems Based on Graph Convolutional Networks

Pei ZHANG, Xiaofei LIU, Wenyun LI, Xuegang LU, Zhenyi WANG, Suwei ZHAI, Huibo SUN

South Power Sys Technol ›› 2025, Vol. 19 ›› Issue (7) : 3-14.

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South Power Sys Technol ›› 2025, Vol. 19 ›› Issue (7) : 3-14. DOI: 10.13648/j.cnki.issn1674-0629.2025.07.001
Special Column on Boao New Power System International Forum

Real-Time Reactive Power Optimization for New Power Systems Based on Graph Convolutional Networks

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Abstract

The rapid fluctuations in renewable energy output cause frequent voltage oscillations in power grids, severely threatening the safe and economical operation of power grids. To address this issue, a real-time reactive power optimization method based on graph convolutional networks （GCN） is proposed. Firstly, a multi-objective reactive power optimization model considering the importance of nodes is constructed. Based on this, the graph representation of the reactive power optimization model is established, and the adjacency matrix is restructured in conjunction with the optimization problem. Then, the optimal solution set is mapped using the GCN algorithm, and the improved CRITIC-AHP-TOPSIS combined weighting algorithm is employed to select the optimal solution, forming a real-time optimization strategy. Finally, using the modified IEEE 39-node system and an actual power grid as examples, the proposed method is verified. The results show that the method not only has the advantages of fast solving speed and avoiding local optima but also achieves more favorable voltage deviation and active power loss, ensuring the safety and economy of new power system operation.

Key words

graph convolutional networks / renewable energy / real-time reactive power optimization / importance of nodes / optimal solution

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Pei ZHANG , Xiaofei LIU , Wenyun LI , et al . Real-Time Reactive Power Optimization for New Power Systems Based on Graph Convolutional Networks[J]. Southern Power System Technology. 2025, 19(7): 3-14 https://doi.org/10.13648/j.cnki.issn1674-0629.2025.07.001

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Funding

the Science and Technology Project of Yunnan Electric Power Dispatching and Control Center, China Southern Power Grid Co., Ltd(YNKJXM20222463)
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