Quantum Computing-Based Search Method for Transmission Sections

The increasing scale and complexity of modern power systems impose higher demands for the secure and stable operation of power grids. Traditional methods for identifying key transmission section (KTS) suffer from limitations such as low computational efficiency and high risk of missing critical sections. Quantum computing possesses unparalleled parallel processing capabilities that classical computing technologies cannot match, offering a groundbreaking technical approach to transmission section (TS) search. This paper proposes KTS identification method based on the quantum approximate optimization algorithm (QAOA). By constructing target and initial Hamiltonians from topological cut-sets, a quantum circuit model is designed. Quantum parameters are then optimized via differential gradient descent and expected cut value tuning, facilitating efficient TS search. The KTS is determined by integrating electrical zone connectivity and power flow distribution factor thresholds, ensuring the physical rationality and security sensitivity of the results. Experiments on the Origin Quantum Qpanda software platform using the IEEE 14-node system and IEEE 30-node system demonstrate that the proposed method significantly improves the identification rate of KTS.