Energies, Vol. 18, Pages 5871: Multi-Criteria-Based Key Transmission Section Identification and Prevention–Emergency Coordinated Optimal Control Strategy
Energies doi: 10.3390/en18225871
Authors:
Xinyu Peng
Chuan He
Honghao Zhang
Lu Nan
Tianqi Liu
Jian Gao
Biao Wang
Xi Ye
Xinwei Sun
Large-scale blackouts in power systems are often triggered by weak links susceptible to cascading failures. As the concentrated reflection of the system’s weak links, identifying key transmission sections and further implementing safety control measures are of great significance for ensuring the stable operation of the system. This paper proposes a multi-criteria-based method for identifying key transmission sections and an optimal strategy for the prevention–emergency coordinated control of key transmission sections. Firstly, a line criticality index based on three characteristics—topology, power flow, and voltage—has been established to identify critical lines. Furthermore, search for all initial transmission sections that include the critical line, and form the initial transmission section set for each critical line, then, based on the analysis of the Theil index of power flow impact rate distribution after the failure of critical lines, a key transmission section identification method integrating multiple criteria is proposed. Then, based on the anticipated faults of key transmission sections, an optimization model for the prevention–emergency coordinated control of key transmission sections is established. A constraint relaxation factor is introduced to divide the above model into two independent sub-problems, then the golden section method is applied to update the value of constraint relaxation factors, so as to iteratively search for the optimal solution of the model. Finally, the feasibility and correctness of the proposed method are verified through the simulation and analysis of the IEEE 39-bus system. The results demonstrate that the proposed method can effectively identify the key transmission sections of the system and improve the operational safety of the system through the prevention–emergency coordinated optimal control strategy.