Research on Coordinated Control of Dynamic Reactive Power Sources of DC Blocking and Commutation Failure Transient Overvoltage in New Energy Transmission

Shuqin Sun, Zhenghai Yuan, Dezhi Chen, Zaihua Li (), Xiaojun Tang, Yunting Song and Guanghao Zhou
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Shuqin Sun: College of Instrumentation and Electrical Engineering, Jilin University, Changchun 130061, China
Zhenghai Yuan: College of Instrumentation and Electrical Engineering, Jilin University, Changchun 130061, China
Dezhi Chen: China Electric Power Research Institute, Beijing 100192, China
Zaihua Li: China Electric Power Research Institute, Beijing 100192, China
Xiaojun Tang: China Electric Power Research Institute, Beijing 100192, China
Yunting Song: China Electric Power Research Institute, Beijing 100192, China
Guanghao Zhou: College of Instrumentation and Electrical Engineering, Jilin University, Changchun 130061, China

Energies, 2025, vol. 18, issue 9, 1-24

Abstract: With the large-scale deployment of renewable energy, transmission systems for new energy sources are increasingly exposed to transient overvoltage issues induced by DC blockages and commutation failures. To address the challenges of an imprecise response to multiple fault scenarios and the inefficiency of independent device actions in existing dynamic reactive power control schemes, this paper proposes a coordinated optimization control strategy integrating multiple dynamic reactive power sources tailored to different fault characteristics. An equivalent model of the renewable energy DC transmission system is established to elucidate the underlying mechanisms of transient overvoltage formation under various fault conditions. By employing trajectory sensitivity analysis and parameter perturbation methods, the influence patterns of control parameters on transient overvoltage behaviors across different fault scenarios are quantitatively assessed, thereby overcoming the limitations of traditional empirical parameter tuning approaches. Subsequently, a multi-source coordinated optimization model is developed with the objective of minimizing transient overvoltages under simultaneous dual-fault conditions. A multi-objective particle swarm optimization algorithm, incorporating comprehensive trajectory sensitivity and dynamically adaptive inertia weights, is introduced, alongside Pareto front theory, to achieve rapid and balanced optimization among competing objectives. Simulation results validate that the proposed strategy significantly enhances transient overvoltage suppression across diverse fault conditions. The findings provide robust theoretical foundations and practical guidance for the refined parameter tuning and high-efficiency coordinated control of dynamic reactive power sources in renewable energy transmission systems.

Keywords: new energy; transient overvoltage; dynamic reactive power source; trajectory sensitivity; collaborative control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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