Reactive Power Collaborative Control Strategy and Verification Method for Suppressing Voltage Oscillation in Renewable Energy Clusters

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Authors: Yanzhang Liu, Lingzhi Zhu, Minhui Qian, Jia Chen
Cited by: 0

Abstract

With the progressive implementation of China's dual-carbon strategy, the proportion of renewable energy in the power system continues to rise. Large-scale renewable energy clusters for centralized power transmission have been established in regions such as Northeast and Northwest China, while offshore wind power in coastal areas of East China is experiencing rapid growth. The inherent intermittency and stochastic variability of wind and solar resources introduce significant uncertainty into power output, leading to frequent operational challenges within renewable energy clusters, including voltage fluctuations and reactive power oscillation. To address these challenges, this paper proposes a multi-mode adaptive coordinated reactive power control strategy for renewable energy clusters. The research framework proceeds as follows: First, two key indicators characterizing the voltage dynamic behavior of renewable energy clusters are analyzed, namely, voltage sensitivity and the Multi-plant Short-Circuit Ratio (MRSCR). Subsequently, based on the physical implications of these indicators, conventional control modes, including constant voltage, constant reactive power, and constant power factor control, are refined and adaptively deployed, forming an integrated multi-mode coordinated control strategy. Finally, the effectiveness of the proposed strategy is verified through a closed-loop, co-simulation testing platform that combines digital simulation with physical hardware-in-the-loop elements. The results indicate that, compared to conventional automatic voltage control (AVC) methods, the proposed strategy demonstrates enhanced adaptability to frequently changing grid operating conditions and contributes more effectively to the mitigation of voltage oscillation issues in renewable energy clusters.

Fields of Study & Subjects

Microgrid Control and Optimization Power System Optimization and Stability Wind Turbine Control Systems

Publication details

Journal / source
Preprints.org
Publication date
5 January 2026
Document type
Preprint