Abstract：To solve the problem that the power quality disturbance signal in power grid is difficult to detect accurately in the strong noise environment, an algorithm for power quality disturbance detection based on adaptive symplectic geometric mode decomposition and short-time energy difference factor is proposed in this paper. Firstly, the filter reconstruction of traditional symplectic geometric mode decomposition is improved based on adaptive symplectic geometric mode decomposition to reconstruct power quality disturbance signals accurately. Then, the short-term energy of the reconstructed signal is calculated to derive the parameter free adaptive threshold calculation formula based on short-time energy and construct the short-term energy differential factor. Based on this, a power quality disturbance detection platform based on virtual instrument is developed to detect the power quality disturbance accurately in real life. The simulation and the experimental results show that the proposed algorithm can detect the disturbance start and end time effectively for single disturbance, complex disturbance and zero crossing disturbance under noise environment, and can effectively overcome the influence of disturbance amplitude fluctuation on the detection results. Compared with the existing detection algorithm, the measurement results are more rapid and accurate.
李云峰, 高云鹏, 蔡星月, 朱彦卿, 吴聪. 自适应辛几何模态分解和短时能量差分因子在电能质量扰动检测中的应用[J]. 电工技术学报, 2022, 37(17): 4390-4400.
Li Yunfeng, Gao Yunpeng, Cai Xingyue, Zhu Yanqing, Wu Cong. Application of Adaptive Symplectic Geometry Modal Decomposition and Short-Time Energy Difference Factor in Power Quality Disturbance Detection. Transactions of China Electrotechnical Society, 2022, 37(17): 4390-4400.
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2022, Vol. 37 
