基于变分模态分解和极限学习机的换流站直流极线光学电流测量装置误差预测

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Abstract With the rapid development of high voltage direct current (HVDC) transmission in China, optical principle based pole-to-pole DC measurement devices are widely used. Accurately predicting the trend of measurement errors is crucial for the operation and protection of HVDC transmission systems. In response to the problems of large prediction errors and low training efficiency in existing methods, a prediction method based on variational mode decomposition and extreme learning machine is proposed. The error time series of the measurement device is decomposed using variational mode decomposition, and then a particle swarm optimization algorithm is used to optimize the extreme learning machine for multi-step prediction of each mode. The predicted measurement error is obtained through reconstruction. Through comparison with multiple models, the superiority of the proposed method is verified.

Key words： optical DC measurement device error prediction extreme learning machine particle swarm optimization variational mode decomposition

Received: 10 April 2024

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	Articles by authors
	LUO Qiang
	HUANG Yulei
	YAN Jun
	ZI Yuehua
	XU Tianqi

Cite this article:

LUO Qiang,HUANG Yulei,YAN Jun等. Error prediction of optical current measurement device for DC pole line in converter station based on variational mode decomposition and extreme learning machine[J]. Electrical Engineering, 2024, 25(11): 1-9.

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https://dqjs.cesmedia.cn/EN/Y2024/V25/I11/1

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