基于BP-QR模型的负荷区间预测

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Abstract This paper combines BP neural network and quantile regression (QR) algorithm to propose a load interval forecasting method to reduce the errors caused by the uncertain factors of power grid operation. The load interval forecasting is realized by the meteorological factors and the previous day's load value. The experimental results show that the model can show the fluctuation trend of electricity load accurately, and provide forecasting intervals under any confidence level.

Key words： load forecasting interval forecasting quantile regression neural network

Received: 08 October 2021

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	CHEN Xuanwei

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CHEN Xuanwei. Load interval forecasting based on BP-QR model[J]. Electrical Engineering, 2022, 23(4): 14-17.

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http://dqjs.cesmedia.cn/EN/Y2022/V23/I4/14

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