ULTRA-SHORT-TERM PHOTOVOLTAIC POWER MULTI-STEP PREDICTION BASED ON SPEARMAN COEFFICIENT AND TCN

Wu Junyue; Zhao Ergang; Guo Zengliang; Zhang Yaping; Zhang Jianjun

doi:10.19912/j.0254-0096.tynxb.2022-0654

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Acta Energiae Solaris Sinica ›› 2023, Vol. 44 ›› Issue (9) : 180-186. DOI: 10.19912/j.0254-0096.tynxb.2022-0654

ULTRA-SHORT-TERM PHOTOVOLTAIC POWER MULTI-STEP PREDICTION BASED ON SPEARMAN COEFFICIENT AND TCN

Wu Junyue^1-3, Zhao Ergang^1-3, Guo Zengliang⁴, Zhang Yaping⁴, Zhang Jianjun^1-3

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Abstract

This paper developed a ultra-short-term photovoltaic power prediction model based on Spearman coefficient and improved TCN. First, we used Spearman coefficient to screen the input weather characteristics, and then we built a proper TCN to make it suitable for the photovoltaic power prediction problems. Through the actual data test of photovoltaic power station, the fitting degree of the model is 99.41%, and MAE of prediction is 61.04, which is better than the traditional time series problem model LSTM.

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PV power generation / forecasting / neural networks / data processing / time series

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Wu Junyue, Zhao Ergang, Guo Zengliang, Zhang Yaping, Zhang Jianjun. ULTRA-SHORT-TERM PHOTOVOLTAIC POWER MULTI-STEP PREDICTION BASED ON SPEARMAN COEFFICIENT AND TCN[J]. Acta Energiae Solaris Sinica. 2023, 44(9): 180-186 https://doi.org/10.19912/j.0254-0096.tynxb.2022-0654

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