Enhanced Ultra-Short-Term PV Forecasting Using Sky Imagers: Integrating MCR and Cloud Cover Estimation

Weixiong Wu, Rui Gao, Peng Wu, Chen Yuan (), Xiaoling Xia, Renfeng Liu and Yifei Wang
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Weixiong Wu: Mamaya Photovoltaic Branch of Guizhou Beipanjiang Electric Power Co., Ltd., Guiyang 550081, China
Rui Gao: Mamaya Photovoltaic Branch of Guizhou Beipanjiang Electric Power Co., Ltd., Guiyang 550081, China
Peng Wu: Mamaya Photovoltaic Branch of Guizhou Beipanjiang Electric Power Co., Ltd., Guiyang 550081, China
Chen Yuan: Guizhou New Meteorological Technology Co., Ltd., Guiyang 550081, China
Xiaoling Xia: Guizhou New Meteorological Technology Co., Ltd., Guiyang 550081, China
Renfeng Liu: School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan 430023, China
Yifei Wang: School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan 430023, China

Energies, 2024, vol. 18, issue 1, 1-17

Abstract: Accurate photovoltaic (PV) power forecasting is crucial for stable grid integration, particularly under rapidly changing weather conditions. This study presents an ultra-short-term forecasting model that integrates sky imager data and meteorological radar data, achieving significant improvements in forecasting accuracy. By dynamically tracking cloud movement and estimating cloud coverage, the model enhances performance under both clear and cloudy conditions. Over an 8-day evaluation period, the average forecasting accuracy improved from 67.26% to 77.47% (+15%), with MSE reduced by 39.2% (from 481.5 to 292.6), R 2 increased from 0.724 to 0.855, NSE improved from 0.725 to 0.851, and Theil’s U reduced from 0.42 to 0.32. Notable improvements were observed during abrupt weather transitions, particularly on 1 July and 3 July, where the combination of MCR and sky imager data demonstrated superior adaptability. This integrated approach provides a robust foundation for advancing ultra-short-term PV power forecasting.

Keywords: ultra-short-term PV power forecasting; sky imagers; MCR; cloud cover estimation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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