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Wei Zhuang, Zhiheng Li, Ying Wang, Qingyu Xi and Min Xia
Predicting photovoltaic (PV) power generation is a crucial task in the field of clean energy. Achieving high-accuracy PV power prediction requires addressing two challenges in current deep learning methods: (1) In photovoltaic power generation prediction...
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Ganapathy Ramesh, Jaganathan Logeshwaran, Thangavel Kiruthiga and Jaime Lloret
In general, reliable PV generation prediction is required to increase complete control quality and avoid potential damage. Accurate forecasting of direct solar radiation trends in PV power production could limit the influence of uncertainties on photovol...
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Everton Jose Santana, Ricardo Petri Silva, Bruno Bogaz Zarpelão and Sylvio Barbon Junior
With data collected by Internet of Things sensors, deep learning (DL) models can forecast the generation capacity of photovoltaic (PV) power plants. This functionality is especially relevant for PV power operators and users as PV plants exhibit irregular...
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Youngil Kim, Keunjoo Seo, Robert J. Harrington, Yongju Lee, Hyeok Kim and Sungjin Kim
More accurate self-forecasting not only provides a better-integrated solution for electricity grids but also reduces the cost of operation of the entire power system. To predict solar photovoltaic (PV) power generation (SPVG) for a specific hour, this pa...
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Budiman Putra Asma'ur Rohman, Catur Hilman, Erik Tridianto, Teguh Hady Ariwibowo
Pág. 275 - 288
Solar power is a renewable energy interest many researchers around the world to be explored for human life beneficial especially for electric power generation. Photovoltaic (PV) is one of technology developed massively to exploit the solar power for this...
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Qiang Ni, Shengxian Zhuang, Hanmin Sheng, Song Wang and Jian Xiao
High quality photovoltaic (PV) power prediction intervals (PIs) are essential to power system operation and planning. To improve the reliability and sharpness of PIs, in this paper, a new method is proposed, which involves the model uncertainties and noi...
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