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- W4363649380 abstract "Photovoltaic power generation, which occupies an important position in new energy power generation, is clean and pollution-free. Solar radiation, clear sky index, cloud cover and other natural conditions have a great impact on photovoltaic power generation, so photovoltaic power generation has randomness and volatility, accurate prediction of photovoltaic power generation is very important for grid dispatching. In this paper, a photovoltaic power prediction method of quantum fireworks optimization support vector machine (QFWA-SVM) is proposed. The power of a photovoltaic power plant in Longyan area of Fujian Province is verified by example, and the results show that the method has certain practical application value." @default.
- W4363649380 created "2023-04-11" @default.
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- W4363649380 date "2023-02-24" @default.
- W4363649380 modified "2023-09-25" @default.
- W4363649380 title "Short-term PV Power Generation Prediction Based on QFWA-SVM Model" @default.
- W4363649380 doi "https://doi.org/10.1109/eebda56825.2023.10090655" @default.
- W4363649380 hasPublicationYear "2023" @default.
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