Short-term PV Power Generation Prediction Based on QFWA-SVM Model

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.