Preast Simulation of Maximum Power Generation of Smart Photovoltaic Station Under Voltage Fluctuation
The stability of the output voltage of smart photovoltaic stations is critical to the overall operation of the power grid.The coupling effect of voltage and meteorological factors(such as solar radiation,temperature,etc.)makes its fluctuations random,increasing the complexity of power generation forecasting and reducing the accuracy of fore-casting.Therefore,a prediction method for maximum power generation of smart photovoltaic stations considering voltage fluctuation is proposed.The combination of the AdaBoost algorithm and SVM algorithm is used to classify and process the types of voltage fluctuations,and obtain the voltage fluctuations under different weather conditions.The deep belief network is introduced,and the classification results of voltage fluctuation types are taken as the input char-acteristics of the prediction model.In the case of voltage fluctuations,the maximum power generation of smart photo-voltaic stations is predicted to adapt to the randomness of voltage fluctuations and improve the prediction accuracy.A large number of experimental tests show that the proposed method has a better prediction effect on the maximum power generation of smart photovoltaic stations,and can comprehensively promote the sustainable development and application of clean energy technology.
Voltage fluctuationSmart photovoltaic stationsMaximum power generation forecastDeep belief net-work
万方数据
维普
