Research on New Energy Power Generation Power Prediction Method Based on Machine Learning

Abstract

Due to the influence of many high random factors on the new energy power generation system, the electric energy output by the generator is extremely unstable, which increases the difficulty of predicting the power generation. Traditional power generation forecasting methods are highly dependent on data, and the accuracy of the forecast results is largely affected by the integrity of the data. Therefore, it is necessary to study new energy generation power forecasting methods. Technological progress in the field of machine learning and artificial intelligence has provided an effective way for new energy power generation power prediction and a convenient method to improve the prediction accuracy. According to the mechanism characteristics of new energy power generation system, this paper analyzes the feasibility of machine learning algorithm to deal with the problem of new energy power generation power prediction; studies various models and algorithms related to power system power prediction; proposes a new energy power generation power prediction based on deep learning algorithm model, and use the historical data of a new energy power station in a certain place for simulation. The simulation results show that the machine learning algorithm model can significantly reduce the prediction error and improve the accuracy of power generation prediction.