基于时间序列模型的光伏电板发电量预测研究

Research on Generation Prediction of Photovoltaic Panel Based on Time Series Model

光伏发电是实现“碳达峰、碳中和”目标的重要途径之一,而光伏发电功率受自然因素的影响较大。为提高光伏发电功率的预测精度,以某太阳能电厂的发电数据为基础,运用机器学习的方法,通过ARIMA和Prophet模型来预测太阳能电厂未来发电量。经实验证明,2个模型都能达到较好的预测效果。

Photovoltaic power generation is one of the important ways to achieve“carbon peak and carbon neutrality”,while it is greatly affected by natural factors.In order to improve the prediction accuracy of photovoltaic power generation,the 34-day power generation data of a solar power plant is taken as the research object,and the future power generation of solar power plant is predicted through ARIMA and Prophet models with the help of machine learning method.Experimental results show that both models can predict solar energy generation.