基于IAFSA-GM的化工园区光伏电站功率预测模型

Power forecasting of photovoltaic station in chemical industrial park based on IAFSA-GM

光伏电站已在国内大型化工园区内广泛使用,为了提高GM(1,1)模型的化工园区光伏电站功率预测精度,研究了灰色系统理论中GM(1,1)预测模型的建模机理,系统地分析了GM(1,1)模型在化工园区光伏电站功率预测建模过程中对背景值和初始值等规定的不合理性。本文提出并使用IAFSA直接对背景值和初始值进行优化,并结合滚动式数据更新模式构建了一种改进GM(1,1)预测模型。基于化工园区的光伏电站实例结果表明,上述所提模型是有效和完善的,可显著提高GM(1,1)模型的预测精度。

Photovoltaic power stations have been widely used in large chemical industrial park in China,in order to improve the prediction accuracy of GM(1,1)model,the modeling mechanism of GM(1,1)model of gray system theory is studied in this paper.And the irrationalities of background and initial value in the modeling process are systematically analyzed with GM(1,1)model.This paper expounds and adopts the improved artificial fish swarm algorithm(IAFSA)to optimize the background and initial values directly.Then combining with the rolling data update mode,an improved prediction model of GM(1,1)is proposed.The simulation results of photovoltaic station in chemical industrial park show that the proposed model is effective and prefect,and can improve the prediction model of GM(1,1)effectively.