优化灰色模型在负荷预测中的应用研究

针对传统的灰色模型在负荷增长速度较快时预测精度低的问题,提出了采用交叉遗传粒子群优化算法代替最小二乘法来优化GM(1,1)模型中参数a、b的方法;介绍了灰色预测原理及其数学模型、CGPSO算法及基于CGPSO算法的优化灰色模型,并根据实际负荷数据进行了仿真实验。结果表明,在负荷增长速度较快时,优化灰色模型的预测精度明显高于GM(1,1)模型,能够应用于电力系统的中长期负荷预测,拓展了灰色模型的适用范围。

Research of Application of Optimized Grey Model in Power Load Forecasting

In order to solve the problem of low forecasting accuracy of traditional grey model when power load increases fast,the paper presented a method of using crossover genetic particle swarm optimization algorithm instead of least-squares algorithm to optimize parameters a and b in GM(1,1) model,introduced grey prediction theory and its mathematical model,CGPSO algorithm and optimized grey model,and completed simulation based on actual load data.The results showed the prediction accuracy of the optimized grey mo...