基于蚁群算法的电力负荷预测方法研究

为了提高负荷预测的精度，提出基于改进蚁群算法的电力负荷组合预测方法。该方法以回归分析、灰色模型、二次指数平滑值、龚帕兹模型、弹性系数法、逻辑斯谛模型法、二次移动平均模型为基础建立负荷组合预测模型，利用改进蚁群算法优化组合预测模型的权值，并与单个预测模型进行比较。预测结果表明，基于改进蚁群算法的电力负荷组合预测方法，运算速度快，预测精度高，相对误差小，有一定的实用价值。

Research on Power Load Forecasting Method Based on Ant Colony Algorithm

lu order to improve the accuracy of load forecasting, puts forward the combinatiou forecasting method of electrie power load whieh is based on improved ant colony algorithm. This method establishes load forecast model based on regression analysis, gray model, the two exponential smoothing values, Gompertz model, elastic coefficient method, logistic model, the two, moviug average model. Uses improved ant colony algorithm to decide the weights of optimization combi- nation forecast model, then to compare with single forecasting model. The forecasting resuh shows that the combination forecasting method of electric power based on improved aut colony algorithm has a certain practical value because of its fast operation speed, high accuracy and the smaller relative error.