基于RBF神经网络的短期负荷预测

Short-term Load Forecasting Based on RBF Neural Network

短期电力负荷预测是电力系统运行调度中一项重要的内容,传统的电力负荷预测方法都是建立在线性假设基础之上,由于预测精度低,难以满足现在电力部门的要求。人工神经网络己被应用在电力负荷预测中,并取得了较为理想的结果。主要基于神经网络的负荷预测模型,通过MATLAB仿真实验平台,构建RBF神经网络模型,并用历史电力负荷数据进行训练,成功的进行了电力系统的短期负荷预测,预测结果误差较小,取得了令人满意的结果。

Short-Term Load Forecasting is one of the most important contents of running and dispatching power system.Traditonal load forecasting method is establish the linear hypothesis on the basis of its low prediction accuracy.It is difficult to meet the requirements of the electricity sector.ANN have been applied in power load forecasting,and get the results.This paper builds a RBF neural network model based on MATLAB.Trains short-term load forecasting of a power system by using the historical data.The error of the prediction is relatively small and the results are satisfactory.