基于模糊集理论的短期电力负荷预测

Short-term load forecasting based on fuzzy set technology

利用BP神经网络进行电力系统短期负荷预测,应用模糊集理论将天气、温度等敏感因素模糊化后作为BP神经网络的一部分输入进行训练,构造了相应于不同季节的预测模型,预测未来一天12小时负荷。典型算例的计算表明,该方法是有效的。

In this paper, BP artificial neural network is applied for short-term load forecasting. It choosees sensitive factors such as climate,temperature that are fuzzified using fuzzy set technology as a part of BP neural network's inputs for training, the forecasting models for different seasons are constructed to forecast hourly loads for the next hour to 12 hours out. The result of typical calculation examples shows that the presented method is effective.