摘要
针对电网短期负荷预测中传统方法预测精度较低的问题,提出一种基于反向传播人工神经网络(backpropagation artificial neural network,BP-ANN)短期负荷预测的方法。应用多尺度熵法对短期负荷数据进行分析,得出预测点不仅和前期临近数据相关,而且和远期历史负荷数据相关;同时运用自相关分析法,基于BP-ANN建立适合陕西电网的短期负荷预测方法,并将此方法应用于实际电网负荷中,结果表明此方法简单可行,精度较高,比较实用。
： Aimed at the problem of low accuracy of traditional method for power system short-term load forecast, this paper presents a method for short-term load forecasting based on BP-ANN（ back-propagation artificial neural network）. The multiscale entropy method was used to analyze the short-term load data, Whose results showed that the forecast points were related to both the prophase adjacent data and the periodical long-term historical load data. Meanwhile, with using autocorrelation analysis method, the suitable method for short-term load forecasting of Shaanxi power grid was presented based on BP-ANN, and applied in practical power system load. The results have shown that this method is simple, feasible, more practical, and with high precision.
出处
《电力建设》
2014年第3期54-58,共5页
Electric Power Construction
基金
国家电网公司科技项目(5227221303A0
5227221302A2)
