电力短期负荷预测相似日选取算法

A Novel Algorithm of Selecting Similar Days for Short-term Power Load Forecasting

短期负荷预测是电力系统安全经济运行的基础,相似日选取的准确与否直接影响到短期负荷预测算法的精度。针对短期负荷预测的特点,提出一种能便于考虑各种因素影响的新算法。分析了气象、日类型等因素对负荷影响的常见规律,便于识别主导负荷变化的因素,建立了在短期负荷预测中选取相似日的新方法。理论和实例均表明,该方法适应性较强,能够通过历史数据分析从历史日中选取最合适的相似日,对提高短期负荷预测的精度具有较大价值。

Short-term load forecasting is the basis of safe and economical operation of power grids. The accuracy of selecting similar days directly influences the degree of accuracy of the short-term load forecasting algorithm. After an in-depth analysis of the common laws of such factors as the meteorological factors and the day type that impact power loads, a new algorithm of selecting similar days for the short-term load forecast is proposed. The algorithm can distinguish between the key factors in many cases. The simulation results demonstrate that it can select the most suitable similar day from a large number of historical data to improve the accuracy of short-term load forecasting with relatively strong adaptability.