西安市天然气冬季短期负荷预测研究

Short-term Load Prediction of Natural Gas in Winter in Xi'an City

通过验证西安市冬季天然气门站小时流量时间序列的混沌特性,利用改进的混沌时间序列负荷预测方法,进行了小时流量短期预测。冬季天然气门站流量时间序列可以分解为周期与混沌两种子模型的线性叠加,针对混沌子模型引入加权一阶局域法进行混沌短期负荷预测,提高了总负荷预测精度。

Through verifying the chaotic characteristics of hourly flow rate time series at Xihn natural gas gate station in winter, the short-term prediction of hourly flow rate is performed by using the improved chaotic time series load prediction method. The flow rate time series at the natural gas gate station in winter can be decomposed as a linear superposition of periodical sub-model and chaotic sub-model. The adding-weight one-rank local prediction method is introduced into the chaotic sub-model to perform the chaotic short-term load prediction, which improves the total load prediction accuracy.