基于SARIMA模型的短期天然气负荷区间预测

Short-Term Natural Gas Load Forecasting Based on SARIMA Model

天然气负荷预测对居民生活、商业发展、工业生产等领域都起着决定性作用,且精确的短期负荷预测可以有效量化天然气负荷预测的不确定性,对于能源系统运行调度避险十分关键。天然气负荷由于受到季节的影响会出现巨峰特征,传统的点预测模型没有考虑到天然气的季节性影响,预测结果的准确性偏低。SARIMA模型可以处理具有季节性波动趋势和随机干扰的时间序列数据。因此,采用SARIMA模型对天然气负荷进行去日、季、周期性以及一阶差分的处理,捕获时间序列中的线性特征与季节性特征,依据赤池信息准则与网格搜索确定最优参数模型,按比例划分短期区间预测数值。以西安市天然气用量为例,与传统模型对比,结果表明采用SARIMA模型在序列强季节性区间内误差小,具有较高的准确性。

Natural gas load forecasting plays a decisive role in residential life,commercial development and industrial produc‐tion.And accurate short-term load forecasting can effectively quantify the uncertainty of natural gas load forecasting,which is critical for energy system operation and scheduling risk avoidance.The natural gas load affected by the seasonal effects will ap‐pear giant peak characteristics,the traditional point prediction model does not take into account the seasonal effects of natural gas,the accuracy of the prediction results is low.The SARIMA model can handle time series data with seasonal fluctuation trends and stochastic disturbances.Therefore,the SARIMA model is used to de-periodize the natural gas load as well as the first-order difference,capture the linear and seasonal features in the time series,determine the optimal parameter model based on the red pool information criterion and grid search,and proportionally divide the short-term interval forecast values.Taking the natural gas usage in Xi’an as an example,the results show that the SARIMA model used has a small error in the strong seasonal interval of the series and has a high accuracy when compared with the traditional model.