基于分位数回归平均的电力负荷统计建模与预测  

ELECTRIC LOAD MODELING AND FORECASTING BASED ON QUANTILE REGRESSION AVERAGE

作　　者：杨召 徐姣新 Yang Zhao;Xu Jiaoxin(Shangqiu Institute of Technology,Anyang 455000,Henan,China;Shangqiu University,Luoyang 471000,Henan,China)

机构地区：[1]商丘工学院,河南安阳455000 [2]商丘学院,河南洛阳471000

出　　处：《计算机应用与软件》2021年第11期98-103,204,共7页Computer Applications and Software

摘　　要：概率负荷预测能提供未来负荷值变化和不确定性的额外信息,其对于电力系统的规划和运行具有重要意义。通过对一组姊妹点预测进行分位数回归平均来生成概率负荷预测,既可以利用过去几十年的点负荷预测方法,又不依赖于高质量的预测结果。针对2014年全球能源预测竞赛的公开数据进行算例分析,结果验证了该方法的有效性。Probabilistic load forecasting, which provides additional information on the variability and uncertainty of future load values, is becoming of great importance to power systems planning and operations. This paper proposed a practical methodology to generate probabilistic load forecasts by performing quantile regression averaging on a set of sister point forecasts. It could leverage the development in the point load forecasting literature over the past several decades and did not rely so much on high-quality expert forecasts. We conducted a case study using the publicly available data from the Global Energy Forecasting Competition 2014. The results verify the effectiveness of this approach.

关 键 词：电力负荷预测 预测组合 Pingball损失函数 分位数回归 Winkler评分 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]