摘要： 以区域负荷作为研究对象,分析区域负荷与电网负荷在变化波形性、周期性等方面的特征差异。针对区域负荷变化过程中时序关联性较弱的特点,提出基于金字塔模型的区域负荷自适应超短期预测方法。采用灰色关联分析法,提取与负荷变化具有强关联性的客观特征因素。建立自适应增强随机权网络,加强模型对负荷特征的学习能力以及最优求解效率。设计分层金字塔模型结构,采用滚动淘汰的方式,提升预测模型对区域负荷特征变化的自适应性,降低区域负荷变化趋势突变对超短期预测精度的影响。仿真结果表明,该方法可准确跟随区域负荷变化趋势,具有较高的预测精度与稳定性。

关键词: 区域负荷, 趋势特征, 超短期预测, 金字塔模型, 随机权网络

Abstract: Taking the regional load as the research object,the differences of volatility and periodicity between regional load and grid load are analyzed.According to the characteristics of weak temporal correlation in the process of regional load change,a kind of ultra-short term regional load prediction method based on pyramid model is proposed.The gray relational analysis method is used to extract the objective characteristics of strong correlation with load change.The Adaptive Boosting Random Weighted Network (Ada-RWN) model is established to enhance the ability of load trend characteristics learning and optimal solution efficiency.A hierarchical pyramid model structure,which uses the method of rolling out to improve the adaptability of the forecasting model to the regional load characteristics,is designed to reduce the influence of the regional load variation trend on the ultrashort prediction accuracy.Simulation results show that the proposed method can follow the trend of regional load change and has high prediction accuracy and stability.

Key words: regional load, trend characteristics, ultra-short term prediction, pyramid model, random weighted network

中图分类号: 

• TP311