基于加权双高斯分布的广义自回归条件异方差边际电价预测模型  

A Generalized Auto-Regressive Conditional Heteroskedasticity Model for System Marginal Price Forecasting Based on Weighted Double Gaussian Distribution

作　　者：刘西陲[1] 沈炯[1] 李益国[1] 

机构地区：[1]东南大学能源与环境学院,江苏省南京市210096

出　　处：《电网技术》2010年第1期139-144,共6页Power System Technology

摘　　要：研究电力市场系统边际电价(system marginal price,SMP)条件方差的变化规律及残差的统计分布特征,据此引入广义自回归条件异方差(generalized auto-regressive conditional heteroskedasticity,GARCH)模型,并建立了基于加权双高斯(weighed double Gaussian,WDG)分布假设的GARCH模型(GARCH-WDG)对系统边际电价的变化规律进行研究。美国PJM市场和澳大利亚NSW市场的实际数据表明,GARCH模型对电价的估计和预测均有良好的效果,GARCH-WDG模型则进一步改善了GARCH模型的性能。The regularity of conditional variance variation and the statistical distribution characteristic of residual error of system marginal price （SMP） in electricity market are researched. On this basis, by means of leading in the generalized auto-regressive conditional heteroskedasticity （GARCH） model a GARCH model based on the assumption of weighted double Gaussian （WDG） distribution is proposed to research the variation regularity of SME Taking the actual data from PJM market in USA and NSW market in Australia as samples, both GAR, CH model and the proposed GARCH-WDG model are tested, the testing results show that the GARCH model can offer good estimation and forecasting results of SMP, and the performance of GARCH model can be further improved by the proposed GARCH-WDG model.

关 键 词：系统边际电价 加权双高斯分布 广义自回归条件异方差 电价预测 

分 类 号：F416.2[经济管理—产业经济]