不确定PV-EVs概率潮流降阶扩展累积估计  

Reduced order extended cumulative estimation of probabilistic power flow considering uncertain PV-EVs

作　　者：刘媛媛[1] Liu Yuanyuan(School of New Energy Technology,Nanjing University,Nanjing 210000,China)

机构地区：[1]南京大学新能源学院,江苏南京210000

出　　处：《电子技术应用》2018年第11期158-164,共7页Application of Electronic Technique

摘　　要：为提高现代电力系统概率潮流分析的精度和有效性,提出一种考虑不确定光伏发电和电动汽车充电(PVEVs)的概率潮流Cornish-Fisher级数(CFM)降阶扩展累积估计方法。首先,针对现代社会中光伏发电和电动汽车日益增多的情况,在对电力系统概率潮流计算中同步考虑了这两方面因素所带来的概率潮流计算模型的不确定性;其次,分类考虑了插入式混合动力电动汽车(PHEV)和电池电动车(BEV)充电问题,并采用不同的排队模型表征小区充电和公共充电站充电模型。最后,采用基于Cornish-Fisher级数的扩展累积估计方法对模型系统进行估计,实现了估计模型的降阶处理,提高了计算效率。通过在Ward-Hale 6-bus供电系统和IEEE 140-bus配电系统上的仿真实验,验证了所提方法的有效性。In order to improve the accuracy and effectiveness of probabilistic power flow analysis in modern power system,a reduced order extended cumulant estimation method for probabilistic power flow Cornish-Fisher series(CFM)considering uncertain photovoltaic generation and electric vehicle charging(PV-EVs)is proposed.Firstly,in view of the increasing number of photovoltaic and electric vehicles in modern society,the uncertainties of probabilistic load flow models caused by these two factors are considered simultaneously in the probabilistic power flow calculation of power system.Secondly,we consider the charging problem of plug-in hybrid electric vehicle(PHEV)and battery electric vehicle(BEV),and use different queuing models to characterize the charging models of cell charging and public charging stations.Finally,we use the Cornish-Fisher series expansion cumulant estimation method to estimate the model system,achieve the reduced order processing of the estimation model,and improve the computing efficiency.The effectiveness of the proposed method is verified by the simulation experiments on the Ward-Hale 6-bus power supply system and the IEEE 140-bus distribution system.

关 键 词：光伏发电 电动汽车 概率潮流 累积估计 排队模型 

分 类 号：TM744[电气工程—电力系统及自动化]