Probabilistic Power Flow Studies for Transmission Systems With Photovoltaic Generation Using Cumulants

被引：297

作者：

Fan, Miao ^{[1
]}

Vittal, Vijay ^{[1
]}

Heydt, Gerald Thomas ^{[1
]}

Ayyanar, Raja ^{[1
]}

机构：

[1] Arizona State Univ, Dept Elect Comp & Energy Engn, Tempe, AZ 85287 USA

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 2012年 / 27卷 / 04期

关键词：

Cornish-Fisher expansion; correlation; cumulant; Edgeworth expansion; Gram-Charlier expansion; photovoltaic generation; probabilistic power flow study; renewable resources; stochastic power flow study; LOAD FLOW;

D O I：

10.1109/TPWRS.2012.2190533

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper applies a probabilistic power flow (PPF) algorithm to evaluate the influence of photovoltaic (PV) generation uncertainty on transmission system performance. PV generation has the potential to cause a significant impact on power system reliability in the near future. A cumulant-based PPF algorithm suitable for large systems is used to avoid convolution calculations. Correlation among input random variables is considered. Specifically correlation between adjacent PV resources are considered. Three types of approximation expansions based on cumulants, namely the Gram-Charlier expansion, the Edgeworth expansion, and the Cornish-Fisher expansion, are compared, and their properties, advantages, and deficiencies are discussed. Additionally, a novel probabilistic model of PV generation is developed to obtain the probability density function (PDF) of the PV generation production based on the environmental conditions. The proposed approaches with the three expansions are compared with Monte Carlo simulations (MCS) with results for a 2497-bus representation of the Arizona area of the Western Electricity Coordinating Council (WECC) system.

引用

页码：2251 / 2261

页数：11

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