A Stochastic Transmission Planning Model With Dependent Load and Wind Forecasts

被引：85

作者：

Park, Heejung ^{[1
]}

Baldick, Ross ^{[1
]}

Morton, David P. ^{[2
]}

机构：

[1] Univ Texas Austin, Dept Elect & Comp Engn, Austin, TX 78712 USA

[2] Univ Texas Austin, Dept Mech Engn, Austin, TX 78712 USA

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 2015年 / 30卷 / 06期

基金：

美国国家科学基金会;

关键词：

Decomposition; Gaussian copula; stochastic optimization; transmission planning; wind power; DECOMPOSITION APPROACH; EXPANSION; OPTIMIZATION; COST;

D O I：

10.1109/TPWRS.2014.2385861

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 introduces a two-stage stochastic program for transmission planning. The model has two dependent random variables, namely, total electric load and available wind power. Given univariate marginal distributions for these two random variables and their correlation coefficient, the joint distribution is modeled using a Gaussian copula. The optimal power flow (OPF) problem is solved based on the linearized direct current (DC) power flow. The Electric Reliability Council of Texas (ERCOT) network model and its load and wind data are used for a test case. A 95% confidence interval is formed on the optimality gap of candidate solutions obtained using a sample average approximation with 200 and 300 samples from the joint distribution of load and wind.

引用

页码：3003 / 3011

页数：9

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