Journal
IEEE TRANSACTIONS ON POWER SYSTEMS
Volume 30, Issue 6, Pages 3003-3011Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRS.2014.2385861
Keywords
Decomposition; Gaussian copula; stochastic optimization; transmission planning; wind power
Categories
Funding
- National Science Foundation [ECCS 1065224, 1162328]
- Electric Reliability Council of Texas
- Directorate For Engineering
- Div Of Electrical, Commun & Cyber Sys [1162328] Funding Source: National Science Foundation
- Div Of Electrical, Commun & Cyber Sys
- Directorate For Engineering [1065224] Funding Source: National Science Foundation
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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.
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