A Stochastic Transmission Planning Model With Dependent Load and Wind Forecasts


This paper introduces a 2-stage stochastic program for transmission planning. The model has two dependent random variables, specifically, total electric load and out there wind power. Given univariate marginal distributions for these two random variables and their correlation coefficient, the joint distribution is modeled employing a Gaussian copula. The optimal power flow (OPF) drawback 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 take a look at case. A 95% confidence interval is made on the optimality gap of candidate solutions obtained using a sample average approximation with two hundred and 300 samples from the joint distribution of load and wind.

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