Transmission planning under uncertainties of wind and load: Sequential approximation approach

This paper introduces a transmission planning model for a system integrating a large amount of remote wind power. We consider uncertainties of wind availability and system load, which are represented by two dependent random variables in the optimization problem. A two-stage stochastic model and sequential approximation approach are applied to solve our total cost minimization problem, which involves a sequence of stochastic optimization problems repeatedly solved with an updated approximation of random parameters until the rate of increment of optimal cost becomes smaller than a positive target value. A wind energy integration goal is achieved by penalizing wind curtailment. As a case study, the Electric Reliability Council of Texas (ERCOT) wind and load data, and a simplified model of its transmission system, is employed.