Robust Optimal Power Flow with Wind Integration Using Conditional Value-at-Risk

Abstract

Integrating renewable energy into the power grid requires intelligent risk-aware dispatch accounting for the stochastic availability of renewables. Toward achieving this goal, a robust DC optimal flow problem is developed in the present paper for power systems with a high penetration of wind energy. The optimal dispatch is obtained as the solution to a convex program with a suitable regularizer, which is able to mitigate the potentially high risk of inadequate wind power. The regularizer is constructed based on the energy transaction cost using conditional value-at-risk (CVaR). Bypassing the prohibitive high-dimensional integral, the distribution-free sample average approximation method is efficiently utilized for solving the resulting optimization problem. Case studies are reported to corroborate the efficacy of the novel model and approach tested on the IEEE 30-bus benchmark system with real operation data from seven wind farms.