Distributionally robust dynamic economic dispatch model with conditional value at risk recourse function

To control the risk of intraday operation incurred by wind power, this paper proposes a distributionally robust dynamic economic dispatch model with conditional value at risk (DRDED-CVaR) recourse function, where the CVaR recourse function is used to measure the risk of load shedding and wind spillage. In contrast to traditional stochastic optimization and robust optimization, the DRDED-CVaR model describes the uncertain wind power output considering all possible probability distribution functions (PDF) with mean and covariance information derived from historical data, and it optimizes the expected operation cost under the worst possible distribution. We derive an equivalent semidefinite programming (SDP) for the DRDED-CVaR model and use the delayed constraint generation (DCG) algorithm and the alternate convex search (ACS) algorithm to solve this model. The proposed DRDED-CVaR is compared with the existing dynamic economic dispatch (DED) model on the IEEE 30-bus system. The simulation results demonstrate that the DRDED-CVaR model can effectively control the risk of load shedding and wind curtailment according to the risk preference of the operators.