Distributionally Robust Multiperiod Dispatch Optimization with Uncertainty Modeling for Renewable Generation and Distributed Energy Resources

The core message of this article is to propose a novel approximation method for multiple joint chance constraints (JCCs) to model the uncertainty in power system dispatch problems, which solves the conservativeness and potential infeasibility concerns of the conventional Conditional Value at Risk (CVaR) method. The proposed method is then extended to handle multiple data-driven distributionally robust joint chance constraints (DRJCCs) that fit the practical scenario of power system dispatch problems where the distribution of uncertain variables is often inaccessible.