Adjustable Robust Dynamic Economic Dispatch of Renewable Energy Considering Statistical Information

Robust economic dispatch is a secure and effective approach to account for uncertainties of renewable energy. But because of the fluctuation and intermittent of renewable generation, the conservativeness of robust model is bound to produce additional regulation cost. In this paper, a conservativeness-adjustable robust economic dispatch (CARED) approach is proposed to reduce the conservativeness of robust dispatch (RD) by varying the pre-defined confidence level referring to dispatcher's acceptability to risk. With accuracy statistical information of the forecast error fitted by Gaussian mixture model (GMM), all constraints with uncertain variables are converter to linear constraints and the problem can be solved by convex optimization which is ultra-efficient. Numerical Test results show that the proposed method is effective in reducing the allocation of reserve and the conservativeness of RD with controllable risk level.