Tri-Level Mixed-Integer Optimization for Two-Stage Microgrid Dispatch With Multi-Uncertainties

To meet the diverse operational requirements of microgrids with multi-uncertainties, a tri-level two-stage mixed-integer robust optimization model is proposed to solve the optimal scheduling problem with source-load power and unit N-1 uncertainties. In the first stage, the optimal goal is to obtain robust scheduling plans that can be applied effectively in satisfying the operation and adjustment constraints, as well as to find the minimal operating cost in the basic scenario. Considering the system may concern a specific operating factor (e.g., load satisfaction rate) under a N-1 contingency, the second stage of the model minimizes the total energy of load shedding and renewable energy abandonment in the worst scenario. As the proposed robust model is a multi-level coupled mixed-integer optimization problem, which is difficult to address by either the duality method or the Karush-Kuhn-Tucker (KKT) method, a novel nested reformulation-and-decomposition (R&D) algorithm is proposed to handle this complex problem. Numerical simulations and tests have verified the effectiveness and superiority of the proposed robust model and the solution algorithm. Furthermore, the robust optimal schemes satisfy the engineering application more reasonably.