Stochastic SCUC Solution With Variable Wind Energy Using Constrained Ordinal Optimization

This paper proposes a constrained ordinal optimization (COO) based method for solving the scenario-based stochastic security constrained unit commitment problem. The basic idea is to sample a large number of candidate unit commitment (UC) solutions by a crude model and then use an accurate model on a small selected subset to find good enough UC solutions over all scenarios. To facilitate the proposed method, a feasibility model is utilized that applies analytical conditions for identifying the feasibility of UCs. A blind picking approach based on the feasibility model is incorporated in the COO-based method for seeking good enough solutions. Numerical tests are performed on a modified IEEE 118-bus system with a high penetration of wind energy, in which hourly forecast errors of wind speed and loads and random outages of system components are considered. The simulation results show the validity and the effectiveness of the proposed method. Comparative evaluations of the proposed COO-based method with mixed-integer linear programming solvers are considered in this paper.