Robust Optimization for Dynamic Economic Dispatch Under Wind Power Uncertainty With Different Levels of Uncertainty Budget

Since dynamic economic dispatch with wind power uncertainty poses great challenges for power system operation due to its non-linear and uncertain characteristics, this paper proposes a robust optimization model with different levels of uncertainty budget. The dynamic economic dispatch problem is converted into the robust optimization model with an uncertainty budget, which transforms the nondeterministic model into a deterministic optimization problem. Differential evolution is improved by the sequential quadratic programming method and utilized to solve the robust optimization model. Due to the complex-coupled constraints among thermal units, several constraint-handling procedures are proposed to address those constraint limits, which have a significant impact on the efficiency of the whole optimization. The robust optimization model with an adjustable uncertainty budget is implemented in two test systems. The results obtained for the first test system prove the efficiency of differential evolution-based sequential quadratic programming and the constraint-handling procedures; the performance of the second test system reveals that the robust optimization method with different levels of uncertainty budget provides a promising method for solving the dynamic economic dispatch problem with wind power uncertainty.