Pre-Perturbation Operational Strategy Scheduling in Microgrids by Two-Stage Adjustable Robust Optimization

A two-stage adaptive robust optimization is developed for pre-disturbance scheduling in microgrids (MGs) handling uncertainties associated with electricity market prices, renewable generation, demand forecasts, and islanding events. The objective to produce a reliable optimal solution MG operation that minimizes operational costs the risk/failure In literature, uncertainty sets events cover full period which results sub-optimal solution. this paper, corresponding are modeled based on reliability/resiliency-oriented indexes of MG/grid achieve more accurate/reliable Besides, Benders decomposition algorithm used handle solving problem time-consuming. Therefore, column-and-constraint generation (C&CG) strategy adopted make computationally tractable. Further, budget parameters clarified balance conservatism optimality (cost minimization) sets. effectiveness proposed framework evaluated discussed by using set numerical studies different scenarios an MG. simulations show reduces precise analysis budgets change periods.