An efficient preprocessing approach for uncertainty consideration in microgrids

Uncertainty considerations in microgrid operation and planning are of significant importance as uncertain factors can potentially alter the operator's decisions. New mathematical approaches, such as robust optimization, are commonly adopted to capture uncertainties and ensure practicality. However, this added practicality is at the expense of increased problem size and computational complexity. This paper presents a detailed discussion and analysis of prevailing uncertainties in microgrid operation and planning, and accordingly proposes a new preprocessing approach to integrate uncertainties while reducing computational requirements. Numerical simulations exhibit the merits of the proposed approach over the commonly used robust optimization method from the execution time and practicality perspectives.