A robust model for daily operation of grid-connected microgrids during normal conditions

Abstract

Microgrids (MGs) are designed to serve their hosting critical load in an island mode in case of major events. However, in normal conditions when MGs are in a grid-connected mode, they may face an opportunity to achieve financial profits through optimization of the operation of energy resources and proper participation in wholesale markets. This paper proposes a model to optimize the participation of MGs in the markets and operation of energy resources. Since MGs usually host renewable energy resources, making decisions without considering uncertainties may put MGs at risk. Therefore, the model considers uncertainties associated with the generation of renewable Distributed Generation (DGs), demand, and market prices via robust optimization technique. The model is formulated as a bi-level max-min optimization problem. The problem is solved in two iterative steps. In the first step, a Genetic Algorithm (GA) finds the worst situation of uncertain parameters such that MG profit is minimized. Then, a mixed-integer linear problem is solved to maximize the profit over MG decision variables considering the values determined in the first step. The steps are iterated to reach convergence to the best solution. To confirm the performance of the approach, it is applied to a typical MG and the results are reported.