A Comparative Study of Optimization- and Rule-Based Control for Microgrid Operation

Abstract

As local renewable energy based generation units are being deployed worldwide, distribution grids are facing integration challenges. Here, microgrids provide a solution, by allowing intentional islanding and connection to the public distribution grid depending upon its current state. Microgrids may consist of loads, generation units and storages which can be operated as a single controllable entity. This paper investigates two control approaches for cost-efficient operation of grid-connected microgrids: optimization- and rule-based control. For optimizationbased control, a model predictive control algorithm with mixed integer linear programming formulation is used. A case study for a microgrid in an office building consisting of distributed generation units and different storage units is presented to assess the performance of the two control approaches. The simulation results show the effectiveness of the optimization-based approach and a potential for lower microgrid operating costs compared to the rule-based approach.