A Model Predictive Control Approach for Efficient Optimization of Microgrid Operations using Mixed Integer Linear Programming

Abstract

Microgrid is a subsystem comprises of distributed generator (DG) s, non-conventional generators, storage devices and controllable loads. Microgrids are one of the centers for penetration of non-conventional energy resources, storage backup and management of distribution generation units. It results reduction in costs, emission gases, transmission & distribution losses and also conventional energy crisis. Simply it is highly reliable and ecofriendly. In this paper, we present a study of Model Predictive control (MPC) Approach using mixed integer linear programming (MILP) technique while satisfying operational constraints and a time varying requests. MILP technique is used to formulate the Overall optimization problem and commercial solvers are used for substantial improvements in solution quality and computational burden. To assess the performance of the online optimization-based control strategy a microgrid case study is employed and the simulation results are discussed. A modification for above case study was done by considering uncertainties of non-conventional energy. During uncertainties to meet the critical load demand, DG Units are increased. The results show the effectiveness and feasibility of the proposed approach.