Prediction-based optimization for islanded microgrid resources scheduling and management

Abstract

This paper presents an optimal scheduling and real-time power management for islanded microgrid. Based on prediction data, a multi-objective cost function is formulated aiming to minimize the total energy cost by reducing the diesel-generator fuel consumption and load shedding, while respecting the storage parameters and microgrid operation constraints. The problem is solved with two different optimization algorithms. Simulation results prove that the mixed integer linear programing optimization permits to obtain the lower total energy cost for real-time power balancing.