A novel cost-aware multi-objective energy management method for microgrids

This paper proposes a multi-objective energy management method for microgrids which include local generation sources, grid connection, energy storage units and various loads. Minimization of the energy cost and maximization of batterys lifetime in a microgrid are considered as two main objectives which are optimized simultaneously. To achieve these objectives, microgrids central controller must find the best pattern for charging and discharging the battery. To this purpose, there is a need to have information about time-of-use (TOU) grid electricity rates, forecasted load profile and renewable generation levels. Model predictive control (MPC) policy is then utilized for solving the optimization problem and real-time implementation in a closed-loop framework. The performance and effectiveness of the proposed method is verified by simulating a microgrid model with real yearly data for the demand and renewable generation profiles and TOU rates. It is shown that the saving in energy cost can be increased considerably by applying the proposed MPC algorithm instead of a static energy management approach. Furthermore, the proposed algorithm is capable of regulating the battery usage based on the expected lifetime by considering the battery life span maximization objective.