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This paper demonstrates a double layer optimization strategy to determine the optimum size of battery energy storage system (BESS) considering the EMS of a microgrid (MG). In the developed model, the BESS sizing problem is viewed as the outer optimal loop and the economic dispatch of MG based on BESS data from the outer loop is considered as inner loop. An iterative method and a dynamic programming (DP) method are utilized to solve the optimal problems for outer and inner models respectively. A simulator is built in MATLAB environment for an island microgrid is used to evaluate the efficiency of the proposed method.

With the dramatic development of renewable energy resources all over the world, Vietnam has started to apply them along with the conventional resources to produce the electrical power in recent years. Visually, the aim of this action is to improve the economic as well as the environmental benefits. Therefore, a vast of hybrid systems that combine Wind turbine, Photovoltaic (PV), Diesel generator and battery have been considered with different configurations. According to this topic, there are lots of research trends in the literature. However, we aim to the optimal energy management of this hybrid system. In particular, in this paper, we propose an optimization method to deal with it. The interesting point of the proposed method is the usage of the information of sources, loads, and electricity market as an embedded forecast step to enhance the effectiveness of the actual operation via minimizing the operation cost by scheduling distributed energy resources (DER) while regarding emission reduction in the hybrid system is considered as the objective function. In this optimization problem, the constraints are determined by two terms, namely: the balance of power between the supply and the load demand, and also the limitations of each DER. Thus, to solve this problem, we make use of the dynamic programming (DP) to transform a system into a multi-stage decision procedure with respect to the state of charge (SOC), resulting in the minimum system cost (CS). In order to highlight the pros of the proposed method, we implement the comparison to a rule-based method in the same context. The simulation results are examined in order to evaluate the effectiveness of the developed methodology, which is a so-called global optimization.

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