July 7, 2022
Energy Storage System (ESS) in Microgrids
Energy Storage System (ESS) in Microgrids


This paper presents a methodology for optimal allocation and economic analysis of energy storage system (ESS) in microgrid (MG) based on net present value (NPV). Since the performance of MG largely depends on the arrangement and arrangement of ESS, an optimal ESS device allocation method and economical operation strategy for MG are required. At MG, we discuss the financial advantages and dynamic models of ESSs to optimize their operational strategies and capacity. Then, a matrix real coding genetic algorithm is applied to find the maximum NPV of each GA chromosome consisting of a two-dimensional real matrix representing the ESS’s development schedule and distributed power generation source. This paper intends to propose the optimal size, type, and optimal arrangement of the currently available ESSs so that the total NPV achieved during the operating life of the system is maximized. Finally, some computational simulation results are presented to verify the effectiveness of the proposed method.

A genetic algorithm-based method for sizing energy storage systems (ESSs) in microgrids. The main goal of the proposed method is to find the energy and power capacity of the storage system that minimizes the operating cost of the microgrid. The energy management strategy (EMS) used in this paper is based on the fuzzy expert system responsible for setting the power output of the ESS. The design of EMS is accomplished through genetic algorithms used to establish fuzzy rules and member features of expert systems. Considering that the size of the storage system has a great influence on the energy management strategy, in this paper, EMS and ESS capacity are jointly optimized. In addition, the proposed method predicts the lifespan of the ESS using an aging model. In this way, you can determine the costs associated with energy storage in a more accurate way. The critical unit input problem for the proper operation of the microgrid was also considered in this study. The proposed sizing methodology was validated in two case studies.

A microgrid (MG) is a regional entity composed of distributed energy resources (DER) to achieve regional power reliability and sustainable energy utilization. Renewable energy technologies integrated with the MG concept or energy storage system (ESS) are gaining interest and popularity as they can store energy at peak times and supply energy at peak times. However, the existing ESS technology suffers from difficulties in energy storage due to various problems such as charge/discharge, safety, reliability, size, cost, life cycle, and overall management. Therefore, to improve the performance of ESSs in MG applications, advanced ESSs are required in terms of capacity, protection, control interfaces, energy management and characteristics.

In this paper, types of ESS technologies, ESS structures and their composition, classification, characteristics, energy conversion and evaluation process are comprehensively reviewed. In addition, we analyzed the details of the advantages and disadvantages of ESS in MG applications based on energy formation process, material selection, power transmission mechanism, capacity, efficiency and cycle cycle. Existing reviews critically demonstrate the current technology for ESS in MG applications. However, optimal management of ESS for efficient MG operation remains a challenge in modern power system networks. This review also highlights key factors, issues and challenges along with possible recommendations for further development of ESSs in future MG applications. All of the insights highlighted in this review contribute significantly to the growing effort to develop cost-effective and efficient ESS models with extended lifecycles for sustainable MG implementations.