# Review of Energy Management Systems in Microgrids
## 3 Energy Management Systems Applications in Microgrids  
Microgrids contribute to low carbon emissions by increasing the diversity in energy production as well as the efficiency in energy consumption. In these systems, important issues such as energy management, adjustment of energy supply according to demand, efficient use of energy, and protection of power quality are addressed. Therefore, effective energy management in microgrids is extremely important for the reliability, sustainability, and economy of the system. Energy management goals and practices in a microgrid depend on the user's preferences. Targets are influenced by factors such as geographic location, installed equipment, types of loads to be supplied, grid energy tariff structures, government regulations, and energy storage and generation options on the microgrid. Due to the modular and highly customizable nature of a microgrid, each microgrid has a unique set of goals. In general, the main purpose of a microgrid is to reduce operating costs by maximizing the savings of a microgrid through renewable energy and minimizing generation costs. As presented in Figure 4, microgrid energy management applications are carried out with targets such as environment, capital and operating costs, and energy storage costs. Ref. [42] designed a centralized control system for energy management in an interconnected microgrid based on the concept of flexibility for the end users. It was possible to attain an ideal economic dispatch by employing quadratic programming. This grid was integrated with a photovoltaic system. A modified IEEE 33-node grid was used to test the algorithm. A mixed-mode microgrid energy management system with power sharing, continuous run, and on/off base was proposed by [43]. The power-sharing mode allows for power trading with the main grid, but the fuel cell must always operate in continuous run mode. Both modes are solved using linear programming, an optimization technique. In contrast, a mixed-integer linear programming solution approach is used to solve the on/off mode, maximizing the microgrid's performance concerning the fuel cell, energy storage system, and the on/off connection status of the main grid. The microgrid's operational requirements are taken into consideration when determining the size of the energy storage system. Figure 4: Microgrid energy management objectives. By using a solar desalination system, an energy management system for a hybrid AC/DC microgrid in a remote community was investigated [44]. The proposed optimization algorithm uses mixed-integer non-linear programming as the foundation for its goal function, which minimizes daily operating costs. A proposal for a mixed-integer nonlinear energy management model of an isolated three-phase unbalanced microgrid can be found in [45]. The designed system reduces fuel consumption, system costs, and reactive power penalty costs. Energy storage systems, transmission lines, and transformer mathematical models were developed. Two successive stages of a mixed-integer nonlinear-based unit commitment model and optimal power flow model form the developed model. Ref. [46] studied how to parametrize the uncertainty of solar and wind energy generation in a microgrid using mixed-integer linear programming to manage energy in the microgrid. Two levels of optimization are accomplished. The selection of the parametrization scheme comes first, followed by operational decisions that take market price variation and storage system disposition into account. A multi-timescale-based energy management system was presented by [47]. Two factors are taken into account in the optimization problem: dynamic compensation in real time and daily static programming. The optimal load flows in a mixed-integer quadratic programming method are used to solve this, and data on solar irradiation and wind speed and direction are used to forecast the batteries' load state. Ref.