From an energy management standpoint, natural phenomena such as solar irradiation and wind speed are uncontrolled variables, so the correlation between the energy generated by renewable energy sources and energy demand cannot always be predicted. For this reason, energy storage systems are used to provide more efficient renewable energy systems. In these systems, energy management systems are used to control the energy storage system and establish a balance between the generated power and the power demand. In addition, especially in wind turbines, rapidly varying wind speeds cause wind power fluctuations, which threaten the power system stability, especially at high power levels. Energy storage systems are also used to mitigate the power fluctuations and sustain the power system's stability. In these systems, another controller which controls the energy storage system power to mitigate power fluctuations is required. These two controllers are different from each other. In this study, a combined energy management algorithm is proposed which can perform both as an energy control system and a power fluctuation mitigation system. The proposed controller is tested with wind energy conversion system modeled in MATLAB/Simulink. Simulation results show that the proposed controller acts as an energy management system while, at the same time, mitigating power fluctuations.

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A microgrid can be defined as a grid of interconnected distributed energy resources, loads and energy storage systems. In microgrid systems containing renewable energy resources, the coordinated operation of distributed generation units is important to ensure the stability of the microgrid. A microgrid needs a successful control scheme to achieve its design goals. Undesirable situations such as distorted voltage profile and frequency fluctuations are significantly reduced by installing the appropriate hardware such as energy storage systems, and control strategies. The multi-agent system is one of the approaches used to control microgrids. The application of multi-agent systems in electric power systems is becoming popular because of their inherent benefits such as autonomy, responsiveness, and social ability. This study provides an overview of the agent concept and multi-agent systems, as well as reviews of recent research studies on multi-agent systems’ application in microgrid control systems. In addition, a multi-agent-based controller and energy management system design is proposed for the DC microgrid in the study. The designed microgrid is composed of a photovoltaic system consisting of 30 series-connected PV modules, a wind turbine, a synchronous generator, a battery-based energy storage system, critical and non-critical DC loads, the grid and the control system. The microgrid is controlled by the designed multi-agent-based controller. The proposed multi-agent-based controller has a distributed generation agent, battery agent, load agent and grid agent. The roles of each agent and communication among the agents are designed properly and coordinated to achieve control goals, which basically are the DC bus voltage quality and system stability. The designed microgrid and proposed multi-agent-based controller are tested for two different scenarios, and the performance of the controller has been verified with MATLAB/Simulink simulations. The simulation results show that the proposed controller provides constant DC voltage for any operation condition. Additionally, the system stability is ensured with the proposed controller for variable renewable generation and variable load conditions.