article · Discover Energy
Advanced energy management strategies are necessary for hybrid renewable micro-grids to balance weather fluctuations and variable electrical demand. A strategy designed using MATLAB/Simulink software coordinates energy flows across renewable energy sources, local loads, and the wider utility grid. The algorithm actively controls battery storage by managing charging and discharging rates in response to prevailing operating conditions. Simulation results indicate that the control method successfully directs power flow between the micro-grid and the utility network while enabling high-power battery charging. This higher power rate allows the storage unit to recharge more quickly than standard approaches. Crucially, the system maintains the battery state of charge within an acceptable operational range of 20 to 100 percent.
Integrating renewable energy into power networks requires automated systems that can adapt to changing weather and consumer demand. By coordinating energy transfers and preventing battery damage through strict state-of-charge limits, this type of control helps improve grid resilience, reduces carbon emissions, and maximises the practical use of renewable installations.
This control method is relevant to micro-grid operators, renewable energy integrators, and storage system engineers seeking to coordinate distributed generation. Judged strictly from the abstract, the work was executed within MATLAB/Simulink simulation software, placing it at an early, computer-modelled stage of development prior to physical hardware validation or live deployment.
AI-generated from the published abstract. Always read the original work before citing.
Abstract This paper introduces an energy management strategy for a hybrid renewable micro-grid system. The efficient operation of a hybrid renewable micro-grid system requires an advanced energy management strategy able to coordinate the complex interactions between different energy sources and loads. This strategy must consider some factors such as weather fluctuations and demand variations. Its significance lies in achieving the overarching objectives of these systems, including optimizing renewable energy utilization, reducing greenhouse gas emissions, promoting energy independence, and ensuring grid resilience. The intermittent nature of renewable sources necessitates a predictive approach that anticipates the energy availability and adjusts the system operation. The aim of this study was to develop an energy management system for a hybrid renewable micro-grid system to optimize the deployment of renewable energy resources and increase their integration in the power system. Therefore, the main objective of this work was to develop an energy management strategy that controls the flow of energy between the hybrid micro-grid system and the load connected directly as well as the load connected to the utility grid using MATLAB/Simulink software. The second objective was to control the charging and discharging of the battery. The results show that the developed algorithm was able to control the energy flow between the hybrid micro-grid system and the utility grid and also to ensure a proper relation between the charging /discharging rate of the battery based on their operating conditions. In this application, the battery was charged at higher power. It was seen that a higher charging power enables to fully recharge the battery in a shorter amount of time than usual. The results have shown that it is possible to maximize the charging time by using a greater power and this algorithm ensures the state of charge (SOC) of battery to remain in the admissible limits (between 20 and 100%).
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DOI: 10.1007/s43937-024-00025-9
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