Design and implementation of a microgrid energy management system
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The increasing popularity of Renewable Energy Sources has led to their widespread adoption in recent years. However, their high cost and intermittent nature pose challenges to their efficient and reliable use. Microgrids have emerged as a viable solution to address these challenges and improve energy management for maximum economic benefit and reliability. However, the intermittent nature of some Renewable Energy Sources such as solar and wind power can result in fluctuations in power supply, which can negatively impact the microgrid's stability and reliability. Due to the need for more efficient power management to derive maximum economic benefit and reliability, the development of energy management systems (EMS) for microgrids has become a critical area of research. This project presents the design, implementation, and testing of an EMS for a microgrid using a fuzzy inference system (FIS) to optimize the power flow and control the frequency of the microgrid. The system was developed using MATLAB/Simulink, and its performance was validated through simulations and real-world experiments on a microgrid testbed. The results showed that the developed EMS was able to optimize the power flow, stabilize the frequency, and improve the system's reliability and efficiency. Future work includes the implementation of remote monitoring and control, cybersecurity measures, and the migration of the FIS model to a microcontroller-based platform for real-time operation. The developed EMS has the potential to contribute to the development of more efficient, reliable, and sustainable microgrids for both off-grid and ongrid applications.