Optimizing Microgrid Performance: A Data-Driven Approach with IoT Integration - K. Oubida, Raafat (International Journal of Intelligent Systems and Applications in Engineering, 2024)
The essential goal of this exploration is to work on the efficiency of microgrids by using a data-driven system that is expanded by the joining of Internet of Things (IoT) technology integration. Microgrids, which are decentralized energy systems, are a fundamental part during the time spent upgrading energy resilience, bringing down fossil fuel byproducts, and further developing admittance to power. By and by, there are serious issues associated with expanding the efficiency and reliability of microgrid tasks. These difficulties are brought about by the multifaceted cooperations that happen between the a large number and the dynamic outer impacts. Inside the extent of this examination, we offer a remarkable system that utilizes data-driven procedures to evaluate, reproduce, and improve the performance of microgrids. We plan predictive models to conjecture energy utilization, further develop energy generation and conveyance, and lift system constancy by using real-time data gathered from Internet of Things (IoT)- empowered sensors and devices implanted inside the design of the microgrid. The consolidation of Internet of Things technology makes it conceivable to consistently screen and work the resources of a microgrid, which thus pursues it more straightforward to settle on proactive decisions and execute adaptive management strategies. Through the use of case studies and simulated tests, we illustrate the efficacy of our method in terms of promoting energy sustainability, lowering operational costs, and improving the performance of microgrids. The findings of this study provide a significant contribution to the development of intelligent energy systems and lay the groundwork for future advances in the optimization and administration of microgrid electricity networks.