AI-Enhanced Energy Management Systems for Efficient Flow Control in Microgrids

This paper has presented a new approach for investigating the potential to rationally use promising sustainable energy sources with highly developed energy management systems integrated into IoT and AI technologies. The empirical analysis was done through a Genetic Algorithm model in Python taken on a typical microgrid system that supplied power to 100 homes at an average of 47 kW. The simulation results show an enormous reduction of waste power in the order of 93%, but at a costlier overall in the microgrid, up by approximately 25%. These results act as strong proof that this integrated approach is technically feasible and economically feasible for the pursuit of efficiency and savings. This study goes further to consider the economic implications of the implementation and maintenance of EMS. It also considers cybersecurity as one of the critical challenges in interconnected microgrids that might influence operational integrity. The research further contributes significantly to knowledge on battery consumption loss and the factors that have to be addressed to avoid negative impacts on the overall system. This research considers a microgrid as a key building block in a flexible and resilient energy infrastructure; its approach covers more than just technical discussions but fosters a broader, transdisciplinary dialogue. In the future, smart EMS integrated with IoT and AI is foreseen to be necessary to enable microgrids to maintain a sustainable and reliable power supply in communities. In short, this article gives fresh guidelines for the development of energy systems that are bound to be not only more efficient but also stable enough to resist any challenge that may come from environmental dynamics. Finally, the article calls upon all researchers, policymakers, and other stakeholders to contribute their quota in shaping the future of energy systems of the 21st century in a way that can help make the energy landscape more sustainable and resilient.