Experimental Investigation of AI-Enhanced FPGA-Based Optimal Management and Control of an Isolated Microgrid

In this article, an artificial intelligence (AI)-enhanced field-programmable gate array (FPGA)-based smart energy management system (SEMS) is implemented for optimal autonomous microgrid economic operation. The main objective of this study is to increase the reliability of the isolated microgrid and minimize the operating cost. The proposed system is prototyped using an Altera Cyclone IV EP4CE6 FPGA development kit, which is an extremely flexible and reprogrammable logic device. The results were taken for four continuous hours to clarify the reliability of the model. The results show that the SEMS has achieved high performance, a reliable and affordable energy supply, and a quick response to unexpected changes in the loads or power produced. In addition, the use of optimization techniques to enhance the efficiency of the FPGA makes the microgrid more attractive as it increases its flexibility, controllability, and ability to efficiently manage energy while reducing the overall cost. It succeeds in minimizing operating costs by 26.43% compared to the experimental case that did not utilize optimization techniques.