An improved mayfly optimization with modified perturb and observe based energy management in grid integrated renewable sources

Recent developments show that renewable energies would permanently, safely, and increasingly supply the world's energy needs. Even still, there are some differences in their findings due to climate change, which is a significant problem. To overcome this issue, the Energy Management System (EMS) is introduced to satisfy the demands needs and increase the efficiency of renewable energy to ensure the effectiveness in an optimal way. We implemented a new method of improved Mayfly Optimization based Modified Perturb and Observe (IMO-MP&O) to enhance battery use, ensure energy flow stabilization, and meet the energy needs of connected loads. The IMO-MP&O concept satisfies energy requirements, giving priority to important applications and adapting to fluctuating demands. The main innovation of IMO-MP&O is its adaptive optimization technique, which builds on the advantages of MO to improve the traditional MP&O algorithm. The suggested IMO-MP&O EMS prioritizes key loads, stabilizes energy flow, maximizes battery utilization, and adjusts to changing demands. The overall simulation outcomes display that suggested IMO-MP&O outperforms other algorithms by injecting 5.386 kWh of energy into the grid, representing an enhancement in grid independence. The grid injection of 5.386 kWh is emphasized as a marker of improved grid independence through efficient utilization of surplus renewable generation after satisfying a fixed 35 kWh load. Further, in terms of computation time, the suggested IMO-MP&O attains a better value of 392.15 s than the Grey Wolf-Cuckoo Search Optimization.