Grid-Connected Microgrids' Day-Ahead Energy Scheduling for Demand-Side Management using Improved Moth-Flame Algorithm-IMFO

Demand Side Management (DSM) is a useful technique for utilities since it controls system energy use and lowers peak load demand. The day-ahead energy scheduling for demand-side control in grid-connected microgrids using the Improved Moth-Flame Algorithm (IMFO) was proposed in this paper. Customers who participate in this process earn from the deployment of DSM, and utilities also benefit. Using various devices, this research proposes a load-shifting strategy-based DSM that minimizes the system's energy consumption pattern. Gaussian and chaos mutation are then used to enhance the moth-flame method, which has a tendency to slip into local optima. This suggests that the enhanced moth-flame algorithm is very effective and reliable for scheduling microgrid cluster optimization. Based on the enhanced moth-flame method, a scheduling model for microgrid cluster optimization is built. The experimental findings revealed that, following 160 iterations, the operational cost was 4286.21 yuan in islanding mode. After scheduling was optimized, the operational cost decreased by 8.7% to 3912.3 yuan. The enhanced moth-flame algorithm outperformed existing intelligent algorithms after 10–50 iterations; a consistent normal loss of 20% and 97.19% operating efficiency were attained. This suggests that the enhanced moth-flame algorithm operates with microgrids for Demand Side Management with great efficacy and dependability.