Sustainable Green Energy Management: Optimizing Scheduling of Multi-Energy Systems Considered Energy Cost and Emission Using Attractive Repulsive Shuffled Frog-Leaping

As energy systems become increasingly complex, there is a growing need for sustainable and efficient management strategies that reduce greenhouse gas emissions. In this paper, multi-energy (MES) have emerged as promising solution integrates various sources enables sharing between different sectors. The proposed model based on using an Attractive Repulsive Shuffled Frog-Leaping (ARSFL) algorithm optimizes the scheduling of resources, taking into account constraints such capacity limitations environmental regulations. considers sources, including renewable power-to-gas (P2G) network with power grid, incorporates demand–response mechanism allows consumers to adjust their consumption patterns in response price signals other incentives. ARSFL demonstrates superior performance managing minimizing purchase uncertainty compared particle swarm optimization (PSO) genetic (GA). It also exhibits significantly reduced execution time, saving approximately 1.59% PSO 2.7% GA.