Multilevel Energy Scheduling in Smart Multiple Energy Grid Considering Optimal Participation of the Consumers in Energy Consumption

Efficient energy use is a key aspect of sustainable development in numerous nations, aimed at enhancing economic, technical, and environmental metrics within the energy sector. This study presents an energy scheduling approach within a smart multienergy grid with promoting optimal energy usage by consumers. The energy scheduling is represented through a multiobjective optimization strategy with three levels, taking into account demand side management (DSM) approaches. The DSM approaches encompass shifting power demand and generating local energy from gas and power storage devices. The shifting power demand is modeled to decrease consumers’ bills at the first level. Also, generating local energy by storage devices is done to decrease consumers’ bills at the second level. The maximizing flexibility index, minimizing power losses, and operational costs are modeled as multiobjective functions in optimization of the third level. In the optimization process, the third level utilizes DSM approaches to optimize energy demand for multiobjective functions. The grasshopper optimization algorithm (GOA) along with fuzzy‐based weight sum methods is employed to tackle the optimization approach. The fuzzy‐based weight sum methods are introduced to identify the optimal solution in the Pareto front solutions for multiobjective functions. The proposed energy scheduling is executed on a 69‐node test grid. Finally, the results demonstrate the optimum rate of the objectives and emphasize consumer participation via a comparative assessment of different case studies. With the implementation of the DSM approaches, the flexibility index is improved by 4.3%, and power losses and operational cost are minimized by 19.21% and 13.51%, respectively.