Abstract
The growth in energy consumption and pollution has led to increase the utilization of clean energy resources and electric vehicles (EVs), making the issue of network uncertainty a crucial concern. A multi-energy system offers an optimal approach to enhance the reliability, flexibility, and efficiency of an energy dispatch system through utilizing diverse energy generation resources. In this study, a new design for an optimal load distribution system, considering cost factors and CO2 reduction, is discussed. The model includes different energy generation players, such as combined heat and power units (CHP), gas boilers, water pumps, heat storage units, hydrogen storage systems (HSS), photovoltaic arrays (PV), and wind turbines (WT), to create a broad model for analysis and examination. The model takes into account the random charging consumption of EVs and uncertainties in renewable energy generation enabling a comprehensive assessment and analysis over future energy price uncertainties. Using demand response (DR) program, electrical and thermal systems are modeled and employed, and the effects of the water pump and HSS are discussed. An improved version of particle swarm optimization (PSO) is also used to address the optimization problem. The obtained results validate the performance of the proposed approach by showcasing a synchronized charge/discharge mode for EVs, while simultaneously minimizing the total cost.