Optimal Scheduling of Hybrid Multi-Carrier System Feeding Electrical/Thermal Load Based on Particle Swarm Algorithm

Abstract

In this paper, the optimum coordination of an energy hub system, fed with multiple fuel options (natural gas, wood chips biomass, and electricity) to guarantee economically, environmentally friendly, and reliable operation of an energy hub, is presented. The objective is to lessen the total operating expenses and CO2 emissions of the hub system. Additionally, the effect of renewable energy sources as photovoltaics (PVs) and wind turbines (WTs) on energy hub performance is investigated. A comparison of various configurations of the hub system is done. The proper planning of the hub elements is determined by a multi-objective particle swarm optimization (PSO) algorithm to achieve the lowest level of the gross running cost and total system emissions, simultaneously. The outcomes show that the natural gas turbine (NGT) is superior to the biomass generating unit in lowering the gross operating expenses, while using the biomass wood chips plant is most effective in lessening the total CO2 emissions than the NGT plant. Furthermore, the combination of the natural gas turbine, biomass generator, photovoltaics, and wind turbines enhances the operation of the hub infrastructures by lessening both the gross operating cost and overall CO2 emission simultaneously.