Fuel constrained short-term hydrothermal generation scheduling

Abstract

Due to gradually diminution of fossil fuel, the cost-effective utilization of available fuel for power generation has turn out to be a vital concern of electric power utilities. Thermal power plants have to operate within their fuel confines and contractual constraints. This work suggests social group entropy optimization (SGEO) technique to solve short-term generation scheduling of a power system consisting of fuel constrained thermal generating units, cascaded hydro power plants, solar PV plants, wind turbine generators and pumped storage hydro (PSH) plants with demand side management (DSM). Simulation results of the test system have been compared with those acquired by self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients (HPSO-TVAC), fast convergence evolutionary programming (FCEP) and differential evolution (DE). Numerical results show that fuel consumption can be adequately controlled for fulfilling constraints imposed by suppliers and total cost with fuel constraints is more than the cost without fuel constraints. It has been also observed from the comparison that the suggested SGEO has the ability to bestow with superior-quality solution.