Scenario-Based Fuel Constrained Short-Term Hydrothermal Scheduling

For electric power companies, the economic utilization of existing fossil fuel is currently a primary issue because of the diminishing supply of fossil fuel. Thermal power plants have fuel limitations and contractual restrictions that must be adhered to. As a result, the scenario-based fuel-constrained short-term hydrothermal scheduling problem with renewable energy sources is presented in this paper. The elephant clan optimization (ECO) approach is offered for short-term hydro-thermal scheduling (STHTS) with thermal generators, cascaded hydro, solar PV plants, wind turbine generators (WTG), and pumped storage hydro (PSH) with and without demand side management (DSM) for various scenarios. On a typical test system, the suggested approach is shown to be successful. An analysis of the typical test system's numerical results is compared to those produced via the self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients (HPSO-TVAC) and grey wolf algorithms (GWO). The comparison shows that the suggested ECO is capable of providing a better solution.