Multi-Objective Generation Scheduling of Hydro-Thermal System Incorporating Energy Storage With Demand Side Management Considering Renewable Energy Uncertainties

Atmospheric pollutants, mainly produced by thermal power plants compel to utilize green energy sources such as renewable energy sources and hydroelectric plants in a power system. But due to blinking behavior of sources of renewable energy and due to very high rate of outages, it has a detrimental consequence on overall grid. Demand side management (DSM) programs decrease cost and improve power system security. This study proposes non-dominated sorting genetic algorithm-II (NSGA-II) to solve multi-objective scheduling of generation for fixed head hydro-thermal system integrating pumped hydro energy storage and sources of renewable energy taking into consideration the outage and uncertainty in presence of DSM. Numerical results of the test system attained using the proposed technique were compared with strength pareto evolutionary algorithm 2 (SPEA 2).