Wind farm and pumped storage integrated in generation scheduling using PSO

Wind energy brings many positive benefits to the utility system, such as cost effective energy, long-term price stability, and some system capacity, but it also has different generation characteristics than conventional utility resources. Unlike conventional power generation sources, wind power generators supply intermittent power because of resource uncertainties. This paper presents a new approach to solve the generation scheduling (GS) problem, considering reserve requirement, load-generation balance and wind power generation constraints. The modeling of constraints is an important issue in power system scheduling. This GS problem is solved using new particle swarm optimization (PSO). This problem is applied to a test system which has pumped storage power plants to modify the uncertainties of wind power output and other parameters in power system. Numerical testing results show that near optimal schedules are obtained, and the method can provide a good balance between increasing profit and satisfying constraints.