Stochastic planning and scheduling of energy storage systems for congestion management in electric power systems including renewable energy resources

This paper presents an optimal planning and scheduling on energy storage systems (ESSs) for congestion management in electric power systems including renewable energy resources. The proposed problem finds optimal capacity and charging-discharging regime of ESSs. The storage units are optimally charged and discharged to tackle the uncertainty related to wind-solar units as well as relief congestion in the lines. Output power of solar and wind units is modeled by Gaussian probability distribution function (PDF) and Monte-Carlo simulation (MCS) is applied to tackle the uncertainty. Simulation results demonstrate that the proposed planning can manage congestion of the network efficiently while dealing with wind and solar resources uncertainties.