Estimating capacity credit of wind energy sources using probabilistic methods

Power systems with high wind penetration undergo increased variability and uncertainty, this leads to significant research in finding the wind power capacity credit on generation adequacy. The deterministic methods used in the past does not reflect the stochastic or probabilistic nature of system behavior with regard to customer demands, component failures and intermittent nature of renewable energy sources in particular wind energy sources. It is observed that large scale integration of wind energy has an impact on power system planning and operation. The large scale wind integration calls for generation planning which is an important aspect in order to meet the customer demands with optimum mix of generation like thermal, hydro and renewable. In this paper, probabilistic method namely sequential Monte-Carlo simulation has been implemented and is validated with IEEE RTS for generation adequacy analysis. The wind model has been incorporated in Monte-Carlo simulation approach in order to find the impact of the intermittent energy sources on generation planning in terms of wind power capacity credit. In the present paper, one of the high wind penetration states in INDIA has been considered for case studies. The capacity credit of wind power has been estimated with the planned generation for next five years considering the reliability index as per GRIDCODE.