Generation planning with intermittent renewable energy sources using probabilistic methods

A Power system intends to serve the customers as economical as possible with an acceptable degree of reliability and quality. Deterministic methods used in past does not respond nor reflect the probabilistic or stochastic nature of system behavior like customer demands, intermittent nature of renewable energy sources or of component failures. Hence the probabilistic methods get importance while meeting the customer demands with economical investment and acceptable reliability of supply. The determination of system planning reserves is much more complex with the addition of renewable energy sources because of its intermittent nature. In the paper two types of probabilistic methods namely, analytical and Monte Carlo methods are analyzed and are validated with IEEE RTS. The probabilistic nature of the overall wind power of the utility system has been modeled by normal distribution function with standard deviation error for each time interval. The implemented Monte-Carlo simulation method has been applied for one of southern states having high penetration of wind power, to analyze the generation planning after 12^th plan (2012-13 to 2016-17).