Quantitative risk associated with intermittent wind generation

Abstract

Wind energy is a propitious alternative to fossil-fuel generation due to its benign environmental footprint and sustainability. However, the intermittent nature of wind turbine output may scale up the risk of not meeting current or future load demand. A quantitative risk measure associated with introducing wind turbines into the generation eet is investigated in this paper. Due to the randomness of the wind speed profile, a common wind speed model employing a multistate wind generation pattern, representing various production levels, was adopted, as opposed to conventional generator models, which are suitably represented with a two-state model. Using a hybrid method that combines the analytical technique with Monte Carlo simulation, risk measures such as loss of load probability were evaluated and applied to the RBTS and IEEE-RTS test systems. The expected demand not supplied, due to contemplated uncertainties, was further quantified. Test results show that the capacity credit of wind turbine generators could vary widely depending on system size and configuration. Furthermore, the use of an 11-state wind representation model along with the normal distribution of wind speed produces very close results compared with the Weibull distribution of wind speed.