Risk assessment of stochastic spinning reserve of a wind‐integrated multi‐state generating system based on a cross‐entropy method

Challenges of unprecedented proportions face the electric power industry who takes on the responsibility for scheduling spinning reserve of a wind‐integrated power system in an economical and reliable way. This study proposed a cross‐entropy (CE) based simulation method to evaluate two indices of loss of load probability and expected demand not supplied, as well as the empirical distribution of demand not supplied. The triple together could be used for predictively sketching a full picture of spinning reserve inadequacy risk of a wind‐integrated power system at an imminent operating time instance. The stochastic feature of the concerned multi‐state system is modelled with a discrete‐state continuous‐time Markov process. Case studies based on the RTS‐79 were carried out to illustrate the spinning reserve adequacy fluctuation given different present states of a rapid‐start unit combined with or without considering the wind power penetration. Meanwhile, the advantage of the proposed CE simulation method over the exact convolution method and classical Monte Carlo simulation method in case of adequate spinning reserve is also demonstrated.