Impacts of different wind speed simulation methods on conditional reliability indices

As wind power penetration becomes increasingly significant, the impact of the intermittent and stochastic wind energy on power systems reliability urgently needs to be assessed. This paper examines the impacts of different wind speed simulation methods on the adequacy evaluation by the conditional reliability indices. First, the seasonal property, diurnal distributions, and autocorrelation of wind speeds at a particular site are investigated with the practical observed wind speed data, and several typical wind speed simulation methods are discussed. Then, after analyzing the drawbacks of the traditional unconditional expected-value-based reliability indices, a series of conditional reliability indices are proposed, making it possible to incorporate risk preference into the reliability assessment. Furthermore, an adequacy evaluation process based on sequential Monte Carlo approach is established. Finally, three wind power integration scenarios are designed in the modified IEEE-RTS, and the impacts of different wind speed simulation methods on the conditional reliability indices in the three scenarios are thoroughly compared. Numerical results have shown that time series methods agree well with the observed wind speed method in the conditional reliability indices; the conditional reliability indices in the probability sampling method present the property of high frequency and short duration, especially in the high damage domain; the mean observed wind speed method leads to relatively optimistic results, with higher conditional probability of the healthy state and lower conditional probabilities of the marginal and at-risk states; and the healthy state in this method is of lower occurrence frequency and longer duration.