Probability measure of adequacy assessment using a fuzzy approach

An approach based on fuzzy set theory is developed for defining the failure levels in assessing the adequacy of facilities during the stages of operational and long-term planning in a power system. After analyzing the stochastic uncertainties of load variation and generation nonavailability by the probability load flow algorithm, the ‘probability measure of fuzzy events’ is proposed to combine these uncertainties and the linguistic failure inexactness to evaluate the adequacy indices of both transfer capacity and spinning reserve. The impact of load uncertainty on the adequacy assessment is investigated in nine different cases, and the resulting adequacy indices of each case are summarized. The correlations of the demand characteristics in the relatively short term are also examined for an actual system. Results show that the proposed fuzzy adequacy indices provide more information and a better realization than the deterministic adequacy index. Furthermore, some potential risk to facilities can easily be detected by the fuzzy failure level, whereas the deterministic specified-value level will fail to do so. The proposed technique is implemented on the IEEE 25-bus system to demonstrate its feasibility.