Reliability modeling of different wave energy conversion technologies

Wave as a clean, renewable and sustainable resource is used to produce electricity through different wave energy conversion systems. So far, many devices have been introduced for extracting the wave power and converting it to the electric power. Among different wave energy conversion systems, Pelamis, Wave Dragon, Oyster, Sea wave Slot-coned Generator and Buoy are developed, and commercial scale of these wave converters with large capacity is constructed in the world. The variability of output power of wave generator is main challenge of these renewable resources that must be addressed to integrate the large-scale wave generators in the power system. The assembled elements and also the principle of electric power production of various wave generators are different. For this purpose, in the current research, reliability modeling of different wave energy conversion devices is performed. The suggested reliability model considers both the hazard of assembled elements of the wave converters and change of output power of them. Because of wide change in wave height and wave period, the output of wave generators changes widely. To achieve a several-state reliability model of these wave generators, number of power states in the reliability presentation of them should be decreases. In the current study, the XB index that considers distance among decreased and initial states in numerator and minimum distance of two clusters in denominator is considered to determine optimal number of clusters in reliability presentation of wave generators. Then, fuzzy k-means clustering methodology is utilized to determine probability of these reduced power states. The suggested reliability model of different wave energy converters is used for studying adequacy of electric network with the presence of these production units. Based on the numerical outcomes related to adequacy analysis of RBTS and IEEE-RTS as two reliability test systems, impact of different wave generators on reliability quantities of electric network is investigated.