Reliability modeling of wave energy converters based on pelamis technology

Wave generators, as renewable sources, are increasingly applied for power generation in developed electric networks. With the development of wave generator technologies, large-scale devices such as oscillating water columns, pelamis, wave-dragon, oyster, buoy, sea wave slot cone converter, and tapchan have been invented to extract electrical power from wave energies. The output of wave generators relies on the height and period of waves, and because of the wide variation in these quantities, the produced power from them changes widely. Therefore, in electric networks incorporating large wave generators, reliability is influenced and should be analyzed. In this paper, for the first time, the reliability modeling of pelamis, as a kind of commercial-scale wave generator, is executed. In the proposed multi-state reliability model of pelamis, failures of composed components and changes in the production of power are addressed. To obtain the optimal number of power states in the model, the XB factor is computed. Then, to reduce the number of power states in the model, the fuzzy c-means clustering methodology is applied. The obtained model is used to examine the adequacy assessment of an electric network containing a pelamis farm. Numerical results show that wave converters can improve the reliability performance of electric systems. However, wave period and height affect the reliability indices of the power system. The effectiveness of the proposed method is validated by comparing the outcomes obtained by the analytical and Sequential Monte Carlo Simulation methods.

Automated summary

This paper focuses on the reliability modeling of pelamis, a commercial-scale wave generator. A multi-state reliability model is proposed to address failures of components and changes in power production. The fuzzy c-means clustering methodology is applied to reduce the number of power states in the model. Numerical results demonstrate that wave converters can improve the reliability performance of electric systems, but wave period and height have an impact on the reliability indices of the power system. The effectiveness of the proposed method is validated by comparing with the outcomes obtained by analytical and Sequential Monte Carlo Simulation methods.