Abstract

Tidal current can be used as a source of renewable and clean energy. Deterministic modeling of tidal current speed in power generation systems is commonly used for evaluating the tidal current energy. Due to lack of long-term tidal current measurement, regeneration of a long-period time series of tidal current speeds is of high importance. In this study, both deterministic and statistical models were applied to estimate energy potential at tidal current observation stations in the Khuran Strait in the Persian Gulf. The long-term current speed data were generated by harmonic analysis and probabilistic modeling. To evaluate the efficiencies of the statistical models and predict the tidal current speeds, a set of measurements were performed in the 12 stations. The conducted analysis showed that the Wakeby distribution was the best probability distribution function capable of successfully passing the statistical tests. Kolmogorov–Smirnov (K–S) and root-mean-square error were used to perform a priori and a posteriori statistical tests in two steps. Harmonic analysis and prediction methodology were applied to generate the long-term data to be used in a posteriori test and energy potential energy estimations. In addition, the predicted tidal current speeds derived from the mentioned distribution function were used for energy estimations of tidal current at the Khuran Strait in the Persian Gulf. The mean power density over a year was calculated using the cubed velocity formula with the Betz limit coefficient and current speed distribution frequencies in the tidal current stations. The results indicated that the density power of tidal currents at Laft station was stronger compared to other locations. Moreover, the estimated values for potential energy of tidal currents in both methods were close together (r2 = 0.998) with high precision.

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