Abstract
A probabilistic power-flow analysis method for power systems with tidal power sources is presented in this paper. The regularity of tidal power is modeled using a k -means clustering technique and the randomness of tidal power is modeled by using a nonparametric kernel density estimation method. A stochastic sampling method is also developed to generate random samples of tidal power time series for Monte Carlo based probabilistic power-flow analysis. The influence of tidal current generation on power flows is then evaluated and quantified considering both the regularity and randomness of tidal power. The measured tidal current speed data of two different locations in Florida and Alaska states, USA, and the IEEE 57-bus standard test system are used to verify the correctness and effectiveness of the presented probabilistic power-flow analysis method.
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