{'fraction_non_alphanumeric': 0.01423728813559322, 'fraction_numerical': 0.0, 'mean_word_length': 5.678733031674208, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Reliability Evaluation of Tidal Current Farm Integrated Generation Systems Considering Wake Effects

Based on a sequential Monte–Carlo simulation technique, a reliability evaluation method and several indices are proposed for tidal current farm integrated generation systems in this paper. A tidal current velocity model is first developed to capture the chronology and randomness of tidal current velocity by combining a fuzzy equivalent matrix-based clustering approach with a nonparametric probabilistic modeling technique. The single and multiple wake effects between tidal current turbines in a tidal current farm are quantitatively represented using an analytical wake model. Second, a power output model for a tidal current farm (TCF) is proposed, incorporating the characteristics of tidal current velocity, wake effects and turbine failures. A sequential Monte–Carlo simulation-based reliability evaluation method, as well as several reliability evaluation indices are proposed to quantify the impacts of TCF integration and wake effects on the reliability level of generation systems. The historical tidal current velocity data collected from a site located in FL, USA, and the popular reliability test system known as RBTS with an additional TCF were used to verify the accuracy and effectiveness of the proposed method. The impacts of tidal power integration and the relative distances between turbines in TCF on generation systems’ reliability were also studied.