基于数据插值算法的潮流能发电装置发电性能分析优化方法研究
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1.国家海洋技术中心天津300112; 2.自然资源部舟山潮流能野外科学观测研究站天津300112

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TH17TM761

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国家自然科学基金(42542064)、自然资源部舟山潮流能野外科学观测研究站基金(ZSTE-2024DA05)、自然资源部海洋可再生能源产业发展(N3250NY10)项目资助


Research on optimization analysis method of power performance assessment for tidal energy converters based on data interpolation algorithms
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1.National Ocean Technology Center, Tianjin 300112, China; 2.Observation and Research Station of Zhoushan Tidal Energy, Ministry of Natural Resources, Tianjin 300112, China

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    摘要:

    潮流能发电装置发电性能的分析与评价工作对于促进潮流能发电技术的迭代升级至关重要。然而,对潮流能发电装置现场测试数据集分析时发现,数据集中的潮流流速数据和输出电功率数据并不都是相互匹配的,这不利于对潮流能发电装置的发电性能开展精细化分析与研究。鉴于此,在以往现场测试数据的基础上,采用萨维茨基-戈莱(SG)滤波算法、数据插值算法、对比分析、数理统计等方法,针对潮流能发电装置的输出功率、整机转换效率、年发电量、容量系数、年等效满发小时数等指标,开展潮流能发电装置发电性能分析优化方法研究。研究结果表明:SG滤波方法对潮流流速数据的波动性具有较好的滤除效果,尤其是对处于显著震荡区间内的潮流流速数据的波动性滤除效果良好;插值后的潮流能发电装置输出功率散点图所表征的切入流速为0.5 m/s,切入流速指标相对于插值前降低了约7.4%;插值后的数据集中的最大输出功率为542.9 kW,相对于插值前的最大输出功率提高了约0.6%;插值后的数据集中的整机转换效率最大值约为43.4%,相对于插值前的整机转换效率的最大值42.6%,提高了约1.9%;插值后的数据集与插值前的数据集中的潮流能发电装置年发电量、容量系数、年等效满发小时数指标分别相差700.8 kWh、0.000 2和1.6 h。研究成果期望为潮流能发电装置功率特性的精细化分析工作提供参考。

    Abstract:

    The analysis and evaluation of the power performance of tidal energy converters are crucial for promoting the iterative upgrading of tidal current energy generation technology. However, analysis of field testing datasets of tidal energy converters shows that the tidal current velocity data and output electric power data do not always have a one-to-one correspondence, which is not conducive to refined analysis of the power generation performance of tidal energy converters. In view of this, based on previous field test data, methods such as the Savitzky-Golay (SG) filtering algorithm, data interpolation algorithm, comparative analysis, and mathematical statistics were adopted to conduct research on the analysis methods of the power performance of tidal energy converters, focusing on indicators such as the output power, overall conversion efficiency, annual power generation, capacity factor, and annual equivalent full-load hours of the devices. The research results show that the SG filtering method has a good effect on filtering out the fluctuations of tidal current velocity data, especially for the tidal current velocity data in significantly oscillating intervals. The cut-in velocity characterized by the scatter plot of the output power of the tidal energy converter after interpolation is 0.5 m/s, and the cut-in velocity index is decreased by 7.4% compared with that before interpolation. The maximum output power in the dataset after interpolation is 542.9 kW, which is 0.6% higher than the maximum output power before interpolation. The maximum overall conversion efficiency in the interpolated dataset is approximately 43.4%, which is 1.9% higher than the maximum overall conversion efficiency of 42.6% before interpolation. The differences in the annual power generation, capacity factor, and annual equivalent full-load hours of the tidal energy converter between the datasets before and after interpolation are 700.8 kWh, 0.000 2, and 1.6 h, respectively. These findings provide a valuable reference for the refined performance analysis of tidal energy converters.

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夏海南,贾宁,郭毅,石建军,刘松堂.基于数据插值算法的潮流能发电装置发电性能分析优化方法研究[J].仪器仪表学报,2025,46(10):179-188

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