风电机组效能和性能统一评估模型研究

doi:10.3901/JME.2021.14.253

摘要/Abstract

摘要： 风速和风向的不稳定、不确定性变化，使得风电机组难以保持稳定的风能转换状态，也直接导致了机组发电状态的不确定性。准确评估机组吸能与产能两种状态，对于制定生产、调度策略以及维护维修决策有着非常重要的意义。通过分析机组能量的转换过程，指出风电机组具有显性与隐性两种存在状态，并进一步研究风电机组效能和性能两种功能状态特性。采用云模型描述机组监测数据，应用云特征参数定量描述机组隐性状态的期望特性、偏离特性和离散特性，建立机组自有的、蕴藏在SCADA （Supervisory control and data acquisition，SCADA）数据中的、汇集机组效能与性能综合表现的隐性状态的评价模型。实现对机组不同风速、不同功率参数段局部评价和整个生产参数段整体综合评价，评估结果能为生产调度和维护维修决策提供依据，促进风电场科学、优化管理。最后，采用风电场现场监测数据验证算法的正确性和可靠性。

关键词: 风电机组, 隐性状态, 效能云, 性能云, 量化评估

Abstract: The unstable and uncertain changes of wind speed and direction make it difficult for wind turbines(WTs) to maintain a stable wind energy transition state, which directly leads to the uncertainty of power generation state of WTs. Accurately assessing the two states of energy absorption and production capacity of the wind turbines is of great significance for the formulating production, scheduling strategies and maintenance decisions. By analyzing the energy conversion process of the wind turbines, it is pointed out that the wind turbine has two existing states:explicit and implicit, and further study the two functional state characteristics of efficiency and performance of wind turbine. The cloud model is used to describe the wind turbine monitoring data, and the cloud characteristic parameters are used to quantitatively describe the expected characteristics, deviated characteristics and discrete characteristics of the unit's implicit state. The evaluation model of implicit state for wind turbines, which is embodied in Supervisory control and data acquisition(SCADA) data and brings together wind turbine's efficiency and performance, is established. The partial evaluation of the different wind speeds sections and different power parameter sections of the unit and the overall comprehensive evaluation of the entire production parameter sections are realized. The evaluation results can provide basis for production scheduling and maintenance decisions, and promote wind farm science and optimization management. Finally, the wind farm field monitoring data is used to verify the correctness and reliability of the algorithm.

Key words: wind turbines, implicit state, efficiency cloud, performance cloud, quantitative assessment

中图分类号:

TM614

董兴辉, 李佳, 高迪, 郑凯. 风电机组效能和性能统一评估模型研究[J]. 机械工程学报, 2021, 57(14): 253-260.

DONG Xinghui, LI Jia, GAO Di, ZHENG Kai. Research on Unified Assessment Model of Wind Turbine Efficiency and Performance[J]. Journal of Mechanical Engineering, 2021, 57(14): 253-260.

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