Study on Obtaining Real Power Curve of Wind Turbines Using SCADA Data
Study on Obtaining Real Power Curve of Wind Turbines Using SCADA Data
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DOI：
10.3389/fenrg.2022.916355
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发表时间：
2022-07
期刊：
影响因子：
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通讯作者：
J. Dai;Huifan Zeng;Fan Zhang;Huang Chen;Mimi Li
中科院分区：
文献类型：
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作者：
J. Dai;Huifan Zeng;Fan Zhang;Huang Chen;Mimi Li
准确获取风力涡轮机的性能参数是风力涡轮机运行和维护过程中需要解决的关键问题。功率曲线是评价风力发电机组性能的重要指标。如何对风力发电机组进行建模并获取其功率曲线一直是研究的热点之一。提出了一种获取风电机组实际功率曲线的新方法。首先，设计了基本的数据预处理算法，对原始数据中的零值和空值进行处理。采用滑动平均滤波法对风速进行处理，目的是考虑一定时期内风对风力涡轮机功率的综合影响。根据理想风力涡轮机的动量理论，结合风速计安装位置的特点，对实测风速与实际风速之间的偏差进行近似修正。在这里，还考虑了空气密度动态变化的影响。然后，采用高斯拟合算法对风功率曲线进行拟合。对比分析了风速修正前后功率曲线的特点。同时，考虑和研究了参数不确定性对功率曲线可靠性的影响。最后，对四种风力机的功率曲线特性进行了比较分析。研究结果表明，在这些功率曲线中，WT3和WT4最接近，WT2次之，WT1偏离最远。研究工作为风电机组的现场性能评估、检修和维护提供了有价值的依据。
The key problem to be solved in the process of wind turbine (WT) operation and maintenance is to obtain the wind turbine performance accurately. The power curve is an important indicator to evaluate the performance of wind turbines. How to model and obtain the power curve of wind turbines has always been one of the hot topics in research. This paper proposes a novel idea to get the actual power curve of wind turbines. Firstly, the basic data preprocessing algorithm is designed to process the zero value and null value in the original supervisory control and data acquisition (SCADA) data. The moving average filtering (MAF) method is employed to deal with the wind speed, the purpose of which is to consider the comprehensive result of wind on the wind turbine power in a certain period. According to the momentum theory of the ideal wind turbine and combined with the characteristics of the anemometer installation position, the deviation between the measured wind speed and the actual wind speed is approximately corrected. Here, the influence of dynamic changes in air density is also considered. Then, the Gaussian fitting algorithm is used to fit the wind-power curve. The characteristics of the power curve before and after wind speed correction are compared and analyzed. At the same time, the influence of the parameter uncertainty on the reliability of the power curve is considered and investigated. Finally, the characteristics of the power curves of four wind turbines are compared and analyzed. The research results show that among these power curves, WT3 and WT4 are the closest, WT2 is the next, and WT1 has the farthest deviation from the others. The research work provides a valuable basis for on-site performance evaluation, overhaul, and maintenance of wind turbines.