1. 华北电力大学 新能源电力系统全国重点实验室,北京,102206
2. 华北电力大学 新能源学院,北京,102206
3. 中国石化集团新星石油有限责任公司,北京,100089
网络首发:2025-06-30,
纸质出版:2025
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王坤宁,李莉,李明朔,经秋霞,刘永前. 海上测风塔塔影效应观测及校正算法研究动力工程学报, 2025, 45(10): 1704-1713 https://doi.
org/10.19805/j.cnki.jcspe.2025.250305
王坤宁,李莉,李明朔,经秋霞,刘永前. 海上测风塔塔影效应观测及校正算法研究动力工程学报, 2025, 45(10): 1704-1713 https://doi. DOI: 10.19805/j.cnki.jcspe.2025.250305.
org/10.19805/j.cnki.jcspe.2025.250305 DOI:
提出了测风塔塔影效应观测方案
并在中国某海域设立测风塔
获得了为期一年的测风数据;分析了测风塔塔影效应对关键参数的影响规律
构造了塔影效应影响因子(
T
SIF
)来量化不同风向扇区塔影效应的影响程度;基于时间卷积网络(TCN)提取风速时序信息以及多头自注意力机制(MHSA)捕捉塔影区域的关键影响特征
建立了测风塔塔影效应校正算法。以设立的测风塔为例进行验证。结果表明:
T
SIF
可作为重要辅助特征
提高塔影效应校正精度;风速计的安装方位对风资源测量精度和塔影效应校正效果影响显著。所提出的校正算法适用于工程上绝大多数测风塔
它仅利用某一测风高度处的两套测风数据
实现安装单个风速计的任意高度处风速的塔影效应校正
显著提高了风资源评估精度。
An observation scheme for quantifying tower-shadow effects on offshore wind measurement masts was proposed
and a one-year wind dataset was acquired from a mast deployment in Chinese sea area. The influence pattern of the mast tower shadow on critical parameters was analyzed
and a tower-shadow influence factor (
T
SIF
) was introduced to characterize the severity of shadowing within each wind-direction sector. A mast tower shadow effect correction algorithm was then developed combining a temporal convolutional network (TCN) for extracting wind-speed time-series patterns with a multi-head self-attention mechanism (MHSA) for capturing key shadow-region features. Validation at the installed mast shows that the
T
SIF
serves as an essential auxiliary feature that significantly improves correction accuracy. The mounting azimuth
of anemometers strongly affects both wind-resource measurement precision and the efficacy of tower-shadow correction. The proposed algorithm is applicable to most masts used in engineering and requires only two anemometer data series at one measurement height to correct tower-shadow-induced errors at any single-anemometer height
thereby substantially enhancing the wind-resource assessment accuracy.
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