Evaluation of forecasted wind speed at turbine hub height and wind ramps by five NWP models with observations from 262 wind farms over China

IF 2.3 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Meteorological Applications Pub Date : 2024-10-30 DOI:10.1002/met.70007
Chenxi Jin, Yang Yang, Chao Han, Ting Lei, Chen Li, Bing Lu
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Abstract

Accurate wind speed forecasts are essential for optimizing the efficiency of wind energy operations. Currently, there is limited research on nationwide assessment of predictive performance in multiple numerical weather prediction (NWP) models for wind speed at turbine hub height over China, especially concerning wind ramp events. Utilizing observed measurements from 262 wind farms, this study evaluated the performance of five NWP models in forecasting the mean state and spatiotemporal variations of wind speed as well as wind ramps. The results indicated that the European Center for Medium-Range Weather Forecast Integrated Forecasting System (ECMWF–IFS) performed the best in forecasting climatological wind speed with a temporal correlation coefficient (TCC) of 0.74 and root mean square error (RMSE) of 2.34 m s−1. Although not widely utilized in China, the model from Meteo-France (MF–ARPEGE) showed promising potential for wind energy forecasting with a TCC of 0.72 and RMSE of 2.45 m s−1. In terms of temporal variations of wind speed, all the models could reasonably predict the seasonal variations of wind speed, whereas only three NWP models were able to capture the characteristics of the observed diurnal variation. An error decomposition analysis further revealed that the primary source of predicted error for wind speed was the sequence error component (SEQU), indicating the model errors were mainly attributed from the temporal inconsistency between forecasts and observations. Furthermore, the occurrences of wind ramps were generally underestimated by NWP models, while this shortcoming can be partly overcome by improving the time resolution of NWP models.

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利用中国 262 个风电场的观测数据,评估五个 NWP 模型对风机轮毂高度和风斜率风速的预报
准确的风速预报对于优化风能运行效率至关重要。目前,在全国范围内评估多种数值天气预报(NWP)模式对中国风机轮毂高度风速的预测性能,特别是有关风斜坡事件的预测性能的研究十分有限。本研究利用 262 个风电场的观测数据,评估了五种 NWP 模式在预报风速平均状态和时空变化以及风斜率方面的性能。结果表明,欧洲中期天气预报中心综合预报系统(ECMWF-IFS)在气候风速预报方面表现最佳,其时间相关系数(TCC)为 0.74,均方根误差(RMSE)为 2.34 m s-1。法国气象局的模型(MF-ARPEGE)虽然在中国没有得到广泛应用,但在风能预报方面表现出了良好的潜力,其时间相关系数(TCC)为 0.72,均方根误差(RMSE)为 2.45 m s-1。在风速的时间变化方面,所有模式都能合理预测风速的季节变化,而只有三个 NWP 模式能够捕捉到观测到的昼夜变化特征。误差分解分析进一步显示,风速预测误差的主要来源是序列误差分量(SEQU),表明模式误差主要来自预报与观测的时间不一致。此外,NWP 模式普遍低估了风速陡坡的出现,而这一缺陷可通过提高 NWP 模式的时间分辨率得到部分克服。
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来源期刊
Meteorological Applications
Meteorological Applications 地学-气象与大气科学
CiteScore
5.70
自引率
3.70%
发文量
62
审稿时长
>12 weeks
期刊介绍: The aim of Meteorological Applications is to serve the needs of applied meteorologists, forecasters and users of meteorological services by publishing papers on all aspects of meteorological science, including: applications of meteorological, climatological, analytical and forecasting data, and their socio-economic benefits; forecasting, warning and service delivery techniques and methods; weather hazards, their analysis and prediction; performance, verification and value of numerical models and forecasting services; practical applications of ocean and climate models; education and training.
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