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浙江大学学报(工学版)  2019, Vol. 53 Issue (8): 1572-1581    DOI: 10.3785/j.issn.1008-973X.2019.08.016
电气工程、机械工程     
耦合风电场参数化模型的天气预报模式对风资源的评估和验证
王强(),罗坤*(),吴春雷,樊建人
浙江大学 能源清洁利用国家重点实验室,浙江 杭州 310027
Wind resource assessment of weather research and forecasting model coupled with wind farm parameterization model
Qiang WANG(),Kun LUO*(),Chun-lei WU,Jian-ren FAN
State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310027, China
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摘要:

为了验证耦合风电场参数化模型的天气预报模式(WRF-WFP)对大规模风电场风资源特性评估的准确性,以我国河北省张北县百万千瓦风能基地为研究对象,分别采用耦合与未耦合风电场参数化模型的天气预报模式开展相关的模拟试验,利用在平坦及复杂地形场区的测风塔的观测数据对风速及其概率密度函数分布以及风向进行验证分析. 研究结果表明:耦合与未耦合风电场参数化模型的天气预报数值模式对风资源特性的评估均有较高的可靠性,且对平坦地形区域的模拟精确性优于山地地形区域;由于前者考虑了风电场的尾流效应,对风速预测的精确性比后者高约4.5%. 该数值模式可为风能丰富地区的风电场微观选址、大规模风电场的运行特性及其对大气边界层影响的评估提供可靠的技术支撑.

关键词: 大规模风电场风资源评估天气预报模式风电场参数化模型精确性    
Abstract:

To validate the accuracy of evaluating the wind resource characteristics on large-scale wind farms by the weather research and forecasting model coupled wind farm parameterization model (WRF-WFP), the numerical experiments were performed using coupled and uncoupled WFP models respectively, with a gigawatt-scale wind power base in Zhangbei County of Hebei Province as research objective. The wind speed and its probability density function distribution, and wind direction were validated by the observed data from two wind masts on flat and complex terrain regions. Results showed that the WRF models of coupled and uncoupled WFP model both had high accuracy for assessment of wind resources and the simulation accuracy for the flat region was better than that for the mountain region. However, the accuracy of the coupled model was 4.5% higher than that of the uncoupled model due to the consideration of wind farm wake effects. The proposed numerical model can provide reliable technical support for micro-siting of the wind farm with rich wind resources, and assessing the operational characteristics of large-scale wind farms and their atmospheric impacts.

Key words: large-scale wind farm    wind resource assessment    weather research and forecasting model    wind farm parameterization model    accuracy
收稿日期: 2019-04-09 出版日期: 2019-08-13
CLC:  TK 89  
通讯作者: 罗坤     E-mail: zjuqw@zju.edu.cn;zjulk@zju.edu.cn
作者简介: 王强(1988—),男,博士生,从事风能气象数值模拟研究. orcid.org/0000-0002-9782-6575. E-mail: zjuqw@zju.edu.cn
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引用本文:

王强,罗坤,吴春雷,樊建人. 耦合风电场参数化模型的天气预报模式对风资源的评估和验证[J]. 浙江大学学报(工学版), 2019, 53(8): 1572-1581.

Qiang WANG,Kun LUO,Chun-lei WU,Jian-ren FAN. Wind resource assessment of weather research and forecasting model coupled with wind farm parameterization model. Journal of ZheJiang University (Engineering Science), 2019, 53(8): 1572-1581.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2019.08.016        http://www.zjujournals.com/eng/CN/Y2019/V53/I8/1572

图 1  WRF-WFP模式的三层嵌套区域及其地形特征
图 2  WFP模型中风力机的推力系数、功率输出曲线
参数 数值
额定功率/MW 1.5
额定风速/(m·s?1) 10
切入、切出风速/(m·s?1) 3、25
风轮直径/m 89
轮毂高度/m 80
表 1  WFP模型中风力机的基本参数
图 3  各季度平坦地形和复杂地形下模拟风速与观测风速的时间序列
测点 季节 MBE/(m·s?1) RMSE/(m·s?1) RRMSE IA
WRF-NWFP WRF-WFP WRF-NWFP WRF-WFP WRF-NWFP WRF-WFP WRF-NWFP WRF-WFP
M1 SPR 2.25 2.11 2.96 2.78 0.14 0.12 0.843 0.876
SUM 2.44 2.19 2.98 2.66 0.24 0.19 0.661 0.707
AUT 2.39 2.12 2.94 2.63 0.19 0.15 0.770 0.816
WIN 1.66 1.55 2.14 1.99 0.13 0.11 0.857 0.885
M2 SPR 2.88 2.72 3.65 3.41 0.16 0.13 0.764 0.797
SUM 2.73 2.62 3.27 3.13 0.22 0.20 0.618 0.694
AUT 2.99 2.73 3.58 3.27 0.20 0.16 0.692 0.753
WIN 1.82 1.71 2.30 2.15 0.15 0.14 0.782 0.808
表 2  各季度平坦地形和复杂地形下模拟与观测风速的误差
图 4  各季度下WRF-NWFP和WRF-WFP的模拟与观测风速的概率密度分布
图 5  各季度下WRF-NWFP和WRF-WFP模拟与观测风向玫瑰图
测点 季节 MBE/(°) RMSE/(°) RRMSE IA
WRF-NWFP WRF-WFP WRF-NWFP WRF-WFP WRF-NWFP WRF-WFP WRF-NWFP WRF-WFP
M1 SPR 24.79 24.47 40.41 39.88 0.090 0.087 0.828 0.860
SUM 25.84 24.57 39.78 39.15 0.082 0.078 0.927 0.962
AUT 23.57 23.43 39.10 39.67 0.076 0.075 0.934 0.967
WIN 20.76 20.82 27.06 27.07 0.083 0.081 0.781 0.815
M2 SPR 26.14 26.44 40.90 42.18 0.083 0.086 0.816 0.844
SUM 29.83 29.58 42.32 43.34 0.077 0.078 0.915 0.948
AUT 24.85 23.18 39.49 36.43 0.084 0.074 0.933 0.970
WIN 29.62 29.01 35.55 34.55 0.086 0.081 0.729 0.765
表 3  各季度平坦地形和复杂地形下模拟与观测风向的误差
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