Wind over complex terrain - Microscale modelling with two types of mesoscale winds at Nygardsfjell

被引:29
作者
Bilal, Muhammad [1 ]
Birkelund, Yngve [1 ]
Homola, Matthew [2 ]
Virk, Muhammad Shakeel [3 ]
机构
[1] Arctic Univ Norway, Oslo, Norway
[2] Nordkraft AS, Oslo, Norway
[3] Narvik Univ Coll, Oslo, Norway
关键词
Wind speed; Complex terrain; Meso-scale modelling; Micro-scale modelling; WRF; WRF MODEL; SENSITIVITY;
D O I
10.1016/j.renene.2016.07.042
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Nygardstjell, a complex terrain near Norwegian-Swedish border, is characterized by its significant wind resources. The feasibility of using mesoscale winds as input to microscale model is studied in this work. The main objective is to take into account the actual terrain effects on wind flow over complex terrain. First set of mesoscale winds are modelled with Weather Research and Forecasting (WRF) numerical tool whereas second set of mesoscale winds are taken from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) data system. WindSim, a computational fluid dynamics based numerical solver is used as microscale modelling tool. The results suggest that the performance of microscale model is largely dependent upon the quality of mesoscale winds as input. The proposed coupled models achieve improvements in wind speed modelling, especially during cold weather. WRF-WindSim coupling showed better results than MERRA-WindSim coupling in all three test cases, as root mean square error (RMSE) decreased by 70.9% for the February case, 61.5% for October and 14.4% for June case respectively. Raw mesoscale winds from the WRF model were also more correct than the mesoscale winds from MERRA data set when extracted directly at the wind turbine by decreasing the RMSE by 62.6% for the February case, 62.7% for October and 23.7% for June case respectively. The difference of RMSE values between the mesoscale winds directly at wind turbine versus the coupled meso-microscale model outputs are not conclusive enough to indicate any specific trend. (C) 2016 Published by Elsevier Ltd.
引用
收藏
页码:647 / 653
页数:7
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