Assessing the Reliability and Optimizing Input Parameters of the NWP-CFD Downscaling Method for Generating Onshore Wind Energy Resource Maps of South Korea

Jeonghyeon Kim, Hyungoo Moon, Jin-Yong Kim, Keon Hoon Kim, Hyun-Goo Kim () and Sung Goon Park ()
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Jeonghyeon Kim: Mechanical & Automotive Engineering Department, Seoul National University of Science & Technology, Seoul 01811, Republic of Korea
Hyungoo Moon: Mechanical & Automotive Engineering Department, Seoul National University of Science & Technology, Seoul 01811, Republic of Korea
Jin-Yong Kim: Renewable Energy Big Data Laboratory, Korea Institute of Energy Research, Daejeon 34129, Republic of Korea
Keon Hoon Kim: Renewable Energy Big Data Laboratory, Korea Institute of Energy Research, Daejeon 34129, Republic of Korea
Hyun-Goo Kim: Korea Institute of Energy Research, Wind Energy Research Center, Daejeon 34129, Republic of Korea
Sung Goon Park: Mechanical & Automotive Engineering Department, Seoul National University of Science & Technology, Seoul 01811, Republic of Korea

Energies, 2024, vol. 17, issue 3, 1-19

Abstract: The numerical weather prediction (NWP) method is one of the popular wind resource forecasting methods, but it has the limitation that it does not consider the influence of local topography. The NWP-CFD downscaling considers topographic features and surface roughness by performing computational fluid dynamics (CFD) with the meteorological data obtained by the NWP method as a boundary condition. The NWP-CFD downscaling is expected to be suitable for wind resource forecasting in Korea, but it lacks a quantitative evaluation of its reliability. In this study, we compare the actual measured data, the NWP-based data, and the NWP-CFD-based data quantitatively and analyze the three main input parameters used for the calculation of NWP-CFD (minimum vertical grid size Δ z min , the difference angle Δ dir , and the forest model activation reference length l 0 ). Compared to the actual measurement data, the NWP-based data overestimate wind resources by more than 35%, while the NWP-CFD-based data show an error of about 8.5%. The Δ z min and Δ dir have little effect on the results, but the l 0 has a large effect on the simulation results, and it is necessary to adjust the values appropriately corresponding to the characteristics of an area.

Keywords: numerical weather prediction; computational fluid dynamics; NWP-CFD; reliability test (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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