Wind Resource Assessment Using a Mesoscale Model: The Effect of Horizontal Resolution

2012 ◽  
Author(s):  
S. Jafari ◽  
T. Sommer ◽  
N. Chokani ◽  
R. S. Abhari
Keyword(s):  
Wind Energy ◽  
Complex Terrain ◽  
Prediction Models ◽  
Weather Prediction ◽  
Energy Resource ◽  
Resource Assessment ◽  
Land Area ◽  
Wind Resource Assessment ◽  
Wind Resource ◽  
Horizontal Grid

Prospecting for wind farm sites and pre-development studies of wind energy projects require knowledge of the wind energy resource over large areas (that is, areas of the order of 10’000 km2 and greater). One approach to detail this wind resource is the use of mesoscale numerical weather prediction models. In this paper, the mesoscale Weather Research and Forecasting (WRF) model is used to examine the effect of horizontal grid resolution on the fidelity of the predictions of the wind resource. The simulations are made for three test cases, Switzerland (land area 39’770 km2), Iowa (land area 145,743 km2) and Oregon (land area 248’647 km2), representing a range of terrain types, from complex terrain to flat terrain, over the period from 2006–2010. On the basis of comparisons to the data from meteorological masts and tall communication towers, guidelines are given for the horizontal grid required in the use of mesoscale models of large area wind resource assessment, especially over complex terrain.

scholarly journals Lidar uncertainty and beam averaging correction

2015 ◽  
Vol 12 (1) ◽  
pp. 85-89 ◽  
Author(s):  
A. Giyanani ◽  
W. Bierbooms ◽  
G. van Bussel
Keyword(s):  
Remote Sensing ◽  
Wind Energy ◽  
Complex Terrain ◽  
New Technology ◽  
Resource Assessment ◽  
International Guideline ◽  
Wind Resource Assessment ◽  
Draft Version ◽  
Wind Resource ◽  
Atmospheric Variables

Abstract. Remote sensing of the atmospheric variables with the use of Lidar is a relatively new technology field for wind resource assessment in wind energy. A review of the draft version of an international guideline (CD IEC 61400-12-1 Ed.2) used for wind energy purposes is performed and some extra atmospheric variables are taken into account for proper representation of the site. A measurement campaign with two Leosphere vertical scanning WindCube Lidars and metmast measurements is used for comparison of the uncertainty in wind speed measurements using the CD IEC 61400-12-1 Ed.2. The comparison revealed higher but realistic uncertainties. A simple model for Lidar beam averaging correction is demonstrated for understanding deviation in the measurements. It can be further applied for beam averaging uncertainty calculations in flat and complex terrain.

scholarly journals Reliability of ERA5 Reanalysis Data for Wind Resource Assessment: A Comparison against Tall Towers

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4169
Author(s):  
Giovanni Gualtieri
Keyword(s):  
Wind Speed ◽  
Prediction Models ◽  
Weather Prediction ◽  
Resource Assessment ◽  
Reanalysis Data ◽  
Solar Irradiation ◽  
Wind Resource Assessment ◽  
Regional Reanalysis ◽  
Wind Resource ◽  
Wind Resources

The reliability of ERA5 reanalyses for directly predicting wind resources and energy production has been assessed against observations from six tall towers installed over very heterogeneous sites around the world. Scores were acceptable at the FINO3 (Germany) offshore platform for both wind speed (bias within 1%, r = 0.95−0.96) and capacity factor (CF, at worst biased by 6.70%) and at the flat and sea-level site of Cabauw (Netherlands) for both wind speed (bias within 7%, r = 0.93−0.94) and CF (bias within 6.82%). Conversely, due to the ERA5 limited resolution (~31 km), large under-predictions were found at the Boulder (US) and Ghoroghchi (Iran) mountain sites, and large over-predictions were found at the Wallaby Creek (Australia) forested site. Therefore, using ERA5 in place of higher-resolution regional reanalysis products or numerical weather prediction models should be avoided when addressing sites with high variation of topography and, in particular, land use. ERA5 scores at the Humansdorp (South Africa) coastal location were generally acceptable, at least for wind speed (bias of 14%, r = 0.84) if not for CF (biased by 20.84%). However, due to the inherent sea–land discontinuity resulting in large differences in both surface roughness and solar irradiation (and thus stability conditions), a particular caution should be paid when applying ERA5 over coastal locations.

scholarly journals Offshore Wind Energy Resource Assessment from Satellite Data Observations and WRF in Porto Santo Island

2020 ◽  
Author(s):  
Fabiola S. Pereira ◽  
Carlos S. Silva
Keyword(s):  
Wind Energy ◽  
Weibull Distribution ◽  
Energy Production ◽  
Energy Resource ◽  
Resource Assessment ◽  
Offshore Wind ◽  
Electricity Production ◽  
Offshore Wind Energy ◽  
Wind Resource Assessment ◽  
Wind Resource

Abstract. The vast majority of isolated electricity production systems such as Islands depends on fossil fuels. Porto Santo Island, a Portuguese UNESCO Biosphere Reserve candidate from Madeira Archipelago situated in the Atlantic Ocean, aims to become a sustainable territory in order to reduce its carbon footprint. A sustainable pathway goes through the integration of renewable energy in the electricity production system, in particular, the potential of offshore wind energy. The scope of this work has three main purposes: (1) the offshore wind resource assessment in Porto Santo Island, (2) the determination of a zone of interest regarding the combination of different parameters such us the bathymetry, distance to the coastline and integrated in the national situation plan of maritime space (3) the estimation of the annual energy production from the best-fitted Weibull Distribution. In the first place, a methodology for data analysis was defined processing netcdf data regarding a ten year wind hindcast from WRF (Weather Research and Forecasting) atmospheric model at 100 m above mean sea level from Ocean Observatory, annual and monthly mean offshore wind energy resource maps were created and a comparison with about 20 year times series of surface winds derived from remotely satellite scatterometer observations at different locations was made. Results show that the average annual mean wind speeds reach the range of 6.6–7.6 m/s in specific areas, situated in the northern part of Porto Santo Island with a Weibull distribution shape parameter (k) of 2.4–2.9. Based on the results, the wind resource assessment, the estimation of the annual wind energy production and capacity factors were calculated from the best-fitted Weibull distribution for each of the geographical coordinates selected. Comparisons with observational data show that WRF model is a proficient wind generating tool. The technical energy production potential and a priority zoning for offshore wind power development is performed using wind turbine generators of 3.3 MW–8.0 MW capacity, that could generate between 12 and 26 GWh of energy per year, while avoiding CO2 emissions. The results show that an offshore wind farm plan is an eligible choice, with an average annual wind power density reaching about 300  W/m2 at 100 m height in the north region.

scholarly journals Estimating Air Density Using Observations and Re-Analysis Outputs for Wind Energy Purposes

Energies ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 2038 ◽  
Author(s):  
Rogier Floors ◽  
Morten Nielsen
Keyword(s):  
Wind Energy ◽  
Energy Resource ◽  
Analysis Data ◽  
Resource Assessment ◽  
Current Version ◽  
Wind Resource Assessment ◽  
Industry Standard ◽  
Air Density ◽  
Wind Resource ◽  
Power Curves

A method to estimate air density as a function of elevation for wind energy resource assessments is presented. The current practice of using nearby measurements of pressure and temperature is compared with a method that uses re-analysis data. It is found that using re-analysis data to estimate air density gives similar or smaller mean absolute errors compared to using measurements that were on average located 40 km away. A method to interpolate power curves that are valid for different air densities is presented. The new model is implemented in the industry-standard model for wind resource assessment and compared with the current version of that model and shown to lead to more accurate assessment of the air density at different elevations.

Practical Wind Resource Assessment for Tayside Region in Scotland

1995 ◽  
Vol 6 (4) ◽  
pp. 361-381
Author(s):  
G.S. Saluja ◽  
N.G. Douglas
Keyword(s):  
Renewable Energy ◽  
Wind Energy ◽  
Energy Resource ◽  
Resource Assessment ◽  
Wind Speeds ◽  
Wind Resource Assessment ◽  
Planning Policy ◽  
Policy Guideline ◽  
Wind Energy Development ◽  
Wind Resource

This paper presents the results of a study which estimates the practical wind energy resource for the Tayside Region of Scotland. The study considered all technical, environmental and legislative factors relevant to wind energy development. Due consideration was also given to National Planning Policy Guideline (NPPG6): Renewable Energy and Planning Advice Note 45 (PAN45): Renewable Energy Technology, issued by the Scottish Office Environment Department, in addition to the policies of the planning authorities within Tayside with regards to such matters as development in National Scenic Areas and other designated areas. An area of 1290 km2 was identified as being the minimum practical resource which is free from environmental and technical constraints and which has sufficiently high wind speeds to make extraction of energy from the wind commercially viable. This area could accommodate an installed wind energy capacity of 9675 MW and produce 24.6 TWh of wind generated electricity per annum.

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