Wind Estimate by a Mesoscale Model

Abstract:

Wind is an energy source that has been used for a long time to reach many goals, but has recently become very important in electricity generation. In Rio Grande, a city located in Rio Grande do Sul state, in the extreme south of Brazil, wind forecast is important due to several weather phenomena of different time and space scales that act in the region. They make wind energy be one of the most difficult energy sources to be forecasted, since small variations of wind estimates may result in large differences in energy that is effectively generated. This study aimed at evaluating the performance of a mesoscale model to simulate wind intensity and estimating electricity production by aerogenerators, with and without nudging. This method enabled simulations to be carried out for a long time, with no spin-up time. The period of study is from June 9th to 14th, 2017, with two horizontal grids nested, of 3 and1 km. Results showed that the model is more accurate when nudging rather than spin-up is used. Nevertheless, the model still leads to errors in power forecast, by comparison with the wind power measured at the aerogenerator.

• Periodical: Defect and Diffusion Forum (Volume 396)
• Pages: 197-206
• DOI: https://doi.org/10.4028/www.scientific.net/DDF.396.197
• Online since: August 2019
• Authors: Camila e Silva Gomes*, Nisia Krusche
• Keywords: Mesoscale Model, Wind, Wind Energy

References

[1] Kassem Y, Çamur H, Alghazali A. Evaluation of Wind Energy Potential and Economic Analysis of Wind Energy Turbine Using Present Value Cost Method at Famagusta, Rizokarpaso, Kyrenia, Morphou, Nicosia and Ercan in Cyprus: Case Study. Conf FULL-PAPER 3 RD Int Conf Appl Econ Financ. 2017;(December 2017):63–80.

[2] CCEE. 1. sumário executivo. infoMercado. 2018;127:1–9.

[3] ASSOCIAÇÃO BRASILEIRA DE ENERGIA EÓLICA (ABEEOLICA). Dados Mensais. Bol Anu GERAÇÃO EÓLICA 2017 [Internet]. 2018; Available from: https://www.institutototum.com.br/images/totum/arquivos/Boletim-Anual-de-Geracao-2017.pdf.

[4] Pinto IC. AVALIAÇÃO DO MODELO WRF PARA APLICAÇÃO EM PREVISÃO DE RECURSOS EÓLICOS NO Tese de Doutorado do Curso de Pós-Graduação em Ciência do Sistema Terrestre , orientada pelos Drs . Enio Bueno Pereira , Fernando Ramos Martins , e José Antônio Marengo Orsíni , apr. (2017).

DOI: 10.14393/ufu.di.2015.1

[5] Zanotta RC. AVALIAÇÃO DO DESEMPENHO DE UM MODELO ATMOSFÉRICO DE MESOESCALA NA ESTIMATIVA DE GERAÇÃO DE ENERGIA ELÉTRICA POR AEROGERADORES. Rio Grande: Dissertação; (2017).

DOI: 10.14393/ufu.di.2020.408

[6] Skamarock WC, Klemp JB, Dudhia J, Gill DO, Barker DM, Duda MG, et al. ARW Modelling System UserGuide V.3. Book. 2016;(January):408.

[7] Laprise R. The Euler Equations of Motion with Hydrostatic Pressure as an Independent Variable. Mon Weather Rev 120. 1992;197–207.

DOI: 10.1175/1520-0493(1992)120<0197:teeomw>2.0.co;2

[8] Hoke JE, Anthes RA. The Initialization of Numerical Models by a Dynamic-Initialization Technique [Internet]. Vol. 104, Monthly Weather Review. 1976. p.1551–6. Available from: http://journals.ametsoc.org/doi/abs/10.1175/1520-0493%281976%29104%3C1551%3ATIONMB%3E2.0.CO%3B2.

DOI: 10.1175/1520-0493(1976)104<1551:tionmb>2.0.co;2

[9] Stauffer DR, Seaman NL. Use of Four-Dimensional Data Assimilation in a Limited-Area Mesoscale Model. Part I: Experiments with Synoptic-Scale Data [Internet]. Vol. 118, Monthly Weather Review. 1990. p.1250–77. Available from: http://journals.ametsoc.org/doi/abs/10.1175/1520-0493%281990%29118%3C1250%3AUOFDDA%3E2.0.CO%3B2.

DOI: 10.1175/1520-0493(1990)118<1250:uofdda>2.0.co;2

[10] Deng A, Stauffer DR, Dudhia J, Otte TL, Hunter GK. Update on Analysis Nudging FDDA in WRF-ARW. 2006;(1).

[11] Hou Y-T, Moorthi S, Campana K. Parameterization of solar radiation transfer in the NCEP models. NCEP Off Note. 2002;441:1–34.

[12] Kain JS. The Kain–Fritsch Convective Parameterization: An Update. J Appl Meteorol [Internet]. 2004;43(1):170–81. Available from: http://journals.ametsoc.org/doi/abs/ 10.1175/1520-0450%282004%29043%3C0170%3ATKCPAU%3E2.0.CO%3B2.

DOI: 10.1175/1520-0450(2004)043<0170:tkcpau>2.0.co;2

[13] Hong S-Y, Noh Y, Dudhia J. A New Vertical Diffusion Package with an Explicit Treatment of Entrainment Processes. Mon Weather Rev [Internet]. 2006;134(9):2318–41. Available from: http://journals.ametsoc.org/doi/abs/10.1175/MWR3199.1.

DOI: 10.1175/mwr3199.1

[14] Banks RF, Tiana-Alsina J, Baldasano JM, Rocadenbosch F, Papayannis A, Solomos S, et al. Sensitivity of boundary-layer variables to PBL schemes in the WRF model based on surface meteorological observations, lidar, and radiosondes during the HygrA-CD campaign. Atmos Res [Internet]. 2016;176–177:185–201. Available from: http://dx.doi.org/10.1016/j.atmosres. 2016.02.024.

DOI: 10.1016/j.atmosres.2016.02.024

[15] Moreira DS, Dias PL da S, Lucio PS. SISTEMA DE AVALIAÇÃO ESTATÍSTICA DE MODELOS NUMÉRICOS DE PREVISÃO DO TEMPO. 2006;(11):1–36. Available from: http://mtc-m16b.sid.inpe.br/col/sid.inpe.br/mtc-m15@80/2006/11.07.11.25/doc/Moreira. Sistema.pdf.

DOI: 10.1590/s0102-77862010000100006