IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v139y2017icp706-731.html
   My bibliography  Save this article

Offshore wind resource assessment and wind power plant optimization in the Gulf of Thailand

Author

Listed:
  • Chancham, Chana
  • Waewsak, Jompob
  • Gagnon, Yves

Abstract

This paper presents the offshore wind resource assessment and an offshore wind power plant optimization in the Gulf of Thailand (GoT). The Weather Research and Forecasting (WRF) atmospheric model, along with the NCEP/NCAR R2 reanalysis climatic database, are applied to create wind resource maps at 80 m, 100 m, and 120 m above mean sea level (amsl) in order to identify the potential surface areas for the development of offshore wind power plants. The predicted wind speeds are validated using observed wind speeds obtained from 13 met masts installed along the coastline of the GoT. Results show that the average annual mean wind speeds reach the range of 5.5–6.5 m/s in specific areas of the Bay of Bangkok, situated in the northern part of the GoT. Based on the results of the wind resource assessment and using computational fluid dynamics microscale wind flow modelings, a wind power plant optimization is performed. The technical power potential and a priority zoning for offshore wind power development is performed using wind turbine generators of 3.3–8.0 MW capacity. Depending on the wind turbine generator selected, it is found that 642–924 MW of capacity could be installed in the short-term planning; 2658 to 3825 MW of additional capacity could be added in the medium-term planning, and 2864 to 4120 MW of additional capacity in the long-term planning. These wind power plants would have an annual energy production in the order of 5.6–8 PWh in the short-term, an additional 23 to 33 PWh in the medium-term, and an additional 25 to 36 PWh in the long-term, thus avoiding CO2eq emissions in the order of 3–4.5 million tons CO2eq per year in the short-term, 13 to 18 million tons in the medium-term, and 14 to 20 million tons in the long-term. In total, depending on the wind turbine generator selected, wind power plants in the GoT could have a total installed capacity of 6000 to over 8000 MW, would generate between 50 and 75 PWh of energy per year, while avoiding emissions of 30–40 million tons CO2eq per year.

Suggested Citation

  • Chancham, Chana & Waewsak, Jompob & Gagnon, Yves, 2017. "Offshore wind resource assessment and wind power plant optimization in the Gulf of Thailand," Energy, Elsevier, vol. 139(C), pages 706-731.
  • Handle: RePEc:eee:energy:v:139:y:2017:i:c:p:706-731
    DOI: 10.1016/j.energy.2017.08.026
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544217314019
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2017.08.026?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dhanju, Amardeep & Whitaker, Phillip & Kempton, Willett, 2008. "Assessing offshore wind resources: An accessible methodology," Renewable Energy, Elsevier, vol. 33(1), pages 55-64.
    2. Rehman, Shafiqur & Ahmad, Aftab & Al-Hadhrami, Luai M., 2011. "Development and economic assessment of a grid connected 20Â MW installed capacity wind farm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 833-838, January.
    3. Karagali, Ioanna & Badger, Merete & Hahmann, Andrea N. & Peña, Alfredo & B. Hasager, Charlotte & Sempreviva, Anna Maria, 2013. "Spatial and temporal variability of winds in the Northern European Seas," Renewable Energy, Elsevier, vol. 57(C), pages 200-210.
    4. Kota, Sandhya & Bayne, Stephen B. & Nimmagadda, Sandeep, 2015. "Offshore wind energy: A comparative analysis of UK, USA and India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 685-694.
    5. Waewsak, Jompob & Landry, Mathieu & Gagnon, Yves, 2015. "Offshore wind power potential of the Gulf of Thailand," Renewable Energy, Elsevier, vol. 81(C), pages 609-626.
    6. Mattar, Cristian & Borvarán, Dager, 2016. "Offshore wind power simulation by using WRF in the central coast of Chile," Renewable Energy, Elsevier, vol. 94(C), pages 22-31.
    7. Oh, Ki-Yong & Kim, Ji-Young & Lee, Jun-Shin & Ryu, Ki-Wahn, 2012. "Wind resource assessment around Korean Peninsula for feasibility study on 100 MW class offshore wind farm," Renewable Energy, Elsevier, vol. 42(C), pages 217-226.
    8. Himri, Y. & Rehman, S. & Agus Setiawan, A. & Himri, S., 2012. "Wind energy for rural areas of Algeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 2381-2385.
    9. Waewsak, Jompob & Landry, Mathieu & Gagnon, Yves, 2013. "High resolution wind atlas for Nakhon Si Thammarat and Songkhla provinces, Thailand," Renewable Energy, Elsevier, vol. 53(C), pages 101-110.
    10. Nagababu, Garlapati & Kachhwaha, Surendra Singh & Naidu, Natansh K. & Savsani, Vimal, 2017. "Application of reanalysis data to estimate offshore wind potential in EEZ of India based on marine ecosystem considerations," Energy, Elsevier, vol. 118(C), pages 622-631.
    11. Baseer, M.A. & Meyer, J.P. & Alam, Md. Mahbub & Rehman, S., 2015. "Wind speed and power characteristics for Jubail industrial city, Saudi Arabia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1193-1204.
    12. Möller, Bernd & Hong, Lixuan & Lonsing, Reinhard & Hvelplund, Frede, 2012. "Evaluation of offshore wind resources by scale of development," Energy, Elsevier, vol. 48(1), pages 314-322.
    13. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2014. "Sensitivity of the WRF model wind simulation and wind energy production estimates to planetary boundary layer parameterizations for onshore and offshore areas in the Iberian Peninsula," Applied Energy, Elsevier, vol. 135(C), pages 234-246.
    14. Castro-Santos, Laura & Filgueira-Vizoso, Almudena & Carral-Couce, Luis & Formoso, José Ángel Fraguela, 2016. "Economic feasibility of floating offshore wind farms," Energy, Elsevier, vol. 112(C), pages 868-882.
    15. Shu, Z.R. & Li, Q.S. & He, Y.C. & Chan, P.W., 2016. "Observations of offshore wind characteristics by Doppler-LiDAR for wind energy applications," Applied Energy, Elsevier, vol. 169(C), pages 150-163.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Christina Ortega & Amin Younes & Mark Severy & Charles Chamberlin & Arne Jacobson, 2020. "Resource and Load Compatibility Assessment of Wind Energy Offshore of Humboldt County, California," Energies, MDPI, vol. 13(21), pages 1-27, October.
    2. Wang, Jianzhou & Huang, Xiaojia & Li, Qiwei & Ma, Xuejiao, 2018. "Comparison of seven methods for determining the optimal statistical distribution parameters: A case study of wind energy assessment in the large-scale wind farms of China," Energy, Elsevier, vol. 164(C), pages 432-448.
    3. Li, Jiale & Wang, Xuefei & Yu, Xiong (Bill), 2018. "Use of spatio-temporal calibrated wind shear model to improve accuracy of wind resource assessment," Applied Energy, Elsevier, vol. 213(C), pages 469-485.
    4. Dayal, Kunal K. & Bellon, Gilles & Cater, John E. & Kingan, Michael J. & Sharma, Rajnish N., 2021. "High-resolution mesoscale wind-resource assessment of Fiji using the Weather Research and Forecasting (WRF) model," Energy, Elsevier, vol. 232(C).
    5. Jared A. Lee & Paula Doubrawa & Lulin Xue & Andrew J. Newman & Caroline Draxl & George Scott, 2019. "Wind Resource Assessment for Alaska’s Offshore Regions: Validation of a 14-Year High-Resolution WRF Data Set," Energies, MDPI, vol. 12(14), pages 1-22, July.
    6. Dong, Cong & Huang, Guohe (Gordon) & Cheng, Guanhui, 2021. "Offshore wind can power Canada," Energy, Elsevier, vol. 236(C).
    7. Tuchtenhagen, Patrícia & Carvalho, Gilvani Gomes de & Martins, Guilherme & Silva, Pollyanne Evangelista da & Oliveira, Cristiano Prestrelo de & de Melo Barbosa Andrade, Lara & Araújo, João Medeiros de, 2020. "WRF model assessment for wind intensity and power density simulation in the southern coast of Brazil," Energy, Elsevier, vol. 190(C).
    8. Waewsak, Jompob & Ali, Shahid & Natee, Warut & Kongruang, Chuleerat & Chancham, Chana & Gagnon, Yves, 2020. "Assessment of hybrid, firm renewable energy-based power plants: Application in the southernmost region of Thailand," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    9. Li, Jiale & Yu, Xiong (Bill), 2018. "Onshore and offshore wind energy potential assessment near Lake Erie shoreline: A spatial and temporal analysis," Energy, Elsevier, vol. 147(C), pages 1092-1107.
    10. Segura, E. & Morales, R. & Somolinos, J.A., 2018. "Economic-financial modeling for marine current harnessing projects," Energy, Elsevier, vol. 158(C), pages 859-880.
    11. Salvação, N. & Guedes Soares, C., 2018. "Wind resource assessment offshore the Atlantic Iberian coast with the WRF model," Energy, Elsevier, vol. 145(C), pages 276-287.
    12. Gualtieri, G., 2022. "Analysing the uncertainties of reanalysis data used for wind resource assessment: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    13. Guerrero-Lemus, Ricardo & Nuez, Ignacio de la & González-Díaz, Benjamín, 2018. "Rebuttal letter to the article entitled: “Spatial planning to estimate the offshore wind energy potential in coastal regions and islands. Practical case: The Canary Islands”," Energy, Elsevier, vol. 153(C), pages 12-16.
    14. Al-Nassar, W.K. & Neelamani, S. & Al-Salem, K.A. & Al-Dashti, H.A., 2019. "Feasibility of offshore wind energy as an alternative source for the state of Kuwait," Energy, Elsevier, vol. 169(C), pages 783-796.
    15. Tuy, Soklin & Lee, Han Soo & Chreng, Karodine, 2022. "Integrated assessment of offshore wind power potential using Weather Research and Forecast (WRF) downscaling with Sentinel-1 satellite imagery, optimal sites, annual energy production and equivalent C," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    16. Nguyen, Thi Anh Tuyet & Chou, Shuo-Yan, 2019. "Improved maintenance optimization of offshore wind systems considering effects of government subsidies, lost production and discounted cost model," Energy, Elsevier, vol. 187(C).
    17. Lattawan Niyomtham & Charoenporn Lertsathittanakorn & Jompob Waewsak & Yves Gagnon, 2022. "Mesoscale/Microscale and CFD Modeling for Wind Resource Assessment: Application to the Andaman Coast of Southern Thailand," Energies, MDPI, vol. 15(9), pages 1-19, April.
    18. Minhyeop Kang & Kyungnam Ko & Minyeong Kim, 2020. "Verification of the Reliability of Offshore Wind Resource Prediction Using an Atmosphere–Ocean Coupled Model," Energies, MDPI, vol. 13(1), pages 1-15, January.
    19. He, J.Y. & Chan, P.W. & Li, Q.S. & Lee, C.W., 2022. "Characterizing coastal wind energy resources based on sodar and microwave radiometer observations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    20. Chen, Xinping & Foley, Aoife & Zhang, Zenghai & Wang, Kaimin & O'Driscoll, Kieran, 2020. "An assessment of wind energy potential in the Beibu Gulf considering the energy demands of the Beibu Gulf Economic Rim," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    21. He, Junyi & Chan, P.W. & Li, Qiusheng & Lee, C.W., 2020. "Spatiotemporal analysis of offshore wind field characteristics and energy potential in Hong Kong," Energy, Elsevier, vol. 201(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Salvação, N. & Guedes Soares, C., 2018. "Wind resource assessment offshore the Atlantic Iberian coast with the WRF model," Energy, Elsevier, vol. 145(C), pages 276-287.
    2. Peters, Jared L. & Remmers, Tiny & Wheeler, Andrew J. & Murphy, Jimmy & Cummins, Valerie, 2020. "A systematic review and meta-analysis of GIS use to reveal trends in offshore wind energy research and offer insights on best practices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 128(C).
    3. Jompob Waewsak & Chana Chancham & Somphol Chiwamongkhonkarn & Yves Gagnon, 2019. "Wind Resource Assessment of the Southernmost Region of Thailand Using Atmospheric and Computational Fluid Dynamics Wind Flow Modeling," Energies, MDPI, vol. 12(10), pages 1-18, May.
    4. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2017. "Offshore winds and wind energy production estimates derived from ASCAT, OSCAT, numerical weather prediction models and buoys – A comparative study for the Iberian Peninsula Atlantic coast," Renewable Energy, Elsevier, vol. 102(PB), pages 433-444.
    5. Waewsak, Jompob & Landry, Mathieu & Gagnon, Yves, 2015. "Offshore wind power potential of the Gulf of Thailand," Renewable Energy, Elsevier, vol. 81(C), pages 609-626.
    6. Majidi Nezhad, Meysam & Neshat, Mehdi & Piras, Giuseppe & Astiaso Garcia, Davide, 2022. "Sites exploring prioritisation of offshore wind energy potential and mapping for wind farms installation: Iranian islands case studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    7. Arun Kumar, Surisetty V.V. & Nagababu, Garlapati & Kumar, Raj, 2019. "Comparative study of offshore winds and wind energy production derived from multiple scatterometers and met buoys," Energy, Elsevier, vol. 185(C), pages 599-611.
    8. Nagababu, Garlapati & Kachhwaha, Surendra Singh & Savsani, Vimal, 2017. "Estimation of technical and economic potential of offshore wind along the coast of India," Energy, Elsevier, vol. 138(C), pages 79-91.
    9. de Assis Tavares, Luiz Filipe & Shadman, Milad & Assad, Luiz Paulo de Freitas & Estefen, Segen F., 2022. "Influence of the WRF model and atmospheric reanalysis on the offshore wind resource potential and cost estimation: A case study for Rio de Janeiro State," Energy, Elsevier, vol. 240(C).
    10. Shafiqur Rehman & Md. Mahbub Alam & Luai M. Alhems & M. Mujahid Rafique, 2018. "Horizontal Axis Wind Turbine Blade Design Methodologies for Efficiency Enhancement—A Review," Energies, MDPI, vol. 11(3), pages 1-34, February.
    11. Castro-Santos, Laura & Martins, Elson & Guedes Soares, C., 2017. "Economic comparison of technological alternatives to harness offshore wind and wave energies," Energy, Elsevier, vol. 140(P1), pages 1121-1130.
    12. Dhunny, A.Z. & Timmons, D.S. & Allam, Z. & Lollchund, M.R. & Cunden, T.S.M., 2020. "An economic assessment of near-shore wind farm development using a weather research forecast-based genetic algorithm model," Energy, Elsevier, vol. 201(C).
    13. Romanic, Djordje & Parvu, Dan & Refan, Maryam & Hangan, Horia, 2018. "Wind and tornado climatologies and wind resource modelling for a modern development situated in “Tornado Alley”," Renewable Energy, Elsevier, vol. 115(C), pages 97-112.
    14. Nie, Bingchuan & Li, Jiachun, 2018. "Technical potential assessment of offshore wind energy over shallow continent shelf along China coast," Renewable Energy, Elsevier, vol. 128(PA), pages 391-399.
    15. Tuy, Soklin & Lee, Han Soo & Chreng, Karodine, 2022. "Integrated assessment of offshore wind power potential using Weather Research and Forecast (WRF) downscaling with Sentinel-1 satellite imagery, optimal sites, annual energy production and equivalent C," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    16. González-Alonso de Linaje, N. & Mattar, C. & Borvarán, D., 2019. "Quantifying the wind energy potential differences using different WRF initial conditions on Mediterranean coast of Chile," Energy, Elsevier, vol. 188(C).
    17. Jiang, Dong & Zhuang, Dafang & Huang, Yaohuan & Wang, Jianhua & Fu, Jingying, 2013. "Evaluating the spatio-temporal variation of China's offshore wind resources based on remotely sensed wind field data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 142-148.
    18. Salvação, Nadia & Bentamy, Abderrahim & Guedes Soares, C., 2022. "Developing a new wind dataset by blending satellite data and WRF model wind predictions," Renewable Energy, Elsevier, vol. 198(C), pages 283-295.
    19. Cristian Mattar & Felipe Cabello-Españon & Nicolas G. Alonso-de-Linaje, 2021. "Towards a Future Scenario for Offshore Wind Energy in Chile: Breaking the Paradigm," Sustainability, MDPI, vol. 13(13), pages 1-16, June.
    20. Archer, C.L. & Simão, H.P. & Kempton, W. & Powell, W.B. & Dvorak, M.J., 2017. "The challenge of integrating offshore wind power in the U.S. electric grid. Part I: Wind forecast error," Renewable Energy, Elsevier, vol. 103(C), pages 346-360.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:139:y:2017:i:c:p:706-731. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.