IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i9p1442-d112480.html
   My bibliography  Save this article

Techno-Economic Assessment of Wind Energy Potential at Three Locations in South Korea Using Long-Term Measured Wind Data

Author

Listed:
  • Sajid Ali

    (Smart City Construction Engineering, University of Science & Technology (UST), 217, Gajeong-ro, Yuseong-gu, Daejeon 34113, Korea
    Environmental & Plant Engineering Research Division, Korea Institute of Civil Engineering and Building Technology (KICT), Daehwa-dong 283, Goyangdae-Ro, Ilsanseo-Gu, Goyang-Si, Gyeonggi-do 10223, Korea)

  • Sang-Moon Lee

    (Environmental & Plant Engineering Research Division, Korea Institute of Civil Engineering and Building Technology (KICT), Daehwa-dong 283, Goyangdae-Ro, Ilsanseo-Gu, Goyang-Si, Gyeonggi-do 10223, Korea)

  • Choon-Man Jang

    (Smart City Construction Engineering, University of Science & Technology (UST), 217, Gajeong-ro, Yuseong-gu, Daejeon 34113, Korea
    Environmental & Plant Engineering Research Division, Korea Institute of Civil Engineering and Building Technology (KICT), Daehwa-dong 283, Goyangdae-Ro, Ilsanseo-Gu, Goyang-Si, Gyeonggi-do 10223, Korea)

Abstract

The present study deals with wind energy analysis and the selection of an optimum type of wind turbine in terms of the feasibility of installing wind power system at three locations in South Korea: Deokjeok-do, Baengnyeong-do and Seo-San. The wind data measurements were conducted during 2005–2015 at Deokjeok-do, 2001–2016 at Baengnyeong-do and 1997–2016 at Seo-San. In the first part of this paper wind conditions, like mean wind speed, wind rose diagrams and Weibull shape and scale parameters are presented, so that the wind potential of all the locations could be assessed. It was found that the prevailing wind directions at all locations was either southeast or southwest in which the latter one being more dominant. After analyzing the wind conditions, 50-year and 1-year extreme wind speeds (EWS) were estimated using the graphical method of Gumbel distribution. Finally, according to the wind conditions at each site and international electro-technical commission (IEC) guidelines, a set of five different wind turbines best suited for each location were shortlisted. Each wind turbine was evaluated on the basis of technical parameters like monthly energy production, annual energy production (AEP) and capacity factors (CF). Similarly, economical parameters including net present value (NPV), internal rate of return (IRR), payback period (PBP) and levelized cost of electricity (LCOE) were considered. The analysis shows that a Doosan model WinDS134/3000 wind turbine is the most suitable for Deokjeok-do and Baengnyeong-do, whereas a Hanjin model HJWT 87/2000 is the most suitable wind turbine for Seo-San. Economic sensitivity analysis is also included and discussed in detail to analyze the impact on economics of wind power by varying turbine’s hub height.

Suggested Citation

  • Sajid Ali & Sang-Moon Lee & Choon-Man Jang, 2017. "Techno-Economic Assessment of Wind Energy Potential at Three Locations in South Korea Using Long-Term Measured Wind Data," Energies, MDPI, vol. 10(9), pages 1-24, September.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:9:p:1442-:d:112480
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/9/1442/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/10/9/1442/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cosentino, Valentina & Favuzza, Salvatore & Graditi, Giorgio & Ippolito, Mariano Giuseppe & Massaro, Fabio & Riva Sanseverino, Eleonora & Zizzo, Gaetano, 2012. "Smart renewable generation for an islanded system. Technical and economic issues of future scenarios," Energy, Elsevier, vol. 39(1), pages 196-204.
    2. Carneiro, Tatiane C. & Melo, Sofia P. & Carvalho, Paulo C.M. & Braga, Arthur Plínio de S., 2016. "Particle Swarm Optimization method for estimation of Weibull parameters: A case study for the Brazilian northeast region," Renewable Energy, Elsevier, vol. 86(C), pages 751-759.
    3. Carta, J.A. & Ramírez, P. & Velázquez, S., 2009. "A review of wind speed probability distributions used in wind energy analysis: Case studies in the Canary Islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(5), pages 933-955, June.
    4. Kim, Ji-Young & Oh, Ki-Yong & Kang, Keum-Seok & Lee, Jun-Shin, 2013. "Site selection of offshore wind farms around the Korean Peninsula through economic evaluation," Renewable Energy, Elsevier, vol. 54(C), pages 189-195.
    5. Lee, Myung Eun & Kim, Gunwoo & Jeong, Shin-Taek & Ko, Dong Hui & Kang, Keum Seok, 2013. "Assessment of offshore wind energy at Younggwang in Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 131-141.
    6. Chang-Gi Min & Jong Keun Park & Don Hur & Mun-Kyeom Kim, 2015. "The Economic Viability of Renewable Portfolio Standard Support for Offshore Wind Farm Projects in Korea," Energies, MDPI, vol. 8(9), pages 1-20, September.
    7. Kim, Hyeonwu & Kim, Bumsuk, 2016. "Wind resource assessment and comparative economic analysis using AMOS data on a 30 MW wind farm at Yulchon district in Korea," Renewable Energy, Elsevier, vol. 85(C), pages 96-103.
    8. Riva Sanseverino, Eleonora & Riva Sanseverino, Raffaella & Favuzza, Salvatore & Vaccaro, Valentina, 2014. "Near zero energy islands in the Mediterranean: Supporting policies and local obstacles," Energy Policy, Elsevier, vol. 66(C), pages 592-602.
    9. Mirhosseini, M. & Sharifi, F. & Sedaghat, A., 2011. "Assessing the wind energy potential locations in province of Semnan in Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 449-459, January.
    10. 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.
    11. Oh, Ki-Yong & Kim, Ji-Young & Lee, Jae-Kyung & Ryu, Moo-Sung & Lee, Jun-Shin, 2012. "An assessment of wind energy potential at the demonstration offshore wind farm in Korea," Energy, Elsevier, vol. 46(1), pages 555-563.
    12. Dicorato, M. & Forte, G. & Pisani, M. & Trovato, M., 2011. "Guidelines for assessment of investment cost for offshore wind generation," Renewable Energy, Elsevier, vol. 36(8), pages 2043-2051.
    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. Ahmed WA Hammad & Ali Akbarnezhad & Assed Haddad & Elaine Garrido Vazquez, 2019. "Sustainable Zoning, Land-Use Allocation and Facility Location Optimisation in Smart Cities," Energies, MDPI, vol. 12(7), pages 1-23, April.
    2. Sajid Ali & Choon-Man Jang, 2019. "Selection of Best-Suited Wind Turbines for New Wind Farm Sites Using Techno-Economic and GIS Analysis in South Korea," Energies, MDPI, vol. 12(16), pages 1-22, August.
    3. Suzer, Ahmet Esat & Atasoy, Vehbi Emrah & Ekici, Selcuk, 2021. "Developing a holistic simulation approach for parametric techno-economic analysis of wind energy," Energy Policy, Elsevier, vol. 149(C).
    4. Sajid Ali & Sang-Moon Lee & Choon-Man Jang, 2018. "Forecasting the Long-Term Wind Data via Measure-Correlate-Predict (MCP) Methods," Energies, MDPI, vol. 11(6), pages 1-17, June.
    5. Sajid Ali & Choon-Man Jang, 2020. "Optimum Design of Hybrid Renewable Energy System for Sustainable Energy Supply to a Remote Island," Sustainability, MDPI, vol. 12(3), pages 1-16, February.
    6. Dongbum Kang & Kyungnam Ko & Jongchul Huh, 2018. "Comparative Study of Different Methods for Estimating Weibull Parameters: A Case Study on Jeju Island, South Korea," Energies, MDPI, vol. 11(2), pages 1-19, February.
    7. Laura Cornejo-Bueno & Lucas Cuadra & Silvia Jiménez-Fernández & Javier Acevedo-Rodríguez & Luis Prieto & Sancho Salcedo-Sanz, 2017. "Wind Power Ramp Events Prediction with Hybrid Machine Learning Regression Techniques and Reanalysis Data," Energies, MDPI, vol. 10(11), pages 1-27, November.
    8. Peláez-Rodríguez, C. & Pérez-Aracil, J. & Fister, D. & Prieto-Godino, L. & Deo, R.C. & Salcedo-Sanz, S., 2022. "A hierarchical classification/regression algorithm for improving extreme wind speed events prediction," Renewable Energy, Elsevier, vol. 201(P2), pages 157-178.
    9. Li, Ming & Luo, Haojie & Zhou, Shijie & Senthil Kumar, Gokula Manikandan & Guo, Xinman & Law, Tin Chung & Cao, Sunliang, 2022. "State-of-the-art review of the flexibility and feasibility of emerging offshore and coastal ocean energy technologies in East and Southeast Asia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    10. Mohammed H. Alsharif & Jeong Kim & Jin Hong Kim, 2018. "Opportunities and Challenges of Solar and Wind Energy in South Korea: A Review," Sustainability, MDPI, vol. 10(6), pages 1-23, June.

    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. Ali, Sajid & Lee, Sang-Moon & Jang, Choon-Man, 2018. "Statistical analysis of wind characteristics using Weibull and Rayleigh distributions in Deokjeok-do Island – Incheon, South Korea," Renewable Energy, Elsevier, vol. 123(C), pages 652-663.
    2. Sajid Ali & Sang-Moon Lee & Choon-Man Jang, 2017. "Determination of the Most Optimal On-Shore Wind Farm Site Location Using a GIS-MCDM Methodology: Evaluating the Case of South Korea," Energies, MDPI, vol. 10(12), pages 1-22, December.
    3. Mohammed H. Alsharif & Jeong Kim & Jin Hong Kim, 2018. "Opportunities and Challenges of Solar and Wind Energy in South Korea: A Review," Sustainability, MDPI, vol. 10(6), pages 1-23, June.
    4. Sajid Ali & Choon-Man Jang, 2019. "Selection of Best-Suited Wind Turbines for New Wind Farm Sites Using Techno-Economic and GIS Analysis in South Korea," Energies, MDPI, vol. 12(16), pages 1-22, August.
    5. Poulsen, Thomas & Lema, Rasmus, 2017. "Is the supply chain ready for the green transformation? The case of offshore wind logistics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 758-771.
    6. Kim, Ji-Young & Oh, Ki-Yong & Kim, Min-Suek & Kim, Kwang-Yul, 2019. "Evaluation and characterization of offshore wind resources with long-term met mast data corrected by wind lidar," Renewable Energy, Elsevier, vol. 144(C), pages 41-55.
    7. Oh, Ki-Yong & Nam, Woochul & Ryu, Moo Sung & Kim, Ji-Young & Epureanu, Bogdan I., 2018. "A review of foundations of offshore wind energy convertors: Current status and future perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 16-36.
    8. Woochul Nam & Ki-Yong Oh, 2020. "Mutually Complementary Measure-Correlate-Predict Method for Enhanced Long-Term Wind-Resource Assessment," Mathematics, MDPI, vol. 8(10), pages 1-20, October.
    9. Fazelpour, Farivar & Markarian, Elin & Soltani, Nima, 2017. "Wind energy potential and economic assessment of four locations in Sistan and Balouchestan province in Iran," Renewable Energy, Elsevier, vol. 109(C), pages 646-667.
    10. Amirinia, Gholamreza & Mafi, Somayeh & Mazaheri, Said, 2017. "Offshore wind resource assessment of Persian Gulf using uncertainty analysis and GIS," Renewable Energy, Elsevier, vol. 113(C), pages 915-929.
    11. Zizzo, G. & Beccali, M. & Bonomolo, M. & Di Pietra, B. & Ippolito, M.G. & La Cascia, D. & Leone, G. & Lo Brano, V. & Monteleone, F., 2017. "A feasibility study of some DSM enabling solutions in small islands: The case of Lampedusa," Energy, Elsevier, vol. 140(P1), pages 1030-1046.
    12. Nam, Woochul & Oh, Ki-Yong & Epureanu, Bogdan I., 2019. "Evolution of the dynamic response and its effects on the serviceability of offshore wind turbines with stochastic loads and soil degradation," Reliability Engineering and System Safety, Elsevier, vol. 184(C), pages 151-163.
    13. Deveci, Muhammet & Cali, Umit & Kucuksari, Sadik & Erdogan, Nuh, 2020. "Interval type-2 fuzzy sets based multi-criteria decision-making model for offshore wind farm development in Ireland," Energy, Elsevier, vol. 198(C).
    14. Jin-Young Kim & Hyun-Goo Kim & Yong-Heack Kang, 2017. "Offshore Wind Speed Forecasting: The Correlation between Satellite-Observed Monthly Sea Surface Temperature and Wind Speed over the Seas around the Korean Peninsula," Energies, MDPI, vol. 10(7), pages 1-15, July.
    15. Satir, Mert & Murphy, Fionnuala & McDonnell, Kevin, 2018. "Feasibility study of an offshore wind farm in the Aegean Sea, Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2552-2562.
    16. Ko, Dong Hui & Jeong, Shin Taek & Kim, Yoon Chil, 2015. "Assessment of wind energy for small-scale wind power in Chuuk State, Micronesia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 613-622.
    17. Wais, Piotr, 2017. "Two and three-parameter Weibull distribution in available wind power analysis," Renewable Energy, Elsevier, vol. 103(C), pages 15-29.
    18. Chang, Tian-Pau & Liu, Feng-Jiao & Ko, Hong-Hsi & Cheng, Shih-Ping & Sun, Li-Chung & Kuo, Shye-Chorng, 2014. "Comparative analysis on power curve models of wind turbine generator in estimating capacity factor," Energy, Elsevier, vol. 73(C), pages 88-95.
    19. Yang, Zihao & Dong, Sheng, 2024. "A novel framework for wind energy assessment at multi-time scale based on non-stationary wind speed models: A case study in China," Renewable Energy, Elsevier, vol. 226(C).
    20. El Alimi, Souheil & Maatallah, Taher & Dahmouni, Anouar Wajdi & Ben Nasrallah, Sassi, 2012. "Modeling and investigation of the wind resource in the gulf of Tunis, Tunisia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 5466-5478.

    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:gam:jeners:v:10:y:2017:i:9:p:1442-:d:112480. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.