IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v179y2021icp1742-1750.html
   My bibliography  Save this article

Potential capacity factor estimates of wind generating resources for transmission planning

Author

Listed:
  • Hur, Jin

Abstract

Wind Generating Resources (WGRs) are variable, uncontrollable, and uncertain compared to traditional generating resources. As Wind Generating Resources (WGRs) have the intermittent nature of WGRs and uncertain characteristics according to the weather condition, the accurate prediction of WGRs' capacity factor is an essential factor associated with integrating a large amount of wind generating resources into the grid. As wind farm outputs depend on natural wind resources that vary over space and time, spatial correlation analysis is also needed to estimate power outputs of wind generation resources. In this paper, we propose the potential capacity factor estimates of new wind generating resources using the augmented spatial analysis and modelling of power outputs produced by wind farms that are geographically distributed in windy areas. To validate the proposed spatial prediction model, we use the empirical data from the Jeju Island's wind farms in South Korea.

Suggested Citation

  • Hur, Jin, 2021. "Potential capacity factor estimates of wind generating resources for transmission planning," Renewable Energy, Elsevier, vol. 179(C), pages 1742-1750.
    • Handle: RePEc:eee:renene:v:179:y:2021:i:c:p:1742-1750
    DOI: 10.1016/j.renene.2021.08.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148121011757
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2021.08.015?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. Girard, R. & Laquaine, K. & Kariniotakis, G., 2013. "Assessment of wind power predictability as a decision factor in the investment phase of wind farms," Applied Energy, Elsevier, vol. 101(C), pages 609-617.
    2. Lee, Yerim & Hur, Jin, 2019. "A simultaneous approach implementing wind-powered electric vehicle charging stations for charging demand dispersion," Renewable Energy, Elsevier, vol. 144(C), pages 172-179.
    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. Bodong, Song & Wiseong, Jin & Chengmeng, Li & Khakichi, Aroos, 2023. "Economic management and planning based on a probabilistic model in a multi-energy market in the presence of renewable energy sources with a demand-side management program," Energy, Elsevier, vol. 269(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. Sehyeon Kim & Markus Holz & Soojin Park & Yongbeum Yoon & Eunchel Cho & Junsin Yi, 2021. "Future Options for Lightweight Photovoltaic Modules in Electrical Passenger Cars," Sustainability, MDPI, vol. 13(5), pages 1-7, February.
    2. Elberg, Christina & Hagspiel, Simeon, 2015. "Spatial dependencies of wind power and interrelations with spot price dynamics," European Journal of Operational Research, Elsevier, vol. 241(1), pages 260-272.
    3. Seyed Reza Mirnezami & Amin Mohseni Cheraghlou, 2022. "Wind Power in Iran: Technical, Policy, and Financial Aspects for Better Energy Resource Management," Energies, MDPI, vol. 15(9), pages 1-18, April.
    4. Rahimiyan, Morteza, 2014. "A statistical cognitive model to assess impact of spatially correlated wind production on market behaviors," Applied Energy, Elsevier, vol. 122(C), pages 62-72.
    5. Hu, Jing & Harmsen, Robert & Crijns-Graus, Wina & Worrell, Ernst, 2019. "Geographical optimization of variable renewable energy capacity in China using modern portfolio theory," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    6. Wang, Han & Yan, Jie & Han, Shuang & Liu, Yongqian, 2020. "Switching strategy of the low wind speed wind turbine based on real-time wind process prediction for the integration of wind power and EVs," Renewable Energy, Elsevier, vol. 157(C), pages 256-272.
    7. Petković, Dalibor & Shamshirband, Shahaboddin & Kamsin, Amirrudin & Lee, Malrey & Anicic, Obrad & Nikolić, Vlastimir, 2016. "Survey of the most influential parameters on the wind farm net present value (NPV) by adaptive neuro-fuzzy approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1270-1278.
    8. Enevoldsen, Peter, 2016. "Onshore wind energy in Northern European forests: Reviewing the risks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1251-1262.
    9. Julio Barzola-Monteses & Mónica Mite-León & Mayken Espinoza-Andaluz & Juan Gómez-Romero & Waldo Fajardo, 2019. "Time Series Analysis for Predicting Hydroelectric Power Production: The Ecuador Case," Sustainability, MDPI, vol. 11(23), pages 1-19, November.
    10. Hernández-Escobedo, Q. & Saldaña-Flores, R. & Rodríguez-García, E.R. & Manzano-Agugliaro, F., 2014. "Wind energy resource in Northern Mexico," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 890-914.
    11. Bossavy, Arthur & Girard, Robin & Kariniotakis, Georges, 2016. "Sensitivity analysis in the technical potential assessment of onshore wind and ground solar photovoltaic power resources at regional scale," Applied Energy, Elsevier, vol. 182(C), pages 145-153.
    12. Momeni, Farhang & Sabzpoushan, Seyedali & Valizadeh, Reza & Morad, Mohammad Reza & Liu, Xun & Ni, Jun, 2019. "Plant leaf-mimetic smart wind turbine blades by 4D printing," Renewable Energy, Elsevier, vol. 130(C), pages 329-351.
    13. Xu, Jiuping & Liu, Tingting, 2020. "Technological paradigm-based approaches towards challenges and policy shifts for sustainable wind energy development," Energy Policy, Elsevier, vol. 142(C).
    14. Qi, Yunying & Xu, Xiao & Liu, Youbo & Pan, Li & Liu, Junyong & Hu, Weihao, 2024. "Intelligent energy management for an on-grid hydrogen refueling station based on dueling double deep Q network algorithm with NoisyNet," Renewable Energy, Elsevier, vol. 222(C).
    15. Feng, Cong & Sun, Mucun & Cui, Mingjian & Chartan, Erol Kevin & Hodge, Bri-Mathias & Zhang, Jie, 2019. "Characterizing forecastability of wind sites in the United States," Renewable Energy, Elsevier, vol. 133(C), pages 1352-1365.
    16. Heba M. Abdullah & Rashad M. Kamel & Anas Tahir & Azzam Sleit & Adel Gastli, 2020. "The Simultaneous Impact of EV Charging and PV Inverter Reactive Power on the Hosting Distribution System’s Performance: A Case Study in Kuwait," Energies, MDPI, vol. 13(17), pages 1-22, August.
    17. Higgins, P. & Foley, A.M. & Douglas, R. & Li, K., 2014. "Impact of offshore wind power forecast error in a carbon constraint electricity market," Energy, Elsevier, vol. 76(C), pages 187-197.
    18. Jankowska, Barbara & Staliński, Adam & Trąpczyński, Piotr, 2021. "Public policy support and the competitiveness of the renewable energy sector – The case of Poland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    19. Hélène Le Cadre & Anthony Papavasiliou & Yves Smeers, 2015. "Wind Farm Portfolio Optimization under Network Capacity Constraints," Post-Print hal-01007992, HAL.
    20. Qiao, Zheng & Guo, Qinglai & Sun, Hongbin & Pan, Zhaoguang & Liu, Yuquan & Xiong, Wen, 2017. "An interval gas flow analysis in natural gas and electricity coupled networks considering the uncertainty of wind power," Applied Energy, Elsevier, vol. 201(C), pages 343-353.

    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:renene:v:179:y:2021:i:c:p:1742-1750. 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/renewable-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.