IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v113y2014icp648-659.html
   My bibliography  Save this article

Fast computation of the maximum wind penetration based on frequency response in small isolated power systems

Author

Listed:
  • Yu, H.Y.
  • Bansal, R.C.
  • Dong, Z.Y.

Abstract

This paper investigates the frequency deviation and stability analysis of a small isolated power system in response to various load levels and demand penetration of unit generators. From the analysis an optimal generation unit commitment strategy is presented in terms of system operation and expansion. The proposed strategy aims to prevent unnecessary generation outages due to frequency disturbances in the system and to ensure system security as well as for the integration of wind energy. This paper also demonstrates that the proposed frequency response technique which is fast and simple can be used to calculate the maximum allowable wind penetration for a small isolated power system.

Suggested Citation

  • Yu, H.Y. & Bansal, R.C. & Dong, Z.Y., 2014. "Fast computation of the maximum wind penetration based on frequency response in small isolated power systems," Applied Energy, Elsevier, vol. 113(C), pages 648-659.
    • Handle: RePEc:eee:appene:v:113:y:2014:i:c:p:648-659
    DOI: 10.1016/j.apenergy.2013.08.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261913006417
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2013.08.006?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. Kaldellis, J.K. & Kavadias, K.A. & Filios, A.E., 2009. "A new computational algorithm for the calculation of maximum wind energy penetration in autonomous electrical generation systems," Applied Energy, Elsevier, vol. 86(7-8), pages 1011-1023, July.
    2. Baringo, L. & Conejo, A.J., 2011. "Wind power investment within a market environment," Applied Energy, Elsevier, vol. 88(9), pages 3239-3247.
    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. Ochoa, Danny & Martinez, Sergio, 2018. "Frequency dependent strategy for mitigating wind power fluctuations of a doubly-fed induction generator wind turbine based on virtual inertia control and blade pitch angle regulation," Renewable Energy, Elsevier, vol. 128(PA), pages 108-124.
    2. Johnson, Samuel C. & Rhodes, Joshua D. & Webber, Michael E., 2020. "Understanding the impact of non-synchronous wind and solar generation on grid stability and identifying mitigation pathways," Applied Energy, Elsevier, vol. 262(C).
    3. Nahid-Al-Masood, & Yan, Ruifeng & Saha, Tapan Kumar, 2015. "A new tool to estimate maximum wind power penetration level: In perspective of frequency response adequacy," Applied Energy, Elsevier, vol. 154(C), pages 209-220.
    4. Quan, Hao & Srinivasan, Dipti & Khambadkone, Ashwin M. & Khosravi, Abbas, 2015. "A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources," Applied Energy, Elsevier, vol. 152(C), pages 71-82.

    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. Velo, R. & Osorio, L. & Fernández, M.D. & Rodríguez, M.R., 2014. "An economic analysis of a stand-alone and grid-connected cattle farm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 883-890.
    2. Kaldellis, J.K., 2011. "Critical evaluation of financial supporting schemes for wind-based projects: Case study Greece," Energy Policy, Elsevier, vol. 39(5), pages 2490-2500, May.
    3. Baringo, L. & Conejo, A.J., 2011. "Wind power investment within a market environment," Applied Energy, Elsevier, vol. 88(9), pages 3239-3247.
    4. Mohandes, M. & Rehman, S. & Rahman, S.M., 2011. "Estimation of wind speed profile using adaptive neuro-fuzzy inference system (ANFIS)," Applied Energy, Elsevier, vol. 88(11), pages 4024-4032.
    5. Ye, Lin & Zhang, Cihang & Xue, Hui & Li, Jiachen & Lu, Peng & Zhao, Yongning, 2019. "Study of assessment on capability of wind power accommodation in regional power grids," Renewable Energy, Elsevier, vol. 133(C), pages 647-662.
    6. Thomas Kleinert & Martin Schmidt, 2023. "Why there is no need to use a big-M in linear bilevel optimization: a computational study of two ready-to-use approaches," Computational Management Science, Springer, vol. 20(1), pages 1-12, December.
    7. Rahmad Syah & Safoura Faghri & Mahyuddin KM Nasution & Afshin Davarpanah & Marek Jaszczur, 2021. "Modeling and Optimization of Wind Turbines in Wind Farms for Solving Multi-Objective Reactive Power Dispatch Using a New Hybrid Scheme," Energies, MDPI, vol. 14(18), pages 1-22, September.
    8. Sun, Bing & Yu, Yixin & Qin, Chao, 2017. "Should China focus on the distributed development of wind and solar photovoltaic power generation? A comparative study," Applied Energy, Elsevier, vol. 185(P1), pages 421-439.
    9. Arjmand, Reza & Rahimiyan, Morteza, 2016. "Statistical analysis of a competitive day-ahead market coupled with correlated wind production and electric load," Applied Energy, Elsevier, vol. 161(C), pages 153-167.
    10. Jadidoleslam, Morteza & Ebrahimi, Akbar & Latify, Mohammad Amin, 2017. "Probabilistic transmission expansion planning to maximize the integration of wind power," Renewable Energy, Elsevier, vol. 114(PB), pages 866-878.
    11. Li, Gong & Shi, Jing, 2010. "On comparing three artificial neural networks for wind speed forecasting," Applied Energy, Elsevier, vol. 87(7), pages 2313-2320, July.
    12. Kaldellis, J.K. & Kapsali, M. & Kavadias, K.A., 2010. "Energy balance analysis of wind-based pumped hydro storage systems in remote island electrical networks," Applied Energy, Elsevier, vol. 87(8), pages 2427-2437, August.
    13. Kaldellis, J.K. & Kapsali, M. & Tiligadas, D., 2012. "Presentation of a stochastic model estimating the wind energy contribution in remote island electrical networks," Applied Energy, Elsevier, vol. 97(C), pages 68-76.
    14. Martinez-Rojas, Marcela & Sumper, Andreas & Gomis-Bellmunt, Oriol & Sudrià-Andreu, Antoni, 2011. "Reactive power dispatch in wind farms using particle swarm optimization technique and feasible solutions search," Applied Energy, Elsevier, vol. 88(12), pages 4678-4686.
    15. Farnoosh, Arash & Lantz, Frederic & Percebois, Jacques, 2014. "Electricity generation analyses in an oil-exporting country: Transition to non-fossil fuel based power units in Saudi Arabia," Energy, Elsevier, vol. 69(C), pages 299-308.
    16. Xydis, G., 2012. "Development of an integrated methodology for the energy needs of a major urban city: The case study of Athens, Greece," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(9), pages 6705-6716.
    17. Dorea Chin & Afzal Siddiqui, 2014. "Capacity expansion and forward contracting in a duopolistic power sector," Computational Management Science, Springer, vol. 11(1), pages 57-86, January.
    18. Kapsali, M. & Anagnostopoulos, J.S. & Kaldellis, J.K., 2012. "Wind powered pumped-hydro storage systems for remote islands: A complete sensitivity analysis based on economic perspectives," Applied Energy, Elsevier, vol. 99(C), pages 430-444.
    19. Papadakis C. Nikolaos & Fafalakis Marios & Katsaprakakis Dimitris, 2023. "A Review of Pumped Hydro Storage Systems," Energies, MDPI, vol. 16(11), pages 1-39, June.
    20. Papaefthymiou, Stefanos V. & Papathanassiou, Stavros A., 2014. "Optimum sizing of wind-pumped-storage hybrid power stations in island systems," Renewable Energy, Elsevier, vol. 64(C), pages 187-196.

    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:appene:v:113:y:2014:i:c:p:648-659. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.