IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v154y2015icp209-220.html
   My bibliography  Save this article

A new tool to estimate maximum wind power penetration level: In perspective of frequency response adequacy

Author

Listed:
  • Nahid-Al-Masood,
  • Yan, Ruifeng
  • Saha, Tapan Kumar

Abstract

Wind energy is becoming a significant source of generation in many countries because of its zero fuel cost and no air pollution. Due to integration of large-scale wind power in conventional grids, synchronous generators are being economically replaced. Modern wind farms are based on power electronics interface; and unlike synchronous generators, they do not have inherent frequency support capability. So, in a combined synchronous and non-synchronous machine based power system, it has always been a concern for a network operator to maintain system frequency within acceptable limits following a major disturbance. From power system security point of view, wind penetration can be limited by frequency response criteria. Up to now, several methodologies have been proposed to estimate maximum threshold of wind integration. However, none of them recommends how a system operator could be immediately informed about a secured wind penetration limit, as soon as generation profile is known. This paper proposes a new estimation tool of maximum wind penetration level from the frequency response adequacy point of view. Available system information viz. inertia and headroom are used as input parameters in the developed tool. Output of this tool will provide the highest margin of wind power that can be integrated at a particular load condition without violating frequency response constraints. The proposed technique is applied and analysed for a 250 bus, 65 machine Australian electricity network.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:154:y:2015:i:c:p:209-220
    DOI: 10.1016/j.apenergy.2015.04.085
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261915005486
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2015.04.085?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. Johnston, Lewis & Díaz-González, Francisco & Gomis-Bellmunt, Oriol & Corchero-García, Cristina & Cruz-Zambrano, Miguel, 2015. "Methodology for the economic optimisation of energy storage systems for frequency support in wind power plants," Applied Energy, Elsevier, vol. 137(C), pages 660-669.
    2. Fikru, Mahelet G. & Gautier, Luis, 2015. "The impact of weather variation on energy consumption in residential houses," Applied Energy, Elsevier, vol. 144(C), pages 19-30.
    3. Waite, Michael & Modi, Vijay, 2014. "Potential for increased wind-generated electricity utilization using heat pumps in urban areas," Applied Energy, Elsevier, vol. 135(C), pages 634-642.
    4. 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.
    5. Gouveia, João Pedro & Dias, Luís & Martins, Inês & Seixas, Júlia, 2014. "Effects of renewables penetration on the security of Portuguese electricity supply," Applied Energy, Elsevier, vol. 123(C), pages 438-447.
    6. Yan, Ruifeng & Saha, Tapan Kumar & Modi, Nilesh & Masood, Nahid-Al & Mosadeghy, Mehdi, 2015. "The combined effects of high penetration of wind and PV on power system frequency response," Applied Energy, Elsevier, vol. 145(C), pages 320-330.
    7. 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.
    8. Chicco, Gianfranco, 2012. "Overview and performance assessment of the clustering methods for electrical load pattern grouping," Energy, Elsevier, vol. 42(1), pages 68-80.
    9. Beccali, M. & Brunone, S. & Finocchiaro, P. & Galletto, J.M., 2013. "Method for size optimisation of large wind–hydrogen systems with high penetration on power grids," Applied Energy, Elsevier, vol. 102(C), pages 534-544.
    10. Purvins, Arturs & Zubaryeva, Alyona & Llorente, Maria & Tzimas, Evangelos & Mercier, Arnaud, 2011. "Challenges and options for a large wind power uptake by the European electricity system," Applied Energy, Elsevier, vol. 88(5), pages 1461-1469, May.
    11. Zúñiga, K.V. & Castilla, I. & Aguilar, R.M., 2014. "Using fuzzy logic to model the behavior of residential electrical utility customers," Applied Energy, Elsevier, vol. 115(C), pages 384-393.
    12. Kaneko, Toshiaki & Uehara, Akie & Senjyu, Tomonobu & Yona, Atsushi & Urasaki, Naomitsu, 2011. "An integrated control method for a wind farm to reduce frequency deviations in a small power system," Applied Energy, Elsevier, vol. 88(4), pages 1049-1058, April.
    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. 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.
    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. Kumar, Dipesh & Chatterjee, Kalyan, 2016. "A review of conventional and advanced MPPT algorithms for wind energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 957-970.
    4. Zou, Peng & Chen, Qixin & Yu, Yang & Xia, Qing & Kang, Chongqing, 2017. "Electricity markets evolution with the changing generation mix: An empirical analysis based on China 2050 High Renewable Energy Penetration Roadmap," Applied Energy, Elsevier, vol. 185(P1), pages 56-67.
    5. Paweł Piotrowski & Marcin Kopyt & Dariusz Baczyński & Sylwester Robak & Tomasz Gulczyński, 2021. "Hybrid and Ensemble Methods of Two Days Ahead Forecasts of Electric Energy Production in a Small Wind Turbine," Energies, MDPI, vol. 14(5), pages 1-25, February.
    6. 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.
    7. Mengqi Qing & Fei Tang & Fusuo Liu & Dichen Liu & Nianchun Du & Benxi Hu, 2020. "An Analytical Method for Estimating the Maximum Penetration of DFIG Considering Frequency Stability," Sustainability, MDPI, vol. 12(23), pages 1-21, November.
    8. Seneviratne, Chinthaka & Ozansoy, C., 2016. "Frequency response due to a large generator loss with the increasing penetration of wind/PV generation – A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 659-668.
    9. Devlin, Joseph & Li, Kang & Higgins, Paraic & Foley, Aoife, 2016. "The importance of gas infrastructure in power systems with high wind power penetrations," Applied Energy, Elsevier, vol. 167(C), pages 294-304.

    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. 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.
    2. Koltsaklis, Nikolaos E. & Georgiadis, Michael C., 2015. "A multi-period, multi-regional generation expansion planning model incorporating unit commitment constraints," Applied Energy, Elsevier, vol. 158(C), pages 310-331.
    3. Stringer, Naomi & Haghdadi, Navid & Bruce, Anna & Riesz, Jenny. & MacGill, Iain, 2020. "Observed behavior of distributed photovoltaic systems during major voltage disturbances and implications for power system security," Applied Energy, Elsevier, vol. 260(C).
    4. Drouineau, Mathilde & Maïzi, Nadia & Mazauric, Vincent, 2014. "Impacts of intermittent sources on the quality of power supply: The key role of reliability indicators," Applied Energy, Elsevier, vol. 116(C), pages 333-343.
    5. 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.
    6. Lakshmanan, Venkatachalam & Marinelli, Mattia & Hu, Junjie & Bindner, Henrik W., 2016. "Provision of secondary frequency control via demand response activation on thermostatically controlled loads: Solutions and experiences from Denmark," Applied Energy, Elsevier, vol. 173(C), pages 470-480.
    7. Cabrera-Tobar, Ana & Bullich-Massagué, Eduard & Aragüés-Peñalba, Mònica & Gomis-Bellmunt, Oriol, 2016. "Review of advanced grid requirements for the integration of large scale photovoltaic power plants in the transmission system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 971-987.
    8. Chen, Han & Huang, Ye & Shen, Huizhong & Chen, Yilin & Ru, Muye & Chen, Yuanchen & Lin, Nan & Su, Shu & Zhuo, Shaojie & Zhong, Qirui & Wang, Xilong & Liu, Junfeng & Li, Bengang & Tao, Shu, 2016. "Modeling temporal variations in global residential energy consumption and pollutant emissions," Applied Energy, Elsevier, vol. 184(C), pages 820-829.
    9. Blarke, Morten B., 2012. "Towards an intermittency-friendly energy system: Comparing electric boilers and heat pumps in distributed cogeneration," Applied Energy, Elsevier, vol. 91(1), pages 349-365.
    10. Xavier Serrano-Guerrero & Guillermo Escrivá-Escrivá & Santiago Luna-Romero & Jean-Michel Clairand, 2020. "A Time-Series Treatment Method to Obtain Electrical Consumption Patterns for Anomalies Detection Improvement in Electrical Consumption Profiles," Energies, MDPI, vol. 13(5), pages 1-23, February.
    11. Leung, Philip C.M. & Lee, Eric W.M., 2013. "Estimation of electrical power consumption in subway station design by intelligent approach," Applied Energy, Elsevier, vol. 101(C), pages 634-643.
    12. Karamanev, Dimitre & Pupkevich, Victor & Penev, Kalin & Glibin, Vassili & Gohil, Jay & Vajihinejad, Vahid, 2017. "Biological conversion of hydrogen to electricity for energy storage," Energy, Elsevier, vol. 129(C), pages 237-245.
    13. Tubagus Aryandi Gunawan & Alessandro Singlitico & Paul Blount & James Burchill & James G. Carton & Rory F. D. Monaghan, 2020. "At What Cost Can Renewable Hydrogen Offset Fossil Fuel Use in Ireland’s Gas Network?," Energies, MDPI, vol. 13(7), pages 1-23, April.
    14. Lan, Hai & Wen, Shuli & Hong, Ying-Yi & Yu, David C. & Zhang, Lijun, 2015. "Optimal sizing of hybrid PV/diesel/battery in ship power system," Applied Energy, Elsevier, vol. 158(C), pages 26-34.
    15. Fulin Fan & Giorgio Zorzi & David Campos-Gaona & Graeme Burt & Olimpo Anaya-Lara & John Nwobu & Ander Madariaga, 2021. "Sizing and Coordination Strategies of Battery Energy Storage System Co-Located with Wind Farm: The UK Perspective," Energies, MDPI, vol. 14(5), pages 1-21, March.
    16. 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.
    17. Zhou, Kaile & Yang, Changhui & Shen, Jianxin, 2017. "Discovering residential electricity consumption patterns through smart-meter data mining: A case study from China," Utilities Policy, Elsevier, vol. 44(C), pages 73-84.
    18. Sadeghianpourhamami, N. & Demeester, T. & Benoit, D.F. & Strobbe, M. & Develder, C., 2016. "Modeling and analysis of residential flexibility: Timing of white good usage," Applied Energy, Elsevier, vol. 179(C), pages 790-805.
    19. Huang, Jinbo & Li, Zhigang & Wu, Q.H., 2017. "Coordinated dispatch of electric power and district heating networks: A decentralized solution using optimality condition decomposition," Applied Energy, Elsevier, vol. 206(C), pages 1508-1522.
    20. Capozzoli, Alfonso & Piscitelli, Marco Savino & Brandi, Silvio & Grassi, Daniele & Chicco, Gianfranco, 2018. "Automated load pattern learning and anomaly detection for enhancing energy management in smart buildings," Energy, Elsevier, vol. 157(C), pages 336-352.

    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:154:y:2015:i:c:p:209-220. 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.