IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v175y2021icp153-166.html
   My bibliography  Save this article

Multiscale power fluctuation evaluation of a hydro-wind-photovoltaic system

Author

Listed:
  • Xiong, Hualin
  • Xu, Beibei
  • Kheav, Kimleng
  • Luo, Xingqi
  • Zhang, Xingjin
  • Patelli, Edoardo
  • Guo, Pengcheng
  • Chen, Diyi

Abstract

The hybrid energy systems are required to operate stably in different time scales. Previous studies on the stability are carried out under the unrealistic assumption of discontinuous time scales. Therefore, a second time scale model for the hybrid energy systems is presented in this study. To overcome the possible uncertainty caused by the discontinuous time scale assumption, a new method is introduced to analyze power fluctuations for the hybrid power system considering the hydroelectric power station (HPS) and PV-wind complementarity. Compared with traditional statistics, the proposed three indices, discussed in terms of variation frequency, have the ability to show the stability and complementarity characteristics of the hybrid system with the time scale varying from second to hour, The results show that the volatility of wind power and photoelectric increase with the increase of time scale. In (100, 102) seconds, the HPS could not compensate for as they do not meet flexibility demand in that particular frequency domain, and hydro-electric power is able to compensate wind and PV power sources well when the time scale is over 102 s. The obtained stability evolution law has important reference significance for the subsequent studies on the stability of hybrid energy systems.

Suggested Citation

  • Xiong, Hualin & Xu, Beibei & Kheav, Kimleng & Luo, Xingqi & Zhang, Xingjin & Patelli, Edoardo & Guo, Pengcheng & Chen, Diyi, 2021. "Multiscale power fluctuation evaluation of a hydro-wind-photovoltaic system," Renewable Energy, Elsevier, vol. 175(C), pages 153-166.
  • Handle: RePEc:eee:renene:v:175:y:2021:i:c:p:153-166
    DOI: 10.1016/j.renene.2021.04.095
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148121006157
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2021.04.095?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. Lamedica, Regina & Santini, Ezio & Ruvio, Alessandro & Palagi, Laura & Rossetta, Irene, 2018. "A MILP methodology to optimize sizing of PV - Wind renewable energy systems," Energy, Elsevier, vol. 165(PB), pages 385-398.
    2. Mak, Davye & Choeum, Daranith & Choi, Dae-Hyun, 2020. "Sensitivity analysis of volt-VAR optimization to data changes in distribution networks with distributed energy resources," Applied Energy, Elsevier, vol. 261(C).
    3. P. Pinson, 2012. "Very-short-term probabilistic forecasting of wind power with generalized logit–normal distributions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 61(4), pages 555-576, August.
    4. Dongxiao Niu & Hao Zhen & Min Yu & Keke Wang & Lijie Sun & Xiaomin Xu, 2020. "Prioritization of Renewable Energy Alternatives for China by Using a Hybrid FMCDM Methodology with Uncertain Information," Sustainability, MDPI, vol. 12(11), pages 1-26, June.
    5. Sebastian Sterl & Inne Vanderkelen & Celray James Chawanda & Daniel Russo & Robert J. Brecha & Ann Griensven & Nicole P. M. Lipzig & Wim Thiery, 2020. "Smart renewable electricity portfolios in West Africa," Nature Sustainability, Nature, vol. 3(9), pages 710-719, September.
    6. Xilin Zhao & Jingjing He & Bo Fu & Li He & Guanghui Xu, 2018. "A System Compensation Based Model Predictive AGC Method for Multiarea Interconnected Power Systems with High Penetration of PV System and Random Time Delay between Different Areas," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-10, October.
    7. Sun, Longgang & Guo, Pengcheng & Luo, Xingqi, 2020. "Numerical investigation on inter-blade cavitation vortex in a Franics turbine," Renewable Energy, Elsevier, vol. 158(C), pages 64-74.
    8. dos Santos Neto, Pedro J. & Barros, Tárcio A.S. & Silveira, Joao P.C. & Ruppert Filho, Ernesto & Vasquez, Juan C. & Guerrero, Josep M., 2020. "Power management techniques for grid-connected DC microgrids: A comparative evaluation," Applied Energy, Elsevier, vol. 269(C).
    9. Kheshti, Mostafa & Ding, Lei & Nayeripour, Majid & Wang, Xiaowei & Terzija, Vladimir, 2019. "Active power support of wind turbines for grid frequency events using a reliable power reference scheme," Renewable Energy, Elsevier, vol. 139(C), pages 1241-1254.
    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. Feio, Andrey Dias & da Silva, Flávio Castro & Teixeira, Marcos Alexandre & Lopes Maria, Ana Caroline & da Silva, Gabriel Brazo Sabino, 2024. "Viability of renewable energy integration in isolated systems in Brazil – A case study at Trindade Island (Espírito Santo, Brazil)," Renewable Energy, Elsevier, vol. 222(C).
    2. Jin, Xiaoyu & Liu, Benxi & Liao, Shengli & Cheng, Chuntian & Jurasz, Jakub & Zhang, Yi & Lu, Jia, 2023. "Exploring the transition role of cascade hydropower in 100% decarbonized energy systems," Energy, Elsevier, vol. 279(C).
    3. Jia, Rui & He, Mengjiao & Zhang, Xinyu & Zhao, Ziwen & Han, Shuo & Jurasz, Jakub & Chen, Diyi & Xu, Beibei, 2022. "Optimal operation of cascade hydro-wind-photovoltaic complementary generation system with vibration avoidance strategy," Applied Energy, Elsevier, vol. 324(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. Fouad Boutros & Moustapha Doumiati & Jean-Christophe Olivier & Imad Mougharbel & Hadi Kanaan, 2024. "Optimal Placement of Multiple Sources in a Mesh-Type DC Microgrid Using Dijkstra’s Algorithm," Energies, MDPI, vol. 17(14), pages 1-18, July.
    2. Shi, Ruifeng & Li, Shaopeng & Zhang, Penghui & Lee, Kwang Y., 2020. "Integration of renewable energy sources and electric vehicles in V2G network with adjustable robust optimization," Renewable Energy, Elsevier, vol. 153(C), pages 1067-1080.
    3. Akhlaque Ahmad Khan & Ahmad Faiz Minai & Rupendra Kumar Pachauri & Hasmat Malik, 2022. "Optimal Sizing, Control, and Management Strategies for Hybrid Renewable Energy Systems: A Comprehensive Review," Energies, MDPI, vol. 15(17), pages 1-29, August.
    4. Zhang, Tong & Burke, Paul J. & Wang, Qi, 2024. "Effectiveness of electric vehicle subsidies in China: A three-dimensional panel study," Resource and Energy Economics, Elsevier, vol. 76(C).
    5. Wang, Huaizhi & Liu, Yangyang & Zhou, Bin & Voropai, Nikolai & Cao, Guangzhong & Jia, Youwei & Barakhtenko, Evgeny, 2020. "Advanced adaptive frequency support scheme for DFIG under cyber uncertainty," Renewable Energy, Elsevier, vol. 161(C), pages 98-109.
    6. Kheshti, Mostafa & Zhao, Xiaowei & Liang, Ting & Nie, Binjian & Ding, Yulong & Greaves, Deborah, 2022. "Liquid air energy storage for ancillary services in an integrated hybrid renewable system," Renewable Energy, Elsevier, vol. 199(C), pages 298-307.
    7. Wen, Honglin & Pinson, Pierre & Gu, Jie & Jin, Zhijian, 2024. "Wind energy forecasting with missing values within a fully conditional specification framework," International Journal of Forecasting, Elsevier, vol. 40(1), pages 77-95.
    8. Shen, Feifei & Zhao, Liang & Du, Wenli & Zhong, Weimin & Qian, Feng, 2020. "Large-scale industrial energy systems optimization under uncertainty: A data-driven robust optimization approach," Applied Energy, Elsevier, vol. 259(C).
    9. Sun, Longgang & Xu, Hongyang & Li, Chenxi & Guo, Pengcheng & Xu, Zhuofei, 2024. "Unsteady assessment and alleviation of inter-blade vortex in Francis turbine," Applied Energy, Elsevier, vol. 358(C).
    10. Croonenbroeck, Carsten & Møller Dahl, Christian, 2014. "Accurate medium-term wind power forecasting in a censored classification framework," Discussion Papers 351, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
    11. Talieh Abdolkhaninezhad & Masoud Monavari & Nematollah Khorasani & Maryam Robati & Forogh Farsad, 2022. "Analysis Indicators of Health-Safety in the Risk Assessment of Landfill with the Combined Method of Fuzzy Multi-Criteria Decision Making and Bow Tie Model," Sustainability, MDPI, vol. 14(22), pages 1-24, November.
    12. Antonio Bracale & Pasquale De Falco, 2015. "An Advanced Bayesian Method for Short-Term Probabilistic Forecasting of the Generation of Wind Power," Energies, MDPI, vol. 8(9), pages 1-22, September.
    13. Croonenbroeck, Carsten & Stadtmann, Georg, 2015. "Minimizing asymmetric loss in medium-term wind power forecasting," Renewable Energy, Elsevier, vol. 81(C), pages 197-208.
    14. repec:hum:wpaper:sfb649dp2015-026 is not listed on IDEAS
    15. Abu Reza Md. Towfiqul Islam & Md. Mijanur Rahman Bappi & Saeed Alqadhi & Ahmed Ali Bindajam & Javed Mallick & Swapan Talukdar, 2023. "Improvement of flood susceptibility mapping by introducing hybrid ensemble learning algorithms and high-resolution satellite imageries," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 119(1), pages 1-37, October.
    16. Sun, Mucun & Feng, Cong & Zhang, Jie, 2020. "Multi-distribution ensemble probabilistic wind power forecasting," Renewable Energy, Elsevier, vol. 148(C), pages 135-149.
    17. Wang, Yun & Chen, Tuo & Zou, Runmin & Song, Dongran & Zhang, Fan & Zhang, Lingjun, 2022. "Ensemble probabilistic wind power forecasting with multi-scale features," Renewable Energy, Elsevier, vol. 201(P1), pages 734-751.
    18. Geng, Xinmin & Zhou, Ye & Zhao, Weiqiang & Shi, Li & Chen, Diyi & Bi, Xiaojian & Xu, Beibei, 2024. "Pricing ancillary service of a Francis hydroelectric generating system to promote renewable energy integration in a clean energy base: Tariff compensation of deep peak regulation," Renewable Energy, Elsevier, vol. 226(C).
    19. Kan, Kan & Binama, Maxime & Chen, Huixiang & Zheng, Yuan & Zhou, Daqing & Su, Wentao & Muhirwa, Alexis, 2022. "Pump as turbine cavitation performance for both conventional and reverse operating modes: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    20. Kumar, Prashant & Singal, S.K. & Gohil, Pankaj P., 2024. "A technical review on combined effect of cavitation and silt erosion on Francis turbine," Renewable and Sustainable Energy Reviews, Elsevier, vol. 190(PB).
    21. Jin, Faye & Luo, Yongyao & Zhao, Qiang & Cao, Jiali & Wang, Zhengwei, 2023. "Energy loss analysis of transition simulation for a prototype reversible pump turbine during load rejection process," Energy, Elsevier, vol. 284(C).

    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:175:y:2021:i:c:p:153-166. 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.