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

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  • 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
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    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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).
    6. 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).
    7. 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.
    8. 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.
    9. 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.
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    1. 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).
    2. 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).
    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).

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