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Complementarity modeling of monthly streamflow and wind speed regimes based on a copula-entropy approach: A Brazilian case study

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  • Ávila R., Leandro
  • Mine, Miriam R.M.
  • Kaviski, Eloy
  • Detzel, Daniel H.M.
  • Fill, Heinz D.
  • Bessa, Marcelo R.
  • Pereira, Guilherme A.A.

Abstract

Wind power energy has been showing significant growth in installed capacity around the world. This opportunity presents big challenges to operate power systems with high wind power penetration levels, considering the variability and intermittent behavior of this type of power source. To reduce uncertainties associated with this kind of power systems, researchers have explored the integration of wind power energy with other renewable energy sources, like solar and hydropower. For instance, the integration of wind and hydro systems can deal with the spatial and temporal complementarity of hydrological and wind regimes to produce energy. Therefore, it is necessary to consider the stochastic behavior and the dependence structures between these variables to define better operational policies. This study explores the spatial correlation of hydrological and wind regimes in different regions of Brazil and defines an entropy-copula-based model for the joint simulation of monthly streamflow and wind speed time series to evaluate the potential integration of hydro and wind energy sources. The proposed model showed a good adherence to the periodic behavior for both variables, and the results indicate that simulated scenarios preserved statistical features of historical data.

Suggested Citation

  • Ávila R., Leandro & Mine, Miriam R.M. & Kaviski, Eloy & Detzel, Daniel H.M. & Fill, Heinz D. & Bessa, Marcelo R. & Pereira, Guilherme A.A., 2020. "Complementarity modeling of monthly streamflow and wind speed regimes based on a copula-entropy approach: A Brazilian case study," Applied Energy, Elsevier, vol. 259(C).
  • Handle: RePEc:eee:appene:v:259:y:2020:i:c:s0306261919318148
    DOI: 10.1016/j.apenergy.2019.114127
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    1. Yonas Gebeyehu Tesfaye & Paul L. Anderson & Mark M. Meerschaert, 2011. "Asymptotic results for Fourier‐PARMA time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(2), pages 157-174, March.
    2. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
    3. Denault, Michel & Dupuis, Debbie & Couture-Cardinal, Sébastien, 2009. "Complementarity of hydro and wind power: Improving the risk profile of energy inflows," Energy Policy, Elsevier, vol. 37(12), pages 5376-5384, December.
    4. Zhao, Haoran & Wu, Qiuwei & Hu, Shuju & Xu, Honghua & Rasmussen, Claus Nygaard, 2015. "Review of energy storage system for wind power integration support," Applied Energy, Elsevier, vol. 137(C), pages 545-553.
    5. Brechmann, Eike C. & Hendrich, Katharina & Czado, Claudia, 2013. "Conditional copula simulation for systemic risk stress testing," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 722-732.
    6. Kevin E. Trenberth & Aiguo Dai & Gerard van der Schrier & Philip D. Jones & Jonathan Barichivich & Keith R. Briffa & Justin Sheffield, 2014. "Global warming and changes in drought," Nature Climate Change, Nature, vol. 4(1), pages 17-22, January.
    7. Prasad, Abhnil A. & Taylor, Robert A. & Kay, Merlinde, 2017. "Assessment of solar and wind resource synergy in Australia," Applied Energy, Elsevier, vol. 190(C), pages 354-367.
    8. Radu, David & Berger, Mathias & Fonteneau, Raphaël & Hardy, Simon & Fettweis, Xavier & Le Du, Marc & Panciatici, Patrick & Balea, Lucian & Ernst, Damien, 2019. "Complementarity assessment of south Greenland katabatic flows and West Europe wind regimes," Energy, Elsevier, vol. 175(C), pages 393-401.
    9. Xu, Jiuping & Wang, Fengjuan & Lv, Chengwei & Huang, Qian & Xie, Heping, 2018. "Economic-environmental equilibrium based optimal scheduling strategy towards wind-solar-thermal power generation system under limited resources," Applied Energy, Elsevier, vol. 231(C), pages 355-371.
    10. Cantão, Mauricio P. & Bessa, Marcelo R. & Bettega, Renê & Detzel, Daniel H.M. & Lima, João M., 2017. "Evaluation of hydro-wind complementarity in the Brazilian territory by means of correlation maps," Renewable Energy, Elsevier, vol. 101(C), pages 1215-1225.
    11. Ren, Guorui & Liu, Jinfu & Wan, Jie & Guo, Yufeng & Yu, Daren, 2017. "Overview of wind power intermittency: Impacts, measurements, and mitigation solutions," Applied Energy, Elsevier, vol. 204(C), pages 47-65.
    12. Erhardt, Tobias Michael & Czado, Claudia & Schepsmeier, Ulf, 2015. "Spatial composite likelihood inference using local C-vines," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 74-88.
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