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A power market-based operation support model for sub-daily hydropower regulation practices

Author

Listed:
  • Torabi Haghighi, Ali
  • Ashraf, Faisal Bin
  • Riml, Joakim
  • Koskela, Jarkko
  • Kløve, Bjørn
  • Marttila, Hannu

Abstract

With increasing power production from renewable energy sources, sub-daily variations in energy demand need to be balanced. Today, hydropower is commonly used as balancing power. In this study, we quantified the impact of capacity constraints, in terms of reservoir volume and hydropower capacity, on the potential to comply with instant energy demand. To evaluate the impact, we developed two new metrics, power market impact and system efficiency ratio, which are based on two threshold flow regimes derived from natural flow as lower threshold release and regulated flow (based on hourly energy prices) as upper threshold release. The operation support model comprises 96 different regulation scenarios based on varying combinations of hydropower and reservoir capacities. For each scenario, an hourly water balance was simulated, to obtain the highest complying with upper threshold release based on actual energy demand. We tested the framework on the Kemijoki river with defined thresholds based on the natural flow regime (tributary river Ounasjoki) and the hourly energy price in Finland in 2017, and estimated the impact of regulation on hourly flow regime at the Taivalkoski hydropower station. The annual flow regime impact in 2013, 2014 and 2015 was estimated to be 74%, 84% and 61%, respectively, while the monthly impact varied from 27% to 100%. Our framework for evaluating interactions between the power market and sub-daily regulation practices is a useful novel tool for sustainable river management and can be easily applied to different rivers and regions and evaluated for different timescales.

Suggested Citation

  • Torabi Haghighi, Ali & Ashraf, Faisal Bin & Riml, Joakim & Koskela, Jarkko & Kløve, Bjørn & Marttila, Hannu, 2019. "A power market-based operation support model for sub-daily hydropower regulation practices," Applied Energy, Elsevier, vol. 255(C).
    • Handle: RePEc:eee:appene:v:255:y:2019:i:c:s0306261919315922
    DOI: 10.1016/j.apenergy.2019.113905
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    Citations

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    Cited by:

    1. Koh, Rachel & Kern, Jordan & Galelli, Stefano, 2022. "Hard-coupling water and power system models increases the complementarity of renewable energy sources," Applied Energy, Elsevier, vol. 321(C).
    2. Yongxiu He & Meiyan Wang & Fengtao Guang, 2019. "Applicability Evaluation of China’s Retail Electricity Price Package Combining Data Envelopment Analysis and a Cloud Model," Energies, MDPI, vol. 13(1), pages 1-21, December.
    3. Zhou, Yuzhou & Zhao, Jiexing & Zhai, Qiaozhu, 2021. "100% renewable energy: A multi-stage robust scheduling approach for cascade hydropower system with wind and photovoltaic power," Applied Energy, Elsevier, vol. 301(C).
    4. Hatamkhani, Amir & Moridi, Ali & Haghighi, Ali Torabi, 2023. "Incorporating ecosystem services value into the optimal development of hydropower projects," Renewable Energy, Elsevier, vol. 203(C), pages 495-505.
    5. Tayerani Charmchi, Amir Saman & Ifaei, Pouya & Yoo, ChangKyoo, 2021. "Smart supply-side management of optimal hydro reservoirs using the water/energy nexus concept: A hydropower pinch analysis," Applied Energy, Elsevier, vol. 281(C).
    6. Ruokamo, Enni & Juutinen, Artti & Ashraf, Faisal Bin & Haghighi, Ali Torabi & Hellsten, Seppo & Huuki, Hannu & Karhinen, Santtu & Kopsakangas-Savolainen, Maria & Marttila, Hannu & Pongracz, Eva & Roma, 2024. "Estimating the economic value of hydropeaking externalities in regulated rivers," Applied Energy, Elsevier, vol. 353(PA).
    7. Changhun Jeong & Roshan Sharma, 2022. "Tuning Model Predictive Control for Rigorous Operation of the Dalsfoss Hydropower Plant," Energies, MDPI, vol. 15(22), pages 1-11, November.

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