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Optimal operation of cascade hydropower stations using hydrogen as storage medium

Author

Listed:
  • Lu, Di
  • Wang, Bende
  • Wang, Yaodong
  • Zhou, Huicheng
  • Liang, Qiuhua
  • Peng, Yong
  • Roskilly, Tony

Abstract

The use of forecast information for cascade hydropower stations is one of the effective ways to increase the electricity generation reliability and economic benefit. However, the uncertainty of forecast is high when the forecast horizon is long. It is a common practice for hydropower stations to abandon water during flood seasons due to the limited capacity of the associated reservoirs. If forecast is accurate, the stored water can be discharged early before the flood peak arrives. This would effectively reduce the amount of water being abandoned and increase electricity generation. But there is a risk that the water stored in reservoirs would become less than expected if the forecast fails or in dry periods. In order to reduce the negative impact of forecast uncertainty, hydrogen production and storage as energy harvested by electrolysis of water using the electricity from the cascade hydropower stations is proposed and used in this study. Hun River cascade hydropower stations in China are selected as a case study. By integrating ten-day inflow forecast with hedging rule curves (HRCs-TDIF), the feasibility of optimal operation of cascade hydropower stations using hydrogen as energy storage is analyzed. Hedging rules curves of hydrogen production (HRCs-HP) is established for analyzing the relationship between electricity generation reliability (EGR) of the cascade hydropower stations and equipment utilization (EU) of hydrogen production under different equipment scales (ES). The results show that the proposed methods for the selected cascade hydropower stations may lead to high EGR and less water being abandoned.

Suggested Citation

  • Lu, Di & Wang, Bende & Wang, Yaodong & Zhou, Huicheng & Liang, Qiuhua & Peng, Yong & Roskilly, Tony, 2015. "Optimal operation of cascade hydropower stations using hydrogen as storage medium," Applied Energy, Elsevier, vol. 137(C), pages 56-63.
    • Handle: RePEc:eee:appene:v:137:y:2015:i:c:p:56-63
    DOI: 10.1016/j.apenergy.2014.09.092
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    2. Liu, Hailiang & Brown, Tom & Andresen, Gorm Bruun & Schlachtberger, David P. & Greiner, Martin, 2019. "The role of hydro power, storage and transmission in the decarbonization of the Chinese power system," Applied Energy, Elsevier, vol. 239(C), pages 1308-1321.
    3. Jiang, Zhiqiang & Ji, Changming & Qin, Hui & Feng, Zhongkai, 2018. "Multi-stage progressive optimality algorithm and its application in energy storage operation chart optimization of cascade reservoirs," Energy, Elsevier, vol. 148(C), pages 309-323.
    4. Mikovits, Christian & Wetterlund, Elisabeth & Wehrle, Sebastian & Baumgartner, Johann & Schmidt, Johannes, 2021. "Stronger together: Multi-annual variability of hydrogen production supported by wind power in Sweden," Applied Energy, Elsevier, vol. 282(PB).
    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. Zhiqiang Jiang & Yaqi Qiao & Yuyun Chen & Changming Ji, 2018. "A New Reservoir Operation Chart Drawing Method Based on Dynamic Programming," Energies, MDPI, vol. 11(12), pages 1-17, November.
    7. Dragomir, George & Șerban, Alexandru & Năstase, Gabriel & Brezeanu, Alin Ionuț, 2016. "Wind energy in Romania: A review from 2009 to 2016," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 129-143.
    8. Zhou, Yanlai & Guo, Shenglian & Chang, Fi-John & Xu, Chong-Yu, 2018. "Boosting hydropower output of mega cascade reservoirs using an evolutionary algorithm with successive approximation," Applied Energy, Elsevier, vol. 228(C), pages 1726-1739.
    9. Ghandehariun, S. & Wang, Z. & Naterer, G.F. & Rosen, M.A., 2015. "Experimental investigation of molten salt droplet quenching and solidification processes of heat recovery in thermochemical hydrogen production," Applied Energy, Elsevier, vol. 157(C), pages 267-275.
    10. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian & Liao, Sheng-li, 2017. "Hydropower system operation optimization by discrete differential dynamic programming based on orthogonal experiment design," Energy, Elsevier, vol. 126(C), pages 720-732.
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    12. Chen, Zi & Guo, Wencheng, 2023. "Stability and dynamic response of two-stage hydropower stations cascaded by regulating reservoir," Renewable Energy, Elsevier, vol. 202(C), pages 651-666.

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