Optimal operation of cascade hydropower stations using hydrogen as storage medium

Di Lu, Bende Wang, Yaodong Wang, Huicheng Zhou, Qiuhua Liang, Yong Peng and Tony Roskilly

Applied Energy, 2015, vol. 137, issue C, 56-63

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.

Keywords: Cascade hydropower stations; Abandoned water; Integrating ten-day inflow forecast; Hedging rule curves; Hydrogen production and storage (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (13)

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DOI: 10.1016/j.apenergy.2014.09.092

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