GSTDTAP  > 资源环境科学
DOI10.1002/2016WR020180
Deriving adaptive operating rules of hydropower reservoirs using time-varying parameters generated by the EnKF
Feng, Maoyuan1,2; Liu, Pan1,2; Guo, Shenglian1,2; Shi, Liangsheng1; Deng, Chao1,2; Ming, Bo1,2
2017-08-01
发表期刊WATER RESOURCES RESEARCH
ISSN0043-1397
EISSN1944-7973
出版年2017
卷号53期号:8
文章类型Article
语种英语
国家Peoples R China
英文摘要

Operating rules have been used widely to decide reservoir operations because of their capacity for coping with uncertain inflow. However, stationary operating rules lack adaptability; thus, under changing environmental conditions, they cause inefficient reservoir operation. This paper derives adaptive operating rules based on time-varying parameters generated using the ensemble Kalman filter (EnKF). A deterministic optimization model is established to obtain optimal water releases, which are further taken as observations of the reservoir simulation model. The EnKF is formulated to update the operating rules sequentially, providing a series of time-varying parameters. To identify the index that dominates the variations of the operating rules, three hydrologic factors are selected: the reservoir inflow, ratio of future inflow to current available water, and available water. Finally, adaptive operating rules are derived by fitting the time-varying parameters with the identified dominant hydrologic factor. China's Three Gorges Reservoir was selected as a case study. Results show that (1) the EnKF has the capability of capturing the variations of the operating rules, (2) reservoir inflow is the factor that dominates the variations of the operating rules, and (3) the derived adaptive operating rules are effective in improving hydropower benefits compared with stationary operating rules. The insightful findings of this study could be used to help adapt reservoir operations to mitigate the effects of changing environmental conditions.


英文关键词reservoir operation adaptive operating rules EnKF time-varying parameters
领域资源环境
收录类别SCI-E
WOS记录号WOS:000411202000030
WOS关键词ENSEMBLE KALMAN FILTER ; DATA ASSIMILATION ; CLIMATIC-CHANGE ; MANN-KENDALL ; SYSTEM ; UNCERTAINTY ; VARIABILITY ; ALGORITHM ; IMPACTS ; INFLOW
WOS类目Environmental Sciences ; Limnology ; Water Resources
WOS研究方向Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources
引用统计
被引频次:42[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/21302
专题资源环境科学
作者单位1.Wuhan Univ, State Key Lab Water Resources & Hydropower Engn, Wuhan, Hubei, Peoples R China;
2.Hubei Prov Collaborat Innovat Ctr Water Resources, Wuhan, Hubei, Peoples R China
推荐引用方式
GB/T 7714
Feng, Maoyuan,Liu, Pan,Guo, Shenglian,et al. Deriving adaptive operating rules of hydropower reservoirs using time-varying parameters generated by the EnKF[J]. WATER RESOURCES RESEARCH,2017,53(8).
APA Feng, Maoyuan,Liu, Pan,Guo, Shenglian,Shi, Liangsheng,Deng, Chao,&Ming, Bo.(2017).Deriving adaptive operating rules of hydropower reservoirs using time-varying parameters generated by the EnKF.WATER RESOURCES RESEARCH,53(8).
MLA Feng, Maoyuan,et al."Deriving adaptive operating rules of hydropower reservoirs using time-varying parameters generated by the EnKF".WATER RESOURCES RESEARCH 53.8(2017).
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