Hydropower System Operation and the Quality of Short-Term Hydrologic Ensemble Forecasts
Publication: Journal of Water Resources Planning and Management
Volume 149, Issue 5
Abstract
Improving the operational effectiveness of hydropower systems is becoming more relevant considering the shift to renewable energy sources and the rising social, financial, and environmental costs associated with the construction of new hydropower facilities. This challenge is interdisciplinary as it involves technical, managerial, and institutional aspects. This paper focuses on a technical aspect, more specifically on the relationship between the quality of short-term ensemble streamflow forecasts and the energy produced by a hydropower system. A secondary objective is to measure the contribution of both the meteorological and structural uncertainties on the energy output. To achieve this, a numerical experiment comprising multiple sets of hydrologic ensemble forecasts of different quality and a suite of reservoir optimization models is developed for a case study in Canada (the hydropower system of the Gatineau River basin). These ensemble forecasts are processed by the short-term reservoir operation model in rolling-horizon mode over a planning period of 6 years. Each day, the short-term optimization model seeks to maximize the energy output over the 14-day forecast lead time considering the expected future value of the system derived from a midterm optimization model. The relationship between hydropower generation and common statistical scores characterizing the ensemble forecasts indicates that although there is a link between the quality of the forecasts and the energy production, it is not a one-to-one causal relationship. Our results also show that the diversity of hydrological models is beneficial to the production of energy, indicating that the diversity of model structures compensates the deficiencies of individuals models and adds value to the forecast.
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Data Availability Statement
Some of the tools and data supporting this study’s findings are open to the public. The HOOPLA toolbox is available in a GitHub repository (https://github.com/AntoineThiboult/HOOPLA). ECMWF meteorological forecasts used in this study can be obtained freely from the TIGGE data portal (htpps://apps.ecmwf.int). The observed hydrometeorological datasets are publicly available at Hydro-Quebec’s website (https://www.hydroquebec.com/production/debits-niveaux-eau.html?). The codes for the short-term and midterm optimization models are available from the corresponding author upon reasonable request. The physical characteristics of hydropower plants are not publicly available as they belong to Hydro-Quebec.
Acknowledgments
The authors acknowledge the financial support of the NSERC Strategic Network FLOODNET.
Author contributions: Michael Osina contributed to the formal analysis, writing of the original draft, visualization, and software. Amaury Tilmant contributed to the conceptualization, methodology, software, validation, review of the writing, supervision, funding acquisition, and project administration. Emixi Valdez contributed to the data curation, formal analysis, software, and review of the writing. Francois Anctil contributed to the conceptualization, methodology, validation, review of the writing, supervision, and funding acquisition. Maria-Helena Ramos contributed to the methodology, validation, and review of the writing.
Disclaimer
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of Hydro-Quebec.
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Journal of Water Resources Planning and Management
Volume 149 • Issue 5 • May 2023
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© 2023 American Society of Civil Engineers.
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Received: Oct 22, 2021
Accepted: Dec 21, 2022
Published online: Mar 13, 2023
Published in print: May 1, 2023
Discussion open until: Aug 13, 2023
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