the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 Jan 2024
Modeling hydropower operations at the scale of a power grid: a demand-based approach
Abstract. Climate change and evolving water management practices may have a profound impact on hydropower generation. While hydrological models have been widely used to assess these effects, they often present some limitations. A major challenge lies in the modeling of release decisions for hydropower reservoirs, which result from intricate trade-offs, involving power sector dispatch, competing water uses and the spatial allocation of power generation within the grid.
To address this gap, this study introduces a novel demand-based approach for integrating hydropower within the routing module of land surface models. First, hydropower infrastructures are placed in coherence with the hydrological network and links are built between hydropower plants and their supplying reservoirs to explicitly represent water transfers built for hydropower generation. Then, coordinated dam operation is simulated by distributing a prescribed electric demand to be satisfied by hydropower over the different power plants on the power grid, while considering the operational constraints associated with the multipurpose nature of most dams.
To validate our approach, this framework is implemented within the water transport scheme of a land surface model and assessed with the case study of the French electrical system. We drive the model with a high-resolution atmospheric reanalysis and prescribe the observed national hydropower production as the total power demand to be met by hydropower infrastructures. By comparing the simulated evolution of the stock in reservoirs to the observations, we find that the model simulates realistic operations of reservoirs and successfully satisfies hydropower production demands over the entire period. We highlight the roles of uncertainties in estimated precipitation and of the limited knowledge of hydropower networks on the estimation of production. Finally, we show that such an integration of hydropower operations in the model improves the simulations of river discharges in mountainous catchments affected by hydropower.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-3106', Anonymous Referee #1, 16 Feb 2024
General comments
This paper reports on the development of a model that simulates hydropower generation in France at 30-minute intervals at individual power plants, using a hydrological model used in meteorological and climatological studies. The primary boundary conditions of the model are electricity demand and meteorological information. Electricity demand is allocated to three different types of power plants: run-of-river, reservoir, and pumped-hydro-storage. River discharge and electricity generation are intensively validated and discussed.
Hydrologic models used in weather and climate studies are theoretically accurate, but often fail to achieve a simplistic objective of reproducing observed flow rates. The model constructed in this paper successfully achieved a reasonably accurate estimation of dam inflows in mountainous areas where flow reproduction is difficult. In addition, the experiment itself, in which dam releases nationwide are adjusted to match fluctuating electricity demand at 30-minute intervals, is significantly novel. At least, I have never seen or heard of such an experiment before.
While the research is excellent, the manuscript is extremely difficult to read. First, the manuscript is long. It seems the authors are trying to describe everything that was implemented and devised. The manuscript needs to be shortened, for example, by moving the treatment of exceptions (e.g., lines 180-185) to the supporting materials. Second, the structure is not standardized. In particular, Methods and Results are written in a mixed style. Sections 2 and 3 should be put together as Methods, and Sections 4 and 5 should be put together as Results. Then, the part corresponding to introducing results in Sections 2 and 3 (e.g., Fig. 7-10) should be moved to Results, and the methodological descriptions in Sections 4 and 5 (e.g., lines 505-516) should be moved to Methods. Finally, some technical terms seem to be not adequately defined or consistently used throughout the text (e.g., dispatch, dispatchable production, poundage, and reservoir). Further polishing is needed to enhance readability. Although I am convinced that the study is novel and reliable in general, I could not fully understand the details due to the above issues. Perhaps I will provide further technical comments after the text is fully revised.
Specific comments
Line 166 “we thus select as feeding reservoir the one that maximizes the potential function…”: Why did the authors seek the feeding reservoirs by using an algorithm? Collecting the published facts or inferring from satellite images sounds more reasonable and accurate. A bit more elaboration is needed here.
Line 180-185: I appreciate the authors providing every detail, but too much information hampers readability. Perhaps this part can be further shortened or moved to supplementary material.
Line 280 “the result of the dispatch of the total power demand”: What does “dispatch” mean? A clear definition should be added.
Figure 12 legend: is “bias<-50%” correct? From the text, I read “Abs(bias)>50%”.
Figure 14: First, is “poundage production” identical to reservoir production? Second, if this is the case, why must run-of-river and reservoir production be shown simultaneously (they are discussed in two different subsections)? Third, the legend “differences” should be reconsidered because it is hard to know what variable was compared here. Finally, I feel that too much information is crammed into one figure. Maybe it might be more understandable if you split it into multiple panels.
Figure 15: Is “pilotable production” identical to “dispatchable production” in Figure 14? The line for “target production” is hard to see.
Citation: https://doi.org/10.5194/egusphere-2023-3106-RC1 - AC1: 'Reply on RC1', Laure Baratgin, 21 May 2024
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RC2: 'Comment on egusphere-2023-3106', Anonymous Referee #2, 05 May 2024
The authors presented a model to simulate hydropower within the routing module of land surface models with a more detailed representation of hydropower plants and their operations. Specifically, the model is validated to produce hydropower at a 30-minute time-step for individual hydropower plants of three types: run-of-river, reservoir, and pumped-hydro-storage. Such a level of detailed representation in hydropower simulation is quite impressive. However, the authors did not demonstrate the value of using such a model. For example, how could such a model be useful to dispatch hydropower in the presence of intermittent renewable resources like wind and solar, and what could be its implications for other types of storage (e.g., batteries)? Answering such questions could be a valuable scientific contribution of the paper. Instead, much of the paper demonstrated the validation of the model to replicate observed river discharge and hydropower at the power plants. Also, the authors’ claim of “operations at the scale of a power grid” seems a bit misleading. The hydropower is simulated based on exogenous (observed) demand for hydropower but not based on the operation of a power grid, i.e., the model did not dispatch hydropower to meet grid-level demand considering other generation, storage, and transmission facilities. Moreover, the paper is not well-written. It is long and written in the form of a technical report (e.g., there are 18 figures and quite a few sections/paragraphs of a single sentence). In summary, I suppose the study requires extended experiments and analysis to demonstrate the value of the proposed model, while the manuscript itself needs to be substantially improved.
Citation: https://doi.org/10.5194/egusphere-2023-3106-RC2 - AC2: 'Reply on RC2', Laure Baratgin, 21 May 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-3106', Anonymous Referee #1, 16 Feb 2024
General comments
This paper reports on the development of a model that simulates hydropower generation in France at 30-minute intervals at individual power plants, using a hydrological model used in meteorological and climatological studies. The primary boundary conditions of the model are electricity demand and meteorological information. Electricity demand is allocated to three different types of power plants: run-of-river, reservoir, and pumped-hydro-storage. River discharge and electricity generation are intensively validated and discussed.
Hydrologic models used in weather and climate studies are theoretically accurate, but often fail to achieve a simplistic objective of reproducing observed flow rates. The model constructed in this paper successfully achieved a reasonably accurate estimation of dam inflows in mountainous areas where flow reproduction is difficult. In addition, the experiment itself, in which dam releases nationwide are adjusted to match fluctuating electricity demand at 30-minute intervals, is significantly novel. At least, I have never seen or heard of such an experiment before.
While the research is excellent, the manuscript is extremely difficult to read. First, the manuscript is long. It seems the authors are trying to describe everything that was implemented and devised. The manuscript needs to be shortened, for example, by moving the treatment of exceptions (e.g., lines 180-185) to the supporting materials. Second, the structure is not standardized. In particular, Methods and Results are written in a mixed style. Sections 2 and 3 should be put together as Methods, and Sections 4 and 5 should be put together as Results. Then, the part corresponding to introducing results in Sections 2 and 3 (e.g., Fig. 7-10) should be moved to Results, and the methodological descriptions in Sections 4 and 5 (e.g., lines 505-516) should be moved to Methods. Finally, some technical terms seem to be not adequately defined or consistently used throughout the text (e.g., dispatch, dispatchable production, poundage, and reservoir). Further polishing is needed to enhance readability. Although I am convinced that the study is novel and reliable in general, I could not fully understand the details due to the above issues. Perhaps I will provide further technical comments after the text is fully revised.
Specific comments
Line 166 “we thus select as feeding reservoir the one that maximizes the potential function…”: Why did the authors seek the feeding reservoirs by using an algorithm? Collecting the published facts or inferring from satellite images sounds more reasonable and accurate. A bit more elaboration is needed here.
Line 180-185: I appreciate the authors providing every detail, but too much information hampers readability. Perhaps this part can be further shortened or moved to supplementary material.
Line 280 “the result of the dispatch of the total power demand”: What does “dispatch” mean? A clear definition should be added.
Figure 12 legend: is “bias<-50%” correct? From the text, I read “Abs(bias)>50%”.
Figure 14: First, is “poundage production” identical to reservoir production? Second, if this is the case, why must run-of-river and reservoir production be shown simultaneously (they are discussed in two different subsections)? Third, the legend “differences” should be reconsidered because it is hard to know what variable was compared here. Finally, I feel that too much information is crammed into one figure. Maybe it might be more understandable if you split it into multiple panels.
Figure 15: Is “pilotable production” identical to “dispatchable production” in Figure 14? The line for “target production” is hard to see.
Citation: https://doi.org/10.5194/egusphere-2023-3106-RC1 - AC1: 'Reply on RC1', Laure Baratgin, 21 May 2024
-
RC2: 'Comment on egusphere-2023-3106', Anonymous Referee #2, 05 May 2024
The authors presented a model to simulate hydropower within the routing module of land surface models with a more detailed representation of hydropower plants and their operations. Specifically, the model is validated to produce hydropower at a 30-minute time-step for individual hydropower plants of three types: run-of-river, reservoir, and pumped-hydro-storage. Such a level of detailed representation in hydropower simulation is quite impressive. However, the authors did not demonstrate the value of using such a model. For example, how could such a model be useful to dispatch hydropower in the presence of intermittent renewable resources like wind and solar, and what could be its implications for other types of storage (e.g., batteries)? Answering such questions could be a valuable scientific contribution of the paper. Instead, much of the paper demonstrated the validation of the model to replicate observed river discharge and hydropower at the power plants. Also, the authors’ claim of “operations at the scale of a power grid” seems a bit misleading. The hydropower is simulated based on exogenous (observed) demand for hydropower but not based on the operation of a power grid, i.e., the model did not dispatch hydropower to meet grid-level demand considering other generation, storage, and transmission facilities. Moreover, the paper is not well-written. It is long and written in the form of a technical report (e.g., there are 18 figures and quite a few sections/paragraphs of a single sentence). In summary, I suppose the study requires extended experiments and analysis to demonstrate the value of the proposed model, while the manuscript itself needs to be substantially improved.
Citation: https://doi.org/10.5194/egusphere-2023-3106-RC2 - AC2: 'Reply on RC2', Laure Baratgin, 21 May 2024
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Cited
Laure Baratgin
Jan Polcher
Patrice Dumas
Philippe Quirion
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(15403 KB) - Metadata XML