Enhancing hydropower modeling in variable generation integration studies

Ibáñez, Eduardo; Magee, Timothy; Clement, Mitch; Brinkman, Gregory; Milligan, Michael; Zagona, Edith

doi:10.1016/j.energy.2014.07.017

Cited by 50 publications

(19 citation statements)

References 21 publications

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“…Most production cost models use a version of constrained cost optimization. This study used PLEXOS Integrated Energy Model (PLEXOS), the PCM created by Energy Exemplar, which has been used in other studies exploring similar problems [11,12,34]. As an input to PLEXOS, a version of the TEPPC 2024 dataset was used with some modifications.…”

Section: Methodsmentioning

confidence: 99%

Hydropower Impacts on Electrical System Production Costs in the Southwest United States

Bain

Acker

2018

Energies

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Abstract:The Colorado River is an important natural resource for the Southwestern United States. Predicted climate change impacts include increased temperature, decreased rainfall and increased probability of drought in this region. Given the large amount of hydropower on the Colorado River and its importance to the bulk electricity system, this purpose of this study was to quantify the value hydropower in operating the electrical system, and examined changes in hydropower value and electricity costs under different possible future drought conditions and regional generation scenarios. The goal was to better understand how these scenarios affect operating costs of the bulk electrical system, as well as the value of the hydropower produced, and proposed a method for doing so. The calculated value of the hydroelectric power was nearly double the mean locational marginal price in the study area, about $73 to $75 for most scenarios, demonstrating a high value of the hydropower. In general, it was found that reduced water availability increased operating costs, and increased the value of the hydropower. A calculated value factor showed that when less hydroelectric power is available, the hydropower is more valuable. Furthermore, the value factor showed that the value of hydro increases with the addition of solar or the retirement of thermal generating resources.

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Section: Methodsmentioning

confidence: 99%

Hydropower Impacts on Electrical System Production Costs in the Southwest United States

Bain

Acker

2018

Energies

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“…The database that includes the location, nameplate capacity, and BA dependency of the hydropower plants were extracted from the WECC TEPPC (Transmission Expansion Planning Policy Committee) 2024 common case and using infrastructure present in 2010 6 . The database is used to set up commercial production cost models such as PLEXOS and PROMOD among others, and are widely used over the WECC (Ibanez et al 2014 to model the unit commitment and dispatch of generators to minimize the production cost of the power grid system. In this study, we simulated the flow regulation based on over 500 reservoirs operated for a range of purposes (water supply, flood control, etc) (Voisin et al 2017 and we explicitly simulate hydropower at the 149 individual hydropower plants that had a capacity greater than 50 MW, collectively accounting for about 51 000 MW or 92% of the total capacity across the WECC.…”

Section: Study Area and Datamentioning

confidence: 99%

Non-stationary hydropower generation projections constrained by environmental and electricity grid operations over the western United States

Zhou

Voisin

2018

Environ. Res. Lett.

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In the western United States, 27% of electricity demand is met by hydropower, so power system planners have a key interest in predicting hydropower availability under changing climate conditions. Large-scale projections of hydropower generation are often simplified based on regression relationships with runoff and they are not always ready to inform power system models due to the coarse time scale (annual) or limited number of represented power plants. We developed an enhanced process-based hydropower model to predict future hydropower generation by addressing the commonly under-represented constraints, including (1) the ecological spills, (2) penstock constraints to provide flexibility in electricity operations, and (3) biases in hydro-meteorological simulations. We evaluated the model over the western United States under two emission scenarios (RCP4.5 and RCP8.5) and ten downscaled global circulation models. At the annual time scale, potential hydropower generation is not projected to change substantially, except in California. At the seasonal time scale, systematic shifting of the generation patterns can be observed in snowmelt-dominated regions. These projected annual and regional trends are comparable to other regression-based relationships. However, the representation of more complex operations and constraints tend to reduce the uncertainties inherent to climate projections at seasonal scale. In the Pacific Northwest region where hydropower is the dominant electricity source, our predicted future change of hydropower generation is about 10% less than the regression-based projections in spring and summer. The model can also capture the seasonal non-stationary in hydrologic changes. The spatio and temporal scales of the model, increased accuracy and quantification of uncertainty allow one to use the products to inform power system models toward supporting energy sector planning activities and water-energy trade-offs.

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“…Ideally, a tool used to analyze the power system would be able to account for both power and river system considerations simultaneously. Although this is technically feasible, many of the necessary river system constraints have not been implemented in PCMs or CEMs because of the data and run-time challenges presented in running these tools simultaneously [17].…”

Section: Power System Modelsmentioning

confidence: 99%

“…These constraints can generally be categorized as environmental, operational, and regulatory. When performing studies on the power system, hydropower modeling should incorporate these constraints to most accurately represent the capabilities of these facilities to potentially facilitate the integration of variable renewable energy resources into the power system [15]- [17]; however, most models do not comprehensively represent the constraints on hydropower operations for various reasons, including a lack of computational resources, the modeling time required with increasingly complex models, or a lack of data to properly account for hydrological considerations. This can lead to inaccurate estimates of the ability of hydropower facilities to provide flexibility.…”

Section: Introductionmentioning

confidence: 99%

Hydropower Modeling Challenges

Stoll

Andrade

Cohen

et al. 2017

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Executive SummaryHydropower facilities are important assets for the electric power sector and represent a key source of flexibility for electric grids with high penetrations of variable generation. As variable renewable generation sources expand, understanding the capabilities and limitations of the flexibility from hydropower resources is important for grid planning. Appropriately modeling these resources, however, is difficult because of the wide variety of constraints these plants face that other generators do not. These constraints can be broadly categorized as environmental, operational, and regulatory. This report highlights several key issues incorporating these constraints when modeling hydropower operations in production cost and capacity expansion models. Many of these challenges involve a lack of data to adequately represent the constraints or issues of model complexity and run time. We present several potential methods for improving the accuracy of hydropower representation in these models to allow for a better understanding of hydropower's capabilities on the electric grid.

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Enhancing hydropower modeling in variable generation integration studies

Cited by 50 publications

References 21 publications

Hydropower Impacts on Electrical System Production Costs in the Southwest United States

Hydropower Impacts on Electrical System Production Costs in the Southwest United States

Non-stationary hydropower generation projections constrained by environmental and electricity grid operations over the western United States

Hydropower Modeling Challenges

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