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This dataset contains compiled observed hydropower generation for hydropower plants in Hawaii. Data have been compiled from data provided to the Energy Information Administration by asset owners. This dataset provides available generation data in monthly and annual files, with quality flags.
This dataset contains compiled observed hydropower generation for hydropower plants in Alaska. Data have been compiled from data provided to the Energy Information Administration by asset owners, data contained in annual reports produced by the Institute of Social and Economic Research at the University of Alaska Anchorage (Alaska Electric Power Statistics and Alaska Energy Statistics) and data provided to the Federal Energy Regulatory Commission by asset owners. This dataset provides available generation data from all sources in monthly and annual files, with quality flags, and generation data identifying the highest quality source in monthly and annual files.
The hydropower system is a cyber-physical system, and the industry is experiencing high operation and maintenance (O&M) costs along with increasing unplanned outages, primarily due to aging equipment and new asset loading patterns. Current (O&M) practices in asset management are predominantly reactive rather than predictive and systematic. To address these challenges, a proposed physics-informed data-driven degradation model aims to simulate the health of components in various environments. Its purpose is to accurately characterize wear and fatigue in the pilot components of hydropower systems. Additionally, the model provides informed confidence in prognostic predictions concerning asset degradation and remaining life.
Pumped Storage Hydropower (PSH) is currently the largest source of utility-scale electricity storage in the U.S. and worldwide. As the accelerating deployment of variable renewable technologies creates opportunity and value for energy storage, it has become increasingly important to characterize PSH costs to understand how it competes. Site-specific considerations and limited cost data in the public domain make it difficult to estimate capital costs for potential new PSH sites. This report documents a spreadsheet-based tool that addresses this challenge and creates a component-level bottom-up cost model for PSH that can be made publicly available for widespread use. It uses detailed site-level physical characteristics and design specifications to calculate key performance and cost parameters for individual components and the project as a whole. The model was developed in consultation with HDR, Inc. and Small Hydro Consulting to ensure it aligns with industry expectations. It enables PSH cost exploration across a wide range of system assumptions and could be customized or extended for the needs of a variety of users.
The Pumped Storage Hydropower (PSH) FAST Commissioning Prize aimed to reduce the time, cost, and risk required to commission PSH projects by crowdsourcing ideas via a three-stage prize. Objectives were to reduce the time to commission PSH projects from 10+ years to less than 5 years and to develop a baseline analysis for PSH.
As renewable penetration increases in the United States, maintaining stability and reliability of low-inertia power grid by providing sufficient frequency control capability becomes a challenge. Advanced pumped storage hydro technologies (APSH) will be expected to play an important role for future grid as not only an energy supplier, but also as an ancillary services provider. This paper studies the impact of using quaternary pumped storage hydropower (Q-PSH), as one of the newly proposed APSH technology, to provide primary frequency response. To quantify the impact of Q-PSH on frequency response of the U.S. Western Interconnection, a user-defined dynamic model of Q-PSH is developed on the GE Positive Sequence Load Flow (PSLF) platform and is implemented in a set of detailed U.S. Western Electricity Coordination Council (WECC) planning cases in which renewable penetration levels are 20%, 40%, 60% and 80%. Simulation results show that Q-PSH can help improve frequency nadir and settling frequency comparing to the conventional PSH.
In this study, we looked at the role of hydropower flexibility in variable renewable energy (VRE) integration. Our focus was on facilities that have at least ten hours of storage, i.e., plants that are "dispatchable" and have capacity values similar to that of fossil-fired generation. For our modeling framework, we used NREL's Mid-Case/95% Carbon Reduction by 2035 standard scenario as our foundation. This zonal model is representative of the buildout of a near-zero carbon policy grid in an otherwise "business-as-usual" policy and economic environment. We chose this scenario because it aligns well with the Administration's net-zero carbon grid by 2035 goal.
This presentation summarizes analysis done by researchers at the National Laboratory of the Rockies and Pacific Northwest National Laboratory to evaluate the potential for and explore project concepts of electricity generation and storage additions on the island of Molokai, Hawaii, as identified in the Community Energy Resilience Action Plan (CERAP) by the Molokai Clean Energy Hui (MCEH), Sustainable Molokai, and the Hawaii Natural Energy Institute (HNEI). These electricity generation and storage additions include distributed photovoltaics (PV), battery energy storage, and generators for critical facilities on the island that can provide backup energy to the facilities during grid disruptions and outages, a floating PV (FPV) system on Kualapuu Reservoir, and pumped storage hydropower (PSH) systems scaled to act as a significant or primary source of energy storage on the Molokai grid. This presentation accompanies the full technical report published under the same title.
This report documents analysis done by researchers at the National Laboratory of the Rockies and Pacific Northwest National Laboratory to evaluate the potential for and explore project concepts of electricity generation and storage additions on the island of Molokai, Hawaii, as identified in the Community Energy Resilience Action Plan (CERAP) by the Molokai Clean Energy Hui (MCEH), Sustainable Molokai, and the Hawaii Natural Energy Institute (HNEI). These electricity generation and storage additions include distributed photovoltaics (PV), battery energy storage, and generators for critical facilities on the island that can provide backup energy to the facilities during grid disruptions and outages, a floating PV (FPV) system on Kualapuu Reservoir, and pumped storage hydropower (PSH) systems scaled to act as a significant or primary source of energy storage on the Molokai grid.
Pumped storage hydropower is often overlooked in future grid planning efforts, in part because the cost to build a new facility is not always clear. That's why the National Renewable Energy Laboratory (NREL), along with the U.S. Department of Energy's Water Power Technologies Office, is developing improved cost estimates and cost models to reduce that uncertainty and give developers the data they need to decide where and when to construct new PSH facilities to support the country's evolving energy grid.
Abstract Objective Study the effects of downstream passage through a novel turbine designed for fish safety, the Restoration Hydro Turbine (RHT), on American Eels Anguilla rostrata in a recirculating turbine test facility. Methods A 55‐cm‐diameter RHT was operated under 10 m of hydraulic head and 667 revolutions/min. In total, 131 eels were passed through the turbine and 43 eels were used as experimental controls (length = 33.9–65.5 cm). High‐speed video of passage through the runner region was captured for 89% of turbine‐passed eels, and injury and behavioral effects were recorded immediately before and after passage, as well as after a 48‐h holding period. A subset of 37 eels was additionally examined with X‐ray imaging for internal injuries. Result The 48‐h survival rate for both treatment and control groups was 100%, with no major internal or external injuries present after the holding period. Conclusion This is a substantial improvement over eel survival rates through conventional Kaplan and Francis turbines, which may range from 40% to 95%, and suggests that hydropower turbines designed for safe downstream fish passage could be implemented without major impacts to eels.
As with most aquatic ecosystems, reservoirs play an important role in the global carbon (C) cycle and emit greenhouse gases (GHG) as carbon dioxide (CO 2 ) and methane (CH 4 ). However, GHG emissions from reservoirs are poorly quantified, especially in temperate systems, resulting in high uncertainty. We compared reservoir C emission estimates and uncertainty of diffusive, ebullitive, and degassing pathways in six hydropower reservoirs in the southeastern United States among four data sources: two field-based surveys and two models (including the GHG Reservoir “G-res” Tool). We found that CH 4 diffusion was most similar across data sources (modeled minus observed, bias = - 21 g CO 2-eq m -2 y -1 ) and had low relative uncertainty (coefficient of variation, CV = 0.98). On the other hand, CO 2 diffusion was least consistent across data sources (bias = - 518 g CO 2-eq m -2 y -1 ). Both field surveys indicated strong negative CO 2 diffusion (i.e., CO 2 uptake) at all reservoirs, while G-res estimated positive CO 2 diffusion. By extension, total C emissions showed similar discrepancies, leading to high uncertainty in upscaling and interpreting reservoir source-sink dynamics. Finally, CH 4 ebullition had the highest relative uncertainty (CV = 2.77) due to high variability across sites. We discuss limitations of field surveys and these models, including temperature-based annualization methods, varying definitions of ebullition zones, low sampling resolution, and lack of dynamism. Future field efforts focused on capturing variability in CO 2 diffusion and CH 4 ebullition will be especially valuable in reducing uncertainty and improving models to advance our understanding reservoir GHG emissions.
Timing of generation is becoming more and more valuable. This creates greater potential tension between environmental and power system objectives since both systems require their own flow patterns. Identifying win–win outcomes in this context requires being able to discuss the value of flexibility across stakeholder groups. This research proposes a two-stage optimization method to understand hydropower flexibility to meet both environmental and power system requirements. The tool simulates the two-settlement market process in the U.S. by maximizing revenues from both the day-ahead and real-time markets, subject to plant operational limits, regulatory flow and ramping requirements, and uncertainties associated with water availability and market prices. The model is formulated as linear programming problems and solved using IBM ILOG CPLEX optimizer. By examining a range of flow requirements, ramping constraints, and storage capacities, the proposed tool shows how to make more informed decisions to weigh the cost of specific flow requirements in the context of the overall license requirements. Results from the case study show that revenue is more sensitive to the ramping constraints than the minimum flow constraints. We also demonstrate that removing flow constraints in a dry month increases monthly revenue by up to 118%, as opposed to only 1% in a wet month. In addition, our results suggest that using a learning-based water flow forecast results in an increase of monthly revenue up to 6.4% compared with persistence forecast.
Small pumped-storage hydropower (PSH) units have gained popularity as distributed energy storage options that can provide flexibility to the operation of power distribution systems. Optimal operation of small PSH units is not only dependent on the energy storage provided to power distribution system, but also on the inflow and outflow of water from and to the water distribution system. Here, in this context, this paper develops an optimization model for coordinated operation of PSH units with power and water distribution systems. The proposed model optimizes the operation of water tanks, variable-speed pumps and PSH in pumping and generating modes to minimize the operation cost of power distribution system, while respecting the power flow constraints of power distribution and hydraulic constraints of water distribution system. Appropriate electricity tariffs are implemented to avoid additional expenses in water distribution system that can be enforced by its coordinated operation in favor of power distribution system. The proposed model is implemented on a 33-bus and a 123-bus test power distribution system connected to a 16-node test water distribution system. Results demonstrate the effectiveness of proposed model in tapping PSH flexibility to reduce the operation cost of power and water distribution systems, while meeting the power and water demands.
Reservoirs are a significant source of carbon (C) to the atmosphere, but their emission rates vary in space and time. Here we compared C emissions via diffusive and ebullitive pathways at several stations in six large hydropower reservoirs in the southeastern US that were previously sampled in summer 2012. We found that carbon dioxide (CO 2 ) diffusion was the dominant flux pathway during 2012 and 2022, with only three exceptions where methane (CH 4 ) diffusion or CH 4 ebullition dominated. CH 4 diffusion rates were positively associated with water temperature. However, we found no clear predictors of CH 4 ebullition, which had extremely high variability, with rates ranging from 0 to 739 mg C m -2 day -1 . For CO 2 diffusion, the direction of the flux shifted between 2012 and 2022, where all but three stations across all reservoirs emitted CO 2 in summer 2012, but every station sequestered CO 2 in summer 2022. Here, indicators of greater algal production were associated with CO 2 sequestration, including surface chlorophyll- a concentration, surface dissolved oxygen saturation, and pH. Additional sampling campaigns outside the summer season highlighted the importance of seasonal phenology in primary production on the direction of CO 2 diffusive fluxes, which shifted to positive CO 2 fluxes by the end of August as productivity decreased. Our results demonstrate the importance of capturing CO 2 sequestration in field and modeling measurements and understanding the seasonal drivers of these estimates. Measuring C emissions from multiple pathways in reservoirs and understanding their spatiotemporal responses and variability are vital to reducing uncertainties in global upscaling efforts.
Here, this paper proposes a proportional–integral-double–derivative (PID 2 ) optimisation method for the Kaplan hydropower system by building a digital twin. The study first uses one multilayer perceptron (MLP) to model the hydroturbine dynamic and then adopts three connected MLPs to model the generator dynamic, both in an open-loop fashion. Inspired by stochastic distribution control (SDC) theory, we regard the training of the turbine's neural network model as a process control problem, and we propose minimising entropy loss to update the network parameters. The next step is to build the digital twin by connecting the neural network models with a PID 2 controller and a lead-lag exciter and run the whole model in a closed-loop fashion. After that, a binary search approach is applied to optimise the PID 2 parameters based on the obtained digital twin model. The simulation results show that the proposed method can reduce the mean square tracking error by more than 90%. Furthermore, the method is extended to jointly optimise the PID 2 controller and excitation system gains through multiobjective optimisation, leveraging Pareto frontier analysis to balance active power and voltage tracking performance. Simulation results confirm the effectiveness of the proposed method, achieving a 83.46% reduction in relative mean square error of active power, a 47.13% reduction in terminal voltage tracking error, and an 82.78% improvement in the overall scalarized objective.
In recent years, ternary pumped storage hydropower (T-PSH), as one of the advanced PSH technologies, has attracted more attention from the industry. The interest is because of the capability of providing fast power support for the future electric grid with high penetration of renewable energy (RE). This paper focuses on studying the impact of T-PSH on frequency response of the U.S. Western Interconnection under different penetration levels of RE, which are from 20% to 80%. The detailed model of T-PSH is developed and implemented in the Western Interconnection grid model based on the GE Positive Sequence Load Flow (PSLF) platform, which can capture the unique dynamics of hydraulic short-circuit (HSC) mode and fast mode switching of T-PSH. To reveal the dynamic benefit from T-PSH, the frequency response of the Western Interconnection has been compared with and without T-PSH. In addition, a new solution is discussed that uses T-PSH to improve system stability issues caused by high RE penetration.
Full converter adjustable-speed pumped storage hydropower (FC AS-PSH) technology, as one of advanced-PSH technology, is developed from wind turbine technology. By making the synchronous machine connect to the grid through a full-size converter, FC AS-PSH has a wider adjustment range of speed and a better reactive power control capability compared with a doubly-fed asynchronous generator AS-PSH technology. When it plays as an energy backup in the power system, FC AS-PSH can provide a much faster response than conventional-PSH (C-PSH) which makes this technology provide better ancillary service for a high renewable penetrated system. In this paper, the dynamic modeling of FC AS-PSH is fully studied. We develop a detailed model of this technology in the IEEE 14-bus system based on GE Positive Sequence Load Flow (PSLF) platform. Especially, the first governor model is developed based on the Engineer’s Program Control Language (EPCL) user-defined model in this platform. All operation modes are validated and studied under a system contingency. Besides, comparison cases between FC AS-PSH and C-PSH are studied to show advantages providing from FC AS-PSH when it works with renewable energy.