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At least 235 records · Page 13

Velocity- and pressure-based metrics for estimating strike injuries during fish passage through hydro turbines

Hydropower is a crucial source of clean and reliable energy worldwide, and its importance will continue to grow. To enhance the environmental sustainability of hydropower development and operations, it is essential to predict the strike injury rates of fish passing through turbines accurately and cost-effectively. However, conventional experiments involving a large number of live fish are still commonly conducted in practice, and previous attempts mainly focused on the dose-response relationships at an individual level or relative comparisons of biological characterization between different conditions. Thus, this study proposes two novel strike metrics based on velocity and pressure (M V and M P ) measured by the cutting-edge Sensor Fish (SF) technology, designed to quantify the biological effects of strikes and collisions between fish and rigid hydraulic structures. SF measurements and 48-hour survival rates of live fish from a study conducted at the Ice Harbor Dam on the Snake River were used to establish thresholds for the two proposed metrics. These metrics and thresholds were then applied to three additional SF studies conducted at hydropower facilities featuring Kaplan turbines within the Columbia River basin. Results from the application of the strike metrics indicate that the estimated survival rates derived from both metrics agree well with previously reported live fish survival rates. Furthermore, the study identified specific passage regions with elevated risks of fish mortality due to strikes and collisions. Overall, the proposed strike metrics present a reliable and cost-effective approach to reducing reliance on live fish and lowering costs in fish passage studies.

Biological characterization↗

Paired Hydro-Battery Hybrid System Operations Using MIQP Based Multi-Objective Optimization

Hybridizing a hydropower plant with a battery energy storage system is often a very expensive decision. So to make the case for feasibility of hybridization the cost benefit analysis must be comprehensive. Most literature found on this subject only uses one out of many different available value streams to carry out a feasibility analysis. To that end, in this study we propose a multi-objective optimization formulation and a mixed-integer quadratic programming optimization engine that considers multiple different value streams and optimizes hydro-battery hybrid system paired operations to maximize revenue generated from energy arbitrage while simultaneously minimizing the total hydro turbine mileage thus reducing turbine starts and stops and improving turbines life all while following all environmental constraints and not violating any limitations either regulatory or preferential (i.e., to support recreational activities like white water rafting, etc.). In this study we also implemented the developed optimization methodology to a real-world case study of Bagnell dam hydropower facility (8 units totaling 240 MW rated power capacity) which is owned and operated by our industry partner Ameren Energy Inc. The case study outcomes shows that by hybridizing the Bagnell dam hydropower facility with a 60 MW x 2-hr battery energy storage system, the annual benefits can be increased over \$6 million while reducing the annual mileage averaged per turbine and number of start/stops by over 98\% and 85\% respectively.

Chalishazar, Vishvas H.↗

Definition and Execution of Regulatory requirements for acceptance of the Whooshh Fish Transport System (Abstract)

The purpose of this project is to assist in the definition, summarization, and execution of the regulatory requirements that validate the Whooshh Fish Transport System (WFTS) as an accepted method of fish passage transport for Endangered Species Act- (ESA) listed species; moving these fish past in-stream barriers, such as hydropower facilities. Validation of this technology, through testing by PNNL, means that regulatory agencies will have documented evidence from which to support an approval decision enabling Whooshh to quickly commercialize their product for use in waterways with ESA listed species and provide the hydropower relicense/development marketplace a viable solution to the fish passage problem that threatens the hydropower industry. Given the definition of “take” in the ESA, without validation, commercialization in this space in the U.S. will not happen because the regulatory agencies will not have the determinative study results they require to authorize the use of this new technology that interact with ESA-listed species.

13 HYDRO ENERGY↗

Annual Technology Baseline: The 2024 Electricity Update

Consistent cost and performance data for various electricity generation technologies can be difficult to find and may change frequently for certain technologies. With the Annual Technology Baseline (ATB), the National Renewable Energy Laboratory annually provides an organized and centralized set of such cost and performance data. The ATB uses the best information from the Department of Energy national laboratories' energy analysts. The ATB has been reviewed by experts and it includes the following electricity generation and storage technologies: land-based wind, offshore wind, distributed wind, utility-scale solar photovoltaics (PV), commercial-scale solar PV, residential-scale solar PV, concentrating solar power, geothermal power, hydropower, utility-scale battery storage, commercial battery storage, residential battery storage, pumped storage hydropower, nuclear, coal, and natural gas. EIA data for conventional biopower are included for reference. This webinar presentation introduces the 2024 update to the ATB Electricity data and documentation.

battery storage↗

Potential Effects of Climate Change and Solar Radiation Modification on Renewable Energy Resources

Solar radiation modification (SRM) is a possible deliberate approach to decrease or reflect incoming solar radiation with the goal of reducing global temperatures, which have increased over the last decades due to high atmospheric greenhouse gas concentrations. Stratospheric aerosol injection, specifically, has shown potential for successfully reducing global temperatures in climate model simulations. Despite the growing literature in the areas of climate change and SRM, their combined effects on renewable energy generation, a climate change mitigation strategy, have not been addressed. In this review paper, we synthesize previous literature on the possible effects of climate change and SRM on renewable energy resources (i.e., wind energy, solar energy, biomass energy, and hydropower), review the status of climate change and SRM research, and explore potential effects of SRM on renewable energy primarily in the Continental United States (CONUS), but with global perspectives as well. We discuss the research challenges and impacts of SRM on renewable energy and conclude by discussing the potential implications of SRM for renewables for SRM governance and policy. This work is not advocating for or against SRM. It is highlighting an important potential impact for future decision makers.

Kumler, Andrew [National Renewable Energy Laborato↗

Climate change and its influence on water systems increases the cost of electricity system decarbonization

The electric sector simultaneously faces two challenges: decarbonization to mitigate, and adaptation to manage, the impacts of climate change. In many regions, these challenges are compounded by an interdependence of electricity and water systems, with water needed for hydropower generation and electricity for water provision. Here, we couple detailed water and electricity system models to evaluate how the Western Interconnection grid can both adapt to climate change and develop carbon-free generation by 2050, while accounting for interactions and climate vulnerabilities of the water sector. We find that by 2050, due to climate change, annual regional electricity use could grow by up to 2% from cooling and water-related electricity demand, while total annual hydropower generation could decrease by up to 23%. To adapt, we show that the region may need to build up to 139 GW of additional generating capacity between 2030 and 2050, equivalent to nearly thrice California's peak demand, and could incur up to $\$$150 billion (+7%) in extra costs.

13 HYDRO ENERGY↗

IrrigationViz: A Geospatial Visualization Application to Facilitate Irrigation Modernization

Irrigation water delivery infrastructure, such as canals and pipelines, are essential to agriculture in the Western U.S., yet many of these systems are reaching the end of their useful lives. Reinvestment can achieve a wide variety of benefits, from water conservation to energy savings or renewable energy generation. Modernization requires significant planning, design, and implementation funding which can be a challenge for many irrigation districts. Here, this paper introduces IrrigationViz, a web-based mapping application designed to help irrigation districts visualize and generate high-level cost and benefit estimates for infrastructure modernization projects. These estimates can help water managers identify projects that benefit from additional engineering resources and ultimately obtain funding. IrrigationViz includes map interactions, graphs, and visualization components to facilitate planning and communication to stakeholders and funders. IrrigationViz combines user-provided information about a water-delivery system with public datasets and basic engineering formulas to generate estimates of the benefits of reinvestment. Estimates include the amount of water seepage in earthen canals, potential hydropower generation associated with replacing a canal with a pressurized pipe, and pipe size recommendations. We found that hydropower generation estimates compared favorably with real world projects, but seepage loss estimates showed high variability relative to on-the-ground measurements

99 - GENERAL AND MISCELLANEOUS↗

Lab Collaboration Project (LCP) for Marine Energy: Quantifying Collision Risk for Fish and Turbines Final Technical Report (Task 10)

A persistent environmental concern for the widespread deployment of tidal turbines is the potential for fish and marine mammals to collide with rotating blades (Copping et al. 2016, Copping and Hemery 2020). This is a consequence of well-documented bird and bat mortalities around wind turbines (Smallwood 2007, Thompson et al. 2017), as well as fish mortality at conventional hydropower dams (Pracheil et al. 2016) and tidal barrages (Dadswell and Rulifson 1994). However, unlike hydropower dams or barrages, tidal turbines do not involve structures that channel all flow through the turbines. Similarly, while functionally similar to wind turbines, tidal turbines often operate at lower relative velocities and, depending on the end-use application, may be significantly smaller than utility-scale wind turbines. Both of these factors reduce the likelihood and severity of collision, but the knowledge base on this topic remains limited.

13 HYDRO ENERGY↗

Dynamic Modeling of a Kaplan Hydroturbine Using Optimal Parametric Tuning and Real Plant Operational Data

To address grid variability caused by renewable energy integration and to maintain grid reliability and resilience, hydropower must quickly adjust its power generation over short time periods. This changing energy generation landscape requires advance technology integration and adaptive parameter optimization for hydropower systems via digital twin effort. However, this is difficult owing to the lack of characterization and modeling for the nonlinear nature of hydroturbines. To solve this issue, this paper first formulates a six-coefficient Kaplan hydroturbine model and then proposes a parametric optimization tuning framework based on the Nelder–Mead algorithm for adaptive dynamic learning of the six-coefficients so as to build models that describe the turbine. To assess the performance of the proposed optimal parametric tuning technique, operational data from a real-world Kaplan hydroturbine unit are collected and used to model the relationship between the gate opening and the generated power production. The findings show that the proposed technique can effectively and adaptively learn the unknown dynamics of the Kaplan hydroturbine while optimally tune the unknown coefficients to match the generated power output from the real hydroturbine unit with an inaccuracy of less than 5%. The method can be used to provides optimal tuning of parameters critical for controller design, operational optimization and daily maintenance for hydroturbines in general.

13 HYDRO ENERGY↗

All Kitted Out

The Hydropower Knowledge Sharing and Succession Planning Toolkit, created by the National Renewable Energy Laboratory (NREL) in collaboration with the U.S. Department of Energy’s Water Power Technologies Office (WPTO), can help your organization effectively plan for workforce changes and share knowledge across employees. By proactively implementing knowledge sharing and succession planning strategies, hydropower organizations can safeguard institutional knowledge, enhance workforce resilience, and ensure long-term operational stability in an evolving industry landscape.

13 HYDRO ENERGY↗

Evaluating How Climate Adaptation Measures Affect the Interconnected Water‐Energy Resource Systems of the Western United States

Abstract The Western US faces increasing water stress from the impacts of climate change, making it difficult to meet water demands for the region's cities, agriculture, and hydropower generators. Existing literature suggests that climate adaptation measures such as water conservation, cropland retirement, wastewater recycling, and managed aquifer recharge can alleviate some of these challenges. Few analyses, however, compare the relative efficacy and system‐wide effects of these adaptations under different climate projections across the entire Western United States. Here we use a Western US‐wide water systems model to evaluate, by sector and sub‐region, how the widespread implementation of these adaptive measures impacts water demands, water deliveries, and electricity use related to the water system for three different climate projections. We find that wastewater recycling has greater potential to lower unmet indoor water demands than urban indoor water conservation measures. However, when implemented at scale, indoor water conservation reduces electricity use by an average of 683 Terawatt hours while wastewater recycling increases energy use by an average of 721 Terawatt hours, cumulatively from 2020 to 2070. Cropland retirement and aquifer recharge adaptations increase the ability to meet agricultural water demand, increase groundwater storage, and reduce summertime electricity use. While most of these findings are consistent across different climate projections, the benefits of aquifer recharge are sensitive to spatial variation of precipitation. Given the limitations and tradeoffs of each individually, the results suggest that a portfolio of adaptation measures will be needed for a climate‐resilient water and energy future in the Western US. Plain Language Summary The Western US faces increased water stress from the impacts of climate change, making it difficult to meet demands for cities, agriculture, and hydropower facilities. Adaptation measures like water conservation, retiring agricultural lands, recycling wastewater, and storing water underground can address these challenges. However, there is little modeling to understand the impact of these adaptations if they were implemented across the entire Western US while also considering climate change. We use a Western US‐wide water systems model to evaluate how implementing adaptation measures impacts groundwater levels, the ability to meet water demands, and electricity use related to water in three different possible climate futures. We find that recycling wastewater to drinking water standards does a better job of meeting urban water demands than water conservation measures. However, indoor water conservation reduces energy use for water while recycling wastewater increases energy use for water. Retiring agricultural lands and storing water underground both increase the ability to meet agricultural water demands, increase underground water storage, and reduce summertime energy use. No adaptation measures provides benefits across every metric we track. Therefore, multiple adaptation measures will likely be needed to achieve a climate‐resilient future for energy and water in the Western US. Key Points Water‐related climate change adaptations have different benefits and tradeoffs for interconnected water‐energy systems in the Western U.S. Wastewater recycling most increases urban water coverage, but has a significant tradeoff in the form of greater electricity use Cropland retirement and aquifer recharge benefit water and electricity systems most in the summer when those systems are most stressed

Singhal, A↗

Reliability and resilience of environmental flows under uncertainty: reconsidering water year types and inconsistent flow requirements in California

Abstract Environmental water allocation in California is a complex legal process involving various government agencies and stakeholders. E-flow requirements can be based on annual runoff typologies called water year types (WYTs), which dictate water volume, timing, and duration. In this study, we examined hydropower licensing documents of the major water and power projects in the Central Sierra Nevada to catalog e-flow requirements by WYT. In this study case, we identify how WYT classification systems and categories vary across and within different basins. Additionally, we assessed the impacts of climate change on hydrology, the frequency of WYTs identified, and the reliability and resilience of e-flows using future projections (2031–2060) of 10 Global Circulation Models (GCMs). We then propose a potential adaptation strategy using a 30 year moving percentiles approach to recalculate WYTs. We identified eight WYT classifications systems were identified, and their WYT distributions statistically significantly changes across all GCMs, even though most GCMs indicate no statistically significant change in hydrology. Disparities in future impacts are observed among and within hydropower projects, with some river reaches showing negative impacts on reliability and resilience. The adaptation strategy can generally boost resilience and improve reliability, but simply updating existing WYT thresholds without flexible regulatory frameworks reconsidering WYTs and e-flows thresholds, may not yield substantial improvements. Challenges in managing e-flows in California within regulatory and hydroclimatic contexts are intricate due to the lack of standardized approaches, leading to inconsistencies and potential conflicts among stakeholders, that will likely be exacerbated by climate change. Thus, we emphasize that targeted, site-specific, and adaptive management strategies are crucial, besides the need for a harmonized and consistent approach to defining and applying WYT categories and methods and/or e-flow assessments.

Environmental Sciences & Ecology↗

Hydroboost

HydroBoost is the most realistic revenue optimization tool for the hybridization of hydropower and battery energy storage systems to date. The innovative representation of how operators actually schedule hydropower in practice results in more realistic predictions of revenue and operations. Unlike other optimization tools, HydroBoost generates forecast energy prices with uncertainty to use in the optimization. This allows HydroBoost to give users a range of potential revenue with an upper bound using the perfect foresight pricing and a lower bound using a naive persistence forecast model. Additional forecast can be generated and used in the optimization, such as additive models, random forest, and neural networks to give further insight into potential revenue. HydroBoost has been designed to be applicable for both run-of-river and reservoir storage sites. The primary focus is on the day-ahead market and requires year-long data with an hour time-step. All time-series input and constraints are contained in an Excel worksheet for convince. The user will run the forecasting generation first with a Python script to give the optimization model the necessary requirements. Next the optimization is ran using Julia and results are generated and stored into a directory as csv files. HydroBoost includes an additional module to generate figures based on the results of the optimization simulation. The results help analyze the results and users to draw insights into how the hydro and battery systems are operated and the revenue each is producing. Additionally, the difference between the perfect foresight model and models that include forecast can easily be inspected.

Phillips, TylerB. [Idaho National Laboratory (INL)↗

EverGREEN 2045: An Energy Mix to Decarbonize Washington State

Washington State’s future resource mix is likely to be comprised of intermittent renewables and carbon-free generation including hydropower by 2045. Generation will likely be comprised of wind, solar photovoltaic (PV), batteries, pumped storage hydropower (PSH), existing nuclear power plants, and potentially enhanced geothermal systems and advanced nuclear reactor technologies. To assess the cost and stability of the future resource mix, we partner with X-energy (advanced reactor design) and AltaRock Energy (enhanced geothermal system) for proprietary cost data. After estimating the costs of these two new technologies, we design plausible future resource mix scenarios to meet Washington State’s Clean Energy Transformation Act which transitions the state to carbon-free generation by 2045. We assess the cost and stability of the future resource mix with power system analysis tools, finding revenues are sufficient to cover variable operating and maintenance costs for most technologies providing power in 2030 and 2045, but capacity payments or power purchase agreements will likely be necessary for flexible resources, including enhanced geothermal systems and advanced nuclear reactors, to participate in the future resource mix.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Financial Analysis of the Smallmouth Bass Flows implemented at the Glen Canyon Dam during Water Year 2024

The Glen Canyon Dam (GCD) is a Colorado River Storage Project (CRSP) power resource that is a component of the Salt Lake City Area Integrated Projects (SLCA/IP). The 2016 record of decision (ROD) for the GCD long-term experimental and management plan (LTEMP) final Environmental Impact Statement (EIS) specifies criteria for GCD monthly water releases, daily and hourly operating limits, and experimental releases. This report presents a financial analysis of the Smallmouth bass (Micropterus dolomieu) (SMB) flows implemented at GCD during Water Year (WY) 2024. These bypass flows were introduced by the U.S. Bureau of Reclamation (USBR) as an emergency response to the growing threat posed by invasive SMB in the Colorado River ecosystem downstream of the dam. SMB are a non-native predatory species that pose a significant threat to native fish populations, including the endangered humpback chub (Gila cypha). The thermal regime below GCD, typically cold due to hypolimnetic releases from Lake Powell, has historically served as a thermal barrier limiting SMB establishment. However, persistently low reservoir levels in recent years have reduced stratification in Lake Powell, allowing warmer water to be released downstream. This has enabled SMB to spawn successfully below the dam, prompting urgent ecological concerns. To mitigate the risk of SMB proliferation, the USBR implemented a series of bypass flows in WY 2024. Drawn from a lower elevation than the penstocks, the bypass structures released cooler water downstream. These short-duration bypass flows aimed to keep temperatures cool enough to prevent SMB from spawning, thereby reducing the ecological threat posed by this invasive species. Although motivated by ecological objectives, these bypass flows came with financial tradeoffs. Releasing water through the bypass structures instead of the turbines at GCD reduced hydropower generation, resulting in a significantly lower financial position for Western Area Power Administration (WAPA), which is responsible for marketing the electricity produced by the GCD Powerplant. This report analyzes the financial impact of the SMB flows implemented from July to November 2024. These experimental releases led to an estimated financial cost of approximately $18.9 million, primarily driven by the substantial volume of water diverted through the bypass structures. This study applies an integrated set of tools to estimate WAPA financial impacts by simulating GCD under two types of cases; namely, (1) a “With Experiment” case that mimics the water operations that actually occurred, including the SMB bypass flows, and (2) a “Without Experiment” case that simulates operations under the assumption that the SMB flows did not occur. Both cases comply with LTEMP hourly and daily operating criteria, and the monthly water release volumes are assumed to be identical under both cases. The Colorado River Storage Project Python-based model (CRiSPPy) model was the main modeling tool used to simulate the dispatch of the GCD hydropower plant and associated water releases from Lake Powell. In the modeling process, the research team used extensive data sets and historical information on SLCA/IP power plant characteristics, hydrologic conditions, and WAPA’s power purchases and sales prices.

13 HYDRO ENERGY↗

Optimize the Autonomous Sensor Fish Device for Understanding Interactions of Aquatic Animals with Marine and Hydrokinetic and Hydro Systems (CRADA 476) Final Report

This project at the Pacific Northwest National Laboratory (PNNL) enhances our understanding of how aquatic life interacts with marine renewable energy (MRE) and hydropower systems through the development and testing of advanced sensor technology. The Marine Sensor Fish (MSF) and its smaller variants, the Sensor Fish Mini (SF Mini) and Flexible Sensor Fish (FSF), measure critical environmental stressors, such as shear forces, pressure changes, and strike impacts, that are essential for assessing the risks posed by energy devices, including tidal turbines, hydropower installations, and other MRE infrastructure. Rigorous field testing has shown that these tools are effective in capturing detailed data on turbulence, pressure variations, strike impacts, and other stressors near these devices, providing valuable insights into the conditions faced by aquatic species. Economically, these tools offer renewable energy developers a practical solution for streamlining environmental assessments and ensuring regulatory compliance, ultimately reducing costs associated with evaluating and mitigating ecological impacts. This research also benefits the public by promoting the growth of renewable energy sources that protect aquatic ecosystems, advancing both sustainable energy production and environmental stewardship.

13 HYDRO ENERGY↗

Grid Resiliency using Hydro-based Microgrids During Wildfires

The primary objective of this project is to assess the techno-economic viability of hydropower resources with supplementary investments, including microgrid controllers, storage solutions, load banks, additional generation like diesel generators, communication links, and transmission infrastructure. The aim is to enable these systems to operate autonomously (in islanded mode) and ensure grid resiliency during and after wildfire events. The project seeks to establish a comprehensive framework for setting up hydropower-based microgrids, from risk estimation to final investment decisions. These microgrids can provide critical support during emergencies and offer additional grid stability and revenue opportunities during regular operations and other system contingencies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

PNNL-ANL Hydrometeorological Super Ensemble

The current dataset contains data upload links to the following **hydrologic (water balance), river routing (water management), and hydropower simulation** data over CONUS: * Climate Forcing: **Livneh** (https://www.nature.com/articles/sdata201542) * Simulation Scenario: **Historical** * Simulation Period: **1971-2013 (1972-2013 for Hydropower)** * Simulation Models: **VIC (Variable Infiltration Capacity)**, **mosartwmpy (Model for Scale Adaptive River Transport-Water Management in Python)**, and **PNNL B1Hydro** * Output Format: **NetCDF** and **CSV**

Tidwell, Vincent C [Pacific Northwest National Lab↗