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DOE OSTI2019

Salish Sea Response to Global Climate Change, Sea Level Rise, and Future Nutrient Loads

Given annual occurrences of hypoxia, harmful algal blooms, and evidence of coastal acidification, the potential impacts of climate change on water quality are of increasing concern in the U.S. Pacific Northwest estuaries such as the Salish Sea. While large-scale global climate projections are well documented, our understanding of the nearshore estuarine-scale response is not as well developed. In this study, the future response within the Salish Sea fjord-like environment was examined using the Salish Sea Model driven by downscaled outputs from the NCAR climate model CESM. We simulated a single projection of 95-year change under the RCP 8.5 greenhouse gas emissions scenario. Results indicate that higher temperatures, lower pH, and decreased dissolved oxygen levels in the upwelled shelf waters in the future would propagate into the Salish Sea. Results point to potential changes in average Salish Sea temperature (≈+1.51°C), dissolved oxygen (≈-0.77 mg/L), and pH (acidification -0.18 units) in the Y2095 relative to historical Y2000. The algal biomass in the Salish Sea could increase by ≈23% with a potential species shift from diatoms towards dinoflagellates. The region of annually recurring hypoxia could increase from <1% today to ≈16% in the future. Finally, the results suggest that the future response in the Salish Sea is less severe relative to the change predicted near the continental shelf boundary. This resilience of the Salish Sea may be attributed to the existence of strong vertical circulation cells that provide mitigation and serve as a physical buffer, thus keeping waters cooler, more oxygenated, and less acidic.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Load monitoring and compensation strategies for guided-waves based structural health monitoring using piezoelectric transducers

Accurate interpretation of in-situ piezoelectric sensor signals is a challenging task. This article presents the development of a numerical compensation model based on physical insight to address the influence of structural loads on piezo-sensor signals. The model requires knowledge of in-situ strain and temperature distribution in a structure while acquiring sensor signals. The parameters of the numerical model are obtained using experiments on flat aluminum plate under uniaxial tensile loading. It is shown that the model parameters obtained experimentally can be used for different structures, and sensor layout. Furthermore, the combined effects of load and temperature on the piezo-sensor response are also investigated and it is observed that both of these factors have a coupled effect on the sensor signals. It is proposed to obtain compensation model parameters under a range of operating temperatures to address this coupling effect. An important outcome of this study is a new load monitoring concept using in-situ piezoelectric sensor signals to track changes in the load paths in a structure.

environmental compensation↗

DOE OSTI2016

Effects of Lewis acidity of metal oxide promoters on the activity and selectivity of Co-based Fischer–Tropsch synthesis catalysts

Metal oxides of Ce, Gd, La, Mn, and Zr were investigated as promoters for improving the activity and selectivity of Co-based FTS catalysts. The extent to which these promoters decrease the selectivity toward CH 4 and increase the selectivity toward C 5+ hydrocarbons was found to depend on both the loading and the composition of the oxide promoter. Elemental mapping by STEM–EDS revealed that the propensity for a given metal oxide to associate with Co affects the sensitivity of the product distribution to changes in promoter loading. For all promoters, a sufficiently high loading resulted in the product distributions becoming insensitive to further increases in promoter loading, very likely due to the formation of a half monolayer of promoter oxide over the Co surface. Simulations suggest that the fraction of Co active sites that are adjacent to the promoter moieties approaches unity at this degree of coverage. The oxidation state of the promoter metal cation under reaction conditions, determined by in situ XANES measurements, was used to calculate relative Lewis acidity of the promoter metal cation. A strong positive correlation was found between the C 5+ product selectivity and the Lewis acidity of the promoter metal cations, suggesting that the promotional effects are a consequence of Lewis acid–base interactions between the reaction intermediates and the promoter metal cations. Rate data obtained at different pressures were used to estimate the apparent rate coefficient and the CO adsorption constant appearing in the Langmuir–Hinshelwood expression that describes the CO consumption kinetics for both unpromoted and the metal oxide-promoted catalysts. Both parameters exhibited positive correlations with the promoter Lewis acidity. In conclusion, these results are consistent with the hypothesis that the metal cations of the promoter act as Lewis acids that interact with the O atom of adsorbed CO to facilitate CO adsorption and dissociation.

Johnson, Gregory R.↗

DOE OSTI2012

Rigorous Kinetic Modeling and Optimization Study of a Modified Claus Unit for an Integrated Gasification Combined Cycle (IGCC) Power Plant with CO{sub 2} Capture

The modified Claus process is one of the most common technologies for sulfur recovery from acid gas streams. Important design criteria for the Claus unit, when part of an Integrated Gasification Combined Cycle (IGCC) power plant, are the ability to destroy ammonia completely and the ability to recover sulfur thoroughly from a relatively low purity acid gas stream without sacrificing flame stability. Because of these criteria, modifications to the conventional process are often required, resulting in a modified Claus process. For the studies discussed here, these modifications include the use of a 95% pure oxygen stream as the oxidant, a split flow configuration, and the preheating of the feeds with the intermediate pressure steam generated in the waste heat boiler (WHB). In the future, for IGCC plants with CO{sub 2} capture, the Claus unit must satisfy emission standards without sacrificing the plant efficiency in the face of typical disturbances of an IGCC plant, such as rapid change in the feed flow rates due to load-following and wide changes in the feed composition because of changes in the coal feed to the gasifier. The Claus unit should be adequately designed and efficiently operated to satisfy these objectives. Even though the Claus process has been commercialized for decades, most papers concerned with the modeling of the Claus process treat the key reactions as equilibrium reactions. Such models are validated by manipulating the temperature approach to equilibrium for a set of steady-state operating data, but they are of limited use for dynamic studies. One of the objectives of this study is to develop a model that can be used for dynamic studies. In a Claus process, especially in the furnace and the WHB, many reactions may take place. In this work, a set of linearly independent reactions has been identified, and kinetic models of the furnace flame and anoxic zones, WHB, and catalytic reactors have been developed. To facilitate the modeling of the Claus furnace, a four-stage method was devised so as to determine which set of linearly independent reactions would best describe the product distributions from available plant data. Various approaches are taken to derive the kinetic rate expressions, which are either missing in the open literature or found to be inconsistent. A set of plant data is used for optimal estimation of the kinetic parameters. The final model agrees well with the published plant data. Using the developed kinetics models of the Claus reaction furnace, WHB, and catalytic stages, two optimization studies are carried out. The first study shows that there exists an optimal steam pressure generated in the WHB that balances hydrogen yield, oxygen demand, and power generation. In the second study, it is shown that an optimal H{sub 2}S/SO{sub 2} ratio exists that balances single-pass conversion, hydrogen yield, oxygen demand, and power generation. In addition, an operability study has been carried out to examine the operating envelope in which both the H{sub 2}S/SO{sub 2} ratio and the adiabatic flame temperature can be controlled in the face of disturbances typical for the operation of an IGCC power plant with CO{sub 2} capture. Impact of CO{sub 2} capture on the Claus process has also been discussed.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2018

Gun-Drill Insertion in Drilling Deep Holes by Means of Multifunctional Machine Tools

The drilling of deep holes by means of gun drills is investigated so as to establish the parameters of the guide hole and its production. The rate of change in the load on the tool is proportional to the active length of the primary cutting edge. Assessment of the smoothness of tool insertion on the basis of the rate of change in the load on the tool is proposed.

42 ENGINEERING↗

DOE OSTI2017

Autonomous plug and play electric vehicle charging scenarios including reactive power provision: a probabilistic load flow analysis

Electric vehicle (EV) charging can have various impacts on low‐voltage distribution systems, along with increasing the uncertainty of network load levels. One method for capturing the statistical uncertainty is probabilistic load flow (PLF). A primary concern of such an approach is determining the correlation between the input variables. Since data are limited, a 1 min resolution bottom‐up time‐variant load model, capturing the changing voltage dependencies of the load, is used for modelling household electrical demand to provide pseudo‐meter data for the three‐phase PLF analysis of a residential distribution network. The correlation between the household and EV charging loads are implicitly taken into account by modelling the EV plug‐in and departure times with the corresponding occupancy model. Two autonomous plug‐and‐play charging scenarios are compared with a standard charging arrangement at both unity and 0.95 capacitive power factors. Four different PLF input correlation scenarios, varying from fully correlated to fully independent, are considered. The proposed charging scenarios and reactive power provision reduce the likelihood of system voltage violations introduced by EVs. The PLF results are verified against those from the initial time‐series analysis providing valuable insight into the uncertainty introduced by EVs and the correlation between household and EV loads.

Melhorn, Alexander C.↗

DOE OSTI2019

Current Developments in Retail Rate Design: Implications for Solar and Other Distributed Energy Resources

Retail electricity pricing is evolving in the context of broader shifts in how electricity customers pay for grid services and how they are compensated for customer-sited generation. This evolution has been prompted by a broad set of factors, chief among them being: widespread adoption of advanced metering infrastructure (AMI), increased customer investment in solar and other distributed energy resources (DERs), concerns about utilities’ fixed cost recovery and revenue sufficiency in an era of flat or declining load growth, and significant changes to utilities’ hourly net load profiles and operational needs as greater amounts of variable renewable energy (VRE) resources connect to the grid. This report discusses five current retail rate design trends among residential and commercial customer classes that have emerged, at least in part, in response to those drivers, and uses case studies to illustrate key motivations, variations in rate design, and aspects of implementation experience.

14 SOLAR ENERGY↗

DOE OSTI2024

Flattop-HEU Benchmark Reevaluation Summary

The Flattop critical assembly was first constructed in the 1950’s at Los Alamos National Laboratory as a follow-on to the Topsy experiment. Flattop is composed of a sphere of special nuclear material (SNM) surrounded by a thick spherical reflector made of natural uranium (NU). Two SNM cores currently exist: a highly-enriched-uranium (HEU) core and a plutonium core. The reflector is composed of three parts: a stationary hemisphere and two movable quarter spheres. For fine reactivity control, there are three control rods of NU that are inserted into the stationary hemisphere from underneath the assembly. The final components that allow for reactivity adjustment are the glory hole pieces, mass adjustment buttons, and hemispherical caps. These pieces can be loaded in various configurations to change the available reactivity loaded in the system.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Learning-Based Load Control to Support Resilient Networked Microgrid Operations

Microgrids have proven to be an effective option for increasing the resiliency of critical end-use loads during extreme events. Building on past operational experiences, some microgrid operators are examining the potential to network microgrids to further improve resiliency. However, the frequency deviations experienced on isolated microgrids during transient events, such as switching operations, step increases in load, and loss of generation, are significantly larger than those typically seen on bulk transmission systems. The larger frequency deviations can cause a loss of inverter-connected assets, resulting in a loss of power to critical end-use loads. This paper presents a method of mitigating the impact of transient events by engaging end-use loads using Grid-Friendly Appliance TM (GFA) controllers. An online, i.e., real-time, device-level algorithm is presented, which adjusts individual GFA controller frequency set-points based on the operational characteristics of each end-use load, and on the changing grid dynamic characteristics. The presented method improves the dynamic stability of the networked microgrid operations while minimizing the interruptions to end-use loads. The presented work is validated with dynamic simulations using a modified version of the IEEE 123-node test system with three microgrids, using the GridLAB-D TM simulation environment.

Radhakrishnan, Nikitha↗

DOE OSTI2024

Weather Sensitive High Spatio-Temporal Resolution Transportation Electric Load Profiles For Multiple Decarbonization Pathways

Electrification of transport compounded with climate change will transform hourly load profiles and their response to weather. We present a novel approach to generating hourly electric load profiles that considers charging strategies and evolving sensitivity to temperature. The approach consists of downscaling annual state-scale sectoral load projections from the multisectoral Global Change Analysis Model (GCAM) into hourly electric load profiles leveraging high resolution climate and population datasets. Profiles are developed and evaluated at the Balancing Authority scale, with a 5-year increment until 2050 over the Western U.S. Interconnect for multiple decarbonization pathways and climate scenarios. The datasets are readily available for production cost model analysis. Our open source approach is transferable to other regions.

Decarbonization, tranportation, Electric vehicle c↗

DOE OSTI2025

Influence of Phase-Change Materials and Operating Periods on Load Shifting for Thermal Storage Heat Pumps in European Climate Zones

As the reliance on heat pumps (HPs) for space conditioning increases worldwide, ex-tensive grid strains during utility peak hours are expected. Significant research efforts focus on investigating the use of integrated thermal energy storage (TES) systems to reduce peak energy demands. Conventionally, TES systems are often integrated to store and provide either cooling or heating, but not both. In this work, a single room-temperature phase-change material (PCM)-TES was integrated for dual-mode opera-tion with an R290 air-to-water 10.5 kW (3-Ton) HP. Two PCM melting temperatures (17°C, 22°C) were assessed to investigate their impact on system performance and cost reductions for Milan, Italy (4A); Barcelona, Spain (3A); and Oslo, Norway (6A). HP and HP-TES performance maps were generated using Modelica-based transient models and co-simulated with a prototype residential building using the Spawn of En-ergyPlusTM with simple rule-based controls. Our simulations indicate that PCM-17°C provided annual cost savings at higher peak-to-off-peak cost ratios, as the demand re-duction dominated the savings potential. The recharge energy costs and requirements became more dominant at lower cost ratios, making PCM-22°C more beneficial at lower cost ratios. Finally, despite Oslo's heating-dominated climate, the utility peak hours favor cooling demand reductions, making PCM-17°C more appealing. In all cases, the cost savings potential stabilized between 4 – 10% regardless of cost ratio, suggesting that system-level component and operation control optimization is required to maximize cost savings further.

25 ENERGY STORAGE↗

DOE OSTI2016

Aerodynamic Drag Reduction Technologies Testing of Heavy-Duty Vocational Vehicles and a Dry Van Trailer

This study focused on two accepted methods for quantifying the benefit of aerodynamic improvement technologies on vocational vehicles: the coastdown technique, and on-road constant speed fuel economy measurements. Both techniques have their advantages. Coastdown tests are conducted over a wide range in speed and allow the rolling resistance and aerodynamic components of road load force to be separated. This in turn allows for the change in road load and fuel economy to be estimated at any speed, as well as over transient cycles. The on-road fuel economy measurements only supply one lumped result, applicable at the specific test speed, but are a direct measurement of fuel usage and are therefore used in this study as a check on the observed coastdown results. Resulting coefficients were then used to populate a vehicle model and simulate expected annual fuel savings over real-world vocational drive cycles.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2021

Mitigating Phase Unbalance for Distribution Systems with High Penetrations of Solar PV (Final Technical Report)

Distribution system operators have traditionally limited unbalance among phases by maintaining similar loadings on each phase. High penetrations of distributed solar PV continually change the net loading on each phase, resulting in time-varying phase unbalances that can damage three-phase devices such as three-phase motors, violate grid codes, and increase technical losses. This project has developed several control strategies for the reactive power outputs of solar PV inverters in order to mitigate power quality issues related to phase unbalance. These control strategies include a decentralized approach that is solely based on local measurements, distributed and grouped approaches that consider subsets of loads and PV generators, and a centralized approach that leverages measurements from a variety of locations in order to compute optimal reactive power setpoints for each inverter. Variants of the controllers handle challenges relevant to practical implementations, including noisy measurements, delayed communications, and reactive power limits. Moreover, the project developed theory that provides convergence guarantees for systems with multiple interacting controllers as well as “balanceability” certificates that ensure satisfaction of phase unbalance requirements with variable loading. The controllers were integrated with NRECA’s Open Modeling Framework (omf.coop) and evaluated using actual distribution system models obtained from several NRECA member utilities. Application of the controllers results in significant improvements to phase unbalance in these test cases with decreases from base case levels of over 3% to under 0.5%, which is within the 2% IEC phase unbalance standard.

14 SOLAR ENERGY↗

DOE OSTI2024

Reviewing Flexibility in Industrial Electrification: U.S. Green Ammonia and Steel Industries [Slides]

The renewable energy transition in the power sector involves a paradigm shift for flexibility. Supply flexibility faces new constraints due to the increased share of variable renewable resources. Increased demand flexibility can allow less use of peaking power plants and delay need for additional capacity and transmission. Industrial customers are larger on average than residential and commercial consumers and have typically provided the largest share of demand response in the United States. We consider industrial demand, studying characteristics of flexible industrial loads. We examine the dynamics of change occurring around industrial load flexibility by focusing on two case studies: green ammonia and steel production via electric arc furnaces. Electric arc furnace steel production is an important component of current demand response programs, whereas green ammonia and green fuels offer new paradigms for flexibility. We analyze the structure and functions of the technological innovation systems of load flexibility in those two industries via interviews with twenty-two stakeholders. We conclude that the technological innovation systems are not well-functioning for flexibility in EAF based steelmaking, but are in the green ammonia space. Explicit connections between scope two greenhouse gas emissions reporting and flexibility are lacking, and industry stakeholders do not appear to make a connection between decarbonization and load flexibility.

25 ENERGY STORAGE↗

DOE OSTI2023

Limits on the Range and Rate of Change in Power Take-Off Load in Ocean Wave Energy Conversion: A Study Using Model Predictive Control

Previous work comparing power take-off (PTO) architectures for ocean wave-powered reverse osmosis suggests that variable displacement in the wave energy converter (WEC)-driven pump does not offer a significant performance advantage. A limitation of that study is that the WEC was subject to a constant load within a given sea state (“Coulomb damping”) and did not account for controlled, moment-to-moment variation of the PTO load enabled by a variable displacement pump. This study explores the potential performance advantage of a variable PTO load over Coulomb damping. Model predictive control is used to provide optimal load control with constraints on the PTO load. The constraints include minimum and maximum loads and a limit on the rate of load adjustment. Parameter studies on these constraints enable conclusions about PTO design requirements in addition to providing an estimated performance advantage over Coulomb damping. Numerical simulation of the Oyster 1 WEC is carried out with performance weighted by historical sea state data from Humboldt Bay, CA. The results show a performance advantage of up to 20% higher yearly-average power absorption over Coulomb damping. Additionally, the parameter studies suggest that the PTO load should be adjustable down to at least 25% of the maximum load and should be adjustable between the minimum and maximum loads within a few seconds.

16 TIDAL AND WAVE POWER↗

DOE OSTI2016

Automated Dynamic Demand Response Implementation on a Micro-grid

In this paper, we describe a system for real-time automated Dynamic and Sustainable Demand Response with sparse data consumption prediction implemented on the University of Southern California campus microgrid. Supply side approaches to resolving energy supply-load imbalance do not work at high levels of renewable energy penetration. Dynamic Demand Response (D 2 R) is a widely used demand-side technique to dynamically adjust electricity consumption during peak load periods. Our D 2 R system consists of accurate machine learning based energy consumption forecasting models that work with sparse data coupled with fast and sustainable load curtailment optimization algorithms that provide the ability to dynamically adapt to changing supply-load imbalances in near real-time. Our Sustainable DR (SDR) algorithms attempt to distribute customer curtailment evenly across sub-intervals during a DR event and avoid expensive demand peaks during a few sub-intervals. It also ensures that each customer is penalized fairly in order to achieve the targeted curtailment. We develop near linear-time constant-factor approximation algorithms along with Polynomial Time Approximation Schemes (PTAS) for SDR curtailment that minimizes the curtailment error defined as the difference between the target and achieved curtailment values. Our SDR curtailment problem is formulated as an Integer Linear Program that optimally matches customers to curtailment strategies during a DR event while also explicitly accounting for customer strategy switching overhead as a constraint. We demonstrate the results of our D 2 R system using real data from experiments performed on the USC smartgrid and show that 1) our prediction algorithms can very accurately predict energy consumption even with noisy or missing data and 2) our curtailment algorithms deliver DR with extremely low curtailment errors in the 0.01-0.05 kWh range.

Kuppannagari, Sanmukh R.↗

DOE OSTI2020

RLScheduler: An Automated HPC Batch Job Scheduler Using Reinforcement Learning

Today’s high-performance computing (HPC) platforms are still dominated by batch jobs. Accordingly, effective batch job scheduling is crucial to obtain high system efficiency. Existing HPC batch job schedulers typically leverage heuristic priority functions to prioritize and schedule jobs. But, once configured and deployed by the experts, such priority functions can hardly adapt to the changes of job loads, optimization goals, or system settings, potentially leading to degraded system efficiency when changes occur. To address this fundamental issue, we present RLScheduler, an automated HPC batch job scheduler built on reinforcement learning. RLScheduler relies on minimal manual interventions or expert knowledge, but can learn high-quality scheduling policies via its own continuous ‘trial and error’. We introduce a new kernel-based neural network structure and trajectory filtering mechanism in RLScheduler to improve and stabilize the learning process. Through extensive evaluations, we confirm that RLScheduler can learn high-quality scheduling policies towards various workloads and various optimization goals with relatively low computation cost. Moreover, we show that the learned models perform stably even when applied to unseen workloads, making them practical for production use.

Zhang, Di↗

DOE OSTI2025

Hydraulic Conductivity Measurements, Utqiagvik (Barrow), Alaska, 2014

Six individual ice cores were collected from the Barrow Environmental Observatory in Barrow, Alaska, in May of 2013 as part of the Next Generation Ecosystem Experiment (NGEE). Each core was drilled at a different location to varying depths. After drilling, the cores were stored in coolers packed with dry ice and flown to Lawrence Berkeley National Laboratory (LBNL) in Berkeley, CA. 3-dimensional images of the cores were constructed using medical X-ray computed tomography (CT) scanner at 120kV. Hydraulic conductivity samples were extracted from these cores at LBNL Richmond Field Station in Richmond, CA, in February 2014 by cutting 5 to 8 inch segments using a chop saw. Samples were packed individually and stored at -20C freezing temperatures to minimize any changes in structure or loss of ice content prior to analysis. Hydraulic conductivity was determined through falling head tests using a permeameter [ELE International, Model #: K-770B] (Appendix A). Samples were placed in a latex membrane via a membrane stretcher while frozen. Use of a membrane stretcher made the membranes easier to secure and minimized contact with the sample. A clear polycarbonate sleeve, fabricated with a stainless steel ring at the bottom to keep the sleeve from floating, was placed around the sample inside the permeameter to minimize deformation during analysis. The permeameter was filled with water and 1.0 PSI of air was applied for confining pressure during sample defrost. Outflow valves were left open to allow for incremental thawing and samples were left to thaw for approximately 12 hours. After approximately 12 hours of thaw, initial falling head tests were performed. When the flow was significantly too fast or too slow, the analysis was stopped and the burette size was adjusted accordingly (i.e. a larger diameter burette was used for flows that were faster than desired or a smaller diameter burette was used for flows that were slower than desired). Two to four measurements were collected on each sample and collection stopped when the applied head load exceeded 25% change from the original load. Analyses were performed between 2 to 3 times for each sample. The final hydraulic conductivity calculations were computed using methodology of Das et al., 1985.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗