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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Dynamic Modeling of Sequential Service Restoration in Islanded Single Master Microgrids

This paper presents a methodology for generating restoration sequences in distribution systems and microgrids with emphasis on deriving optimal switching times for remote control switches (RCS). Microgrid architecture considered are assumed to be operating in islanded single master mode. Control methods for handling the unbalance inherent in distribution systems using single-phase controlled PQ inverters were developed and incorporated in the proposed method. The problem of considering simultaneously both energy optimization and dynamic stability of the system, which is lacking in existing methods, was addressed by studying the transient behavior of microgrids based on extended EMTP simulations and then approximate and incorporate these behaviors into the optimization formulation for restoration. The approach is based on multi-objective optimization of final restored load and total restoration time. The methodology was studied on a modified IEEE 123 node test feeder. An EMTP simulation in PSCAD of the formed microgrids was used to validate the accuracy of the dynamic and steady-state characteristics of the resulting systems. By considering the transient behavior of DGs during restoration, a better restoration sequence that does not trigger protection relays could be realized.

42 ENGINEERING↗
DOE OSTI2024

BENEFIT with Northeastern University: HVAC Hardware-in-the-Loop Experimental Testing of a Heat Pump and Air Conditioner

This dataset includes HVAC Hardware-in-the-Loop (HIL) experimental results for a single stage, SEER 16, HSPF 9.5, 3-ton single-speed air source heat pump with 15 kW of backup auxiliary heating tested in both cooling and heating mode, and a two stage, SEER 21, 2-ton central air conditioner tested in cooling mode for a set of outdoor temperatures and indoor setpoint temperatures. In addition to these tests, experimental tests focused on the operation of auxiliary heating for the heat pump for winter condition were also conducted. The laboratory experiments for transient testing of the heat pump and air conditioner were conducted using the two HIL systems in the Systems Performance Laboratory (SPL) at NREL’s Energy Systems Integration Facility (ESIF). Further information on laboratory design and capabilities of the SPL along with the architecture of HVAC HIL system can be found in: Sparn, B. F. 2018. Laboratory Resources and Techniques to Evaluate Smart Home Technology (No. NREL/CP-5500-71696). National Renewable Energy Laboratory (NREL), Golden, CO (United States). https://www.nrel.gov/docs/fy18osti/71696.pdf and the experimental setup and validation of HVAC HIL platform can be found in: Ramaraj, S. and Sparn, B. 2022. Validation of HVAC Hardware-In-the-Loop Simulation for Advanced Control Strategies in Smart Homes (No. NREL/CP-5500-82562). National Renewable Energy Lab (NREL), Golden, CO (United States). https://www.nrel.gov/docs/fy22osti/82562.pdf. These experimental results can be used to validate how we currently model the cycling behavior of heat pumps and air conditioners. Additionally, many demand response programs implement heat pump and air conditioner control by changing the thermostat set point – these data may also be used to verify our models for heat pump and air conditioner demand response control are implemented correctly. The Test_Matrix file describes all the indoor and outdoor test conditions for heat pump and air conditioner and the file names of data sets include information about the test conditions. A wide range of outdoor air temperatures were chosen to accommodate summer and winter conditions. In addition to operating the HVAC equipment with different outdoor temperatures, we also operate the system with different indoor temperature set points to represent different grid signals or different operating conditions. For cooling conditions, the baseline set point is 72°F. To represent Load Up signals, the setpoint is changed to 68°F. The Load Shed set point is 76°F. For heating conditions, the baseline set point was assumed to be 68°F. The Load add set point is 72°F and the Load shed set point is 64°F. The starting indoor temperature for cooling conditions was set ~2°F above the indoor setpoint temperature so that the equipment turned on quickly. Similarly, the initial indoor temperature was set ~2°F lower than setpoint for heating mode tests to ensure that heating began quickly. The return air temperature was assumed to be equal to the indoor setpoint temperature in all cases. The experimental data are sampled at 1-second intervals. The data from ecobee thermostat at 5-minute interval are resampled and added to the corresponding file. The content of each data set is as follows: • T_Return (C): Measured return air temperature [C] • T_Return_SP (C): Return air temperature setpoint from E+ model, sent to HIL [C] • T_Supply (C): Measured supply air temperature at evaporator outlet [C] • T_Outdoor (C): Measured outdoor air temperature [C] • T_Outdoor_SP (C): Outdoor air temperature setpoint from weather file, sent to HIL [C] • T_Indoor (C): Measured indoor air temperature [C] • T_Indoor_SP (C): Indoor air temperature setpoint from E+ model, sent to HIL [C] • Outdoor Unit Power (W): Measured power of the outdoor unit [W] • Indoor Unit Power (W): Measured power of the indoor unit [W] • Evaporator Airflow Rate (CFM): Measured evaporator or indoor unit airflow rate sent to E+ model [CFM] • Cooling/Heating Capacity (kW): Calculated cooling/heating capacity sent to E+ model [kW] • T_SP_Thermostat (C): Thermostat cooling/heating setpoint temperature [C] • T_Indoor_Thermostat (C): Thermostat indoor air temperature [C]

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Microstructure control to improve creep strength of alumina-forming austenitic heat-resistant steel by pre-strain

Highlights: • The effect of pre-strain on creep strength of AFA steel was studied. • The creep test was performed at 700°C and 200Mpa, and the aging test was carried out using box furnace at 700°C to simulate the microstructural evolution during creep. • Microstuctural evolution was observed by using SEM, EBSD, and TEM to investigate the relationship between creep strength and microstructure. - Abstract: At 700 °C and 200 MPa, the creep rupture time of W-containing alumina-forming austenitic heat-resistant (WAFA) steel increases from 1044 to 3119 h by pre-strain. Pre-strain introduces a lot of dislocation into the matrix and most of the dislocations remain stable to the end of creep without recovery and recrystallization. In addition, the dislocations have enabled secondary NbC and Laves phase to be uniformly distributed and refined. However, the dislocations lower grain boundary strength due to the coarsening of precipitates along grain boundaries Therefore, the increase in the creep rupture time in spite of deterioration of grain boundary strength is attributed to the dislocation strengthening and enhanced precipitation hardening within grains.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A generic microgrid controller: Concept, testing, and insights

Microgrids have garnered attention in recent years as a way to increase the reliability of the grid, increase the reliability of electricity service to customers, adapt to an increasing percentage of intermittent renewable generation, and serve both customer critical loads and the needs of adjacent communities in the case of emergencies such as natural disasters. One barrier to microgrids is the historic cost and lack of standardization associated with microgrid controllers. To reduce this cost and address standardization, specifications for a Generic Microgrid Controller (GMC) were developed with the goal to facilitate the design and ease of adaptation of microgrid controllers to various microgrids of different sizes and with different resources. A GMC must address two core functions, Transition and Dispatch, as well as several optional higher level functions such as economic dispatch, and renewable and load forecasting. The GMC specifications were demonstrated and evaluated using a commercial simulation platform for two different microgrids, a 20MW-Class community microgrid and a 10MW-Class medical center microgrid. For each microgrid, the GMC was tested in hardware-in-the-loop (HIL) using an OPAL-RT real-time digital simulator, and the two core functions were assessed. The results established that (1) the GMC is successful in seamlessly transitioning the microgrids to and from an islanded mode, (2) a load/generation mismatch at the time of separation depends on the microgrid configuration and must be lower than a specific value determined by simulation testing, and (3) the GMC Dispatch Function response is acceptable in maintaining, in the islanded mode, 60Hz for a range of load changes.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Benchmarking the performance of a high-Q cavity qudit using random unitaries

High-coherence cavity resonators are excellent resources for encoding quantum information in higher-dimensional Hilbert spaces, moving beyond traditional qubit-based platforms. A natural strategy is to use the Fock basis to encode information in qudits. One can perform quantum operations on the cavity mode qudit by coupling the system to a non-linear ancillary transmon qubit. However, the performance of the cavity-transmon device is limited by the noisy transmons. It is, therefore, important to develop practical benchmarking tools for these qudit systems in an algorithm-agnostic manner. We gauge the performance of these qudit platforms using sampling tests such as the heavy output generation test as well as the linear cross-entropy benchmark, by way of simulations of such a system subject to realistic dominant noise channels. We use selective number-dependent arbitrary phase and unconditional displacement gates as our universal gateset. Our results show that contemporary transmons comfortably enable controlling a few tens of Fock levels of a cavity mode. This framework allows benchmarking even higher dimensional qudits as those become accessible with improved transmons.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Modelling galaxy cluster triaxiality in stacked cluster weak lensing analyses

Counts of galaxy clusters offer a high-precision probe of cosmology, but control of systematic errors will determine the accuracy of this measurement. Using Buzzard simulations, we quantify one such systematic, the triaxiality distribution of clusters identified with the redMaPPer optical cluster finding algorithm, which was used in the Dark Energy Survey Year-1 (DES Y1) cluster cosmology analysis. We test whether redMaPPer selection biases the clusters’ shape and orientation and find that it only biases orientation, preferentially selecting clusters with their major axes oriented along the line of sight. Modelling the richness–mass relation as log-linear, we find that the log-richness amplitude ln (A) is boosted from the lowest to highest orientation bin with a significance of 14σ, while the orientation dependence of the richness-mass slope and intrinsic scatter is minimal. We also find that the weak lensing shear-profile ratios of cluster-associated dark haloes in different orientation bins resemble a ‘bottleneck’ shape that can be quantified with a Cauchy function. We test the correlation of orientation with two other leading systematics in cluster cosmology – miscentering and projection – and find a null correlation. The resulting mass bias predicted from our templates confirms the DES Y1 finding that triaxiality is a leading source of bias in cluster cosmology. However, the richness-dependence of the bias confirms that triaxiality does not fully resolve the tension at low-richness between DES Y1 cluster cosmology and other probes. Our model can be used for quantifying the impact of triaxiality bias on cosmological constraints for upcoming weak lensing surveys of galaxy clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Impacts of Control, Penetration, and Distribution of Embedded Storage Network in Bulk Power System

The current shift in generation mix from fossil fuel plants towards variable and intermittent renewable energy sources is poised to create a future grid with reduced physical inertia and mismatch between generation and demand. Embedded storage, which is a concept of a coordinated network of storage units sited at the interface between the transmission and distribution system, is proposed as a mechanism to provide a buffer between generation and demand. This paper proposes an automated framework to model and integrate embedded storage in large-scale power systems with industry-grade grid-following (GFL) and grid-forming (GFM) control technologies. More importantly, the developed framework is used to explore the impacts of embedded storage control, penetration, location, and capacity in providing fast frequency response to the grid under contingency events such as generator trips and faults. The framework and study are conducted using the transient-stability simulation tool PSS/E and a realistic model of the Puerto Rico grid as a chosen test system. The simulation results show that GFL and GFM embedded storage, distributed throughout the system, with sufficient penetration and capacity, can effectively improve primary frequency response of the system under the studied contingency events.

Battery Energy Storage, embedded storage, grid-for↗
DOE OSTI2018

EPA and Idaho National Laboratory create first of its scale

Advancing the science and engineering of decontaminating water distribution systems and safely disposing of high-volumes of contaminated water are high priorities for the EPA. To help address these science gaps, EPA homeland security researchers have developed the first-of-its-scale Water Security Test Bed (WSTB). Water is an important component of everyday life. We rely on safe, clean water for our health and the health of the environment. Protecting this vital resource is critical to living safely and securely. The U.S. Environmental Protection Agency is responsible for working with water utilities to protect water systems from contamination and to clean up systems that become contaminated. Purposeful or inadvertent distribution system contamination can result in large amounts of infrastructure and water that must be cleaned. Water distribution systems contamination can be caused by, for example, natural disasters such as Superstorm Sandy or by individuals hoping to cause harm. The WSTB, constructed at the Department of Energy’s (DOE) Idaho National Laboratory, replicates a section of a typical municipal drinking water system including a piping system with roughly 445 feet of pipe and two fire hydrants laid out in an “L” shape using 40-year-old, eight-inch cement mortar lined, ductile iron pipes, excavated after twenty years of use for water conveyance. Researchers built the WSTB above ground for easy access during experiments, and to facilitate fast leak detection. Over the next several years, EPA and partner researchers will conduct experiments using simulants of various biological, chemical, and radioactive materials that simulate high toxic versions of these agents. At this “full” sized system, researchers will demonstrate approaches to contamination detection, sensor and model testing, infrastructure decontamination, water treatment and cyber testing developed at lab and pilot scale. Researchers are also able to verify if laboratory results that were effective in controlled conditions are as effective in full-scale testing. Having the ability to conduct bench scale studies in a real world setting can help address specific research gaps, and help water researchers understand conditions in which real world drinking water systems operate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

RELAP5-3D Modeling of High Temperature Test Facility (HTTF) Test PG-26

The High Temperature Test Facility (HTTF) at Oregon State University (OSU) is a scaled integral effects experiment designed to investigate transient behavior in high-temperature gas-cooled nuclear reactors with prismatic fuel and reflector blocks. Several tests have been completed, and more are still planned to at the HTTF, including depressurized conduction cooldown (DCC) and pressurized conduction cooldown (PCC) transients. This report analyses test PG-26, a progression of the Double Ended Inlet-Outlet Crossover Duct Break transient that is referred to as a DCC. PG-26 has been performed at the HTTF between May 30 and June 30, 2019. Core initial conditions (i.e., before the DCC started) have been met using low power (<100 kW) and two of ten available electric heaters. The DCC transient was initiated during the 50 th hour of the test. The break valves were opened, and hot helium from the core and cold helium from the reactor cavity simulation tank (RCST) started mixing. The gases flowed in a countercurrent fashion, where the top half of the hot duct contained hot helium that flowed in one direction and cold helium that flowed in the other direction in the bottom half of the duct. After the pressure and density reached equilibrium, the event entered a diffusion mode. The onset of a reverse natural circulation was not observed during the DCC period of the test. Version 4.4.2ie of the RELAP5-3D computer code has been used to model the HTTF PG-26 test, and results have been compared to available high-quality measured data. The model used in this study is the quality-controlled HTTF RELAP5-3D model (HTTF base 2018-04-19 QA), originally developed by P. Bayless. The report includes RELAP5-3D results of the “base calculations” as well as some sensitivities to important uncertain model inputs, such as primary helium mass flow rate, core ceramic thermal properties, as well as heat evacuation and loop friction models. Using the base RELAP5-3D model predicts a countercurrent helium flow in the hot duct observed at the beginning of the DCC, but instead of going into a molecular diffusion mode, the model predicts the onset of natural convection. Increasing friction in the core and hot duct prevents the natural convection from happening in some of the simulations. Although some temperatures are well predicted (and even overpredicted), the general tendency is to underpredict the ceramic and helium temperatures and heat removal rates during the DCC, resulting in many of the assessment findings being in minimal or insufficient agreement with the data. It is worth noting that the described discrepancies between measured data and RELAP5-3D predictions are not RELAP5-3D code limitations. More so, they reflect limitations in boundary condition and thermal property knowledge. While the RELAP5-3D calculations of the test provide some insights into what happens during the transient, and point to missing or potentially uncertain data to which the experimenters can direct their attention, the principal conclusion is that the PG-26 test data are insufficient for a system code assessment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Understanding and control of Zener pinning via phase field and ensemble learning

Zener pinning refers to the dispersion of fine particles which influences grain size distribution via movement of grain boundaries in a polycrystalline material. Grain size distribution in polycrystals has a significant impact on their properties including physical, chemical, mechanical, and optical to name a few. We explore the use of Phase-field modeling and machine-learning techniques to understand and improve the control of grain size distribution via Zener pinning in polycrystalline materials. We develop a machine learning model that determines the relative importance of various parameters to exercise microstructure control via Zener pinning. Our workflow combines high-throughput phase-field simulations and machine learning to address the computational bottlenecks associated with large-scale simulations as well as identify features necessary for microstructure control in polycrystals. A random forest (RF) regression model was developed to predict grain sizes based on five Phase-field model parameters, achieving an average prediction error of 0.72 nm for the training data and 1.44 nm for the test data. The importance of the input parameters is analyzed using the SHapley Additive exPlanations (SHAP) approach which reveals that diffusivity, volume fraction, and particle diameter are the most important parameters in determining the final grain size. These findings will allow us to select the best second-phase particles, optimize grain size distributions and thus design microstructures with the desired properties. The developed method is a highly versatile and generalizable approach that can be used to assess the combined effects of individual features in the presence of multiple variables.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Real-time capable modeling of neutral beam injection on NSTX-U using neural networks

A new model of heating, current drive, torque and other effects of neutral beam injection on NSTX-U that uses neural networks has been developed. The model has been trained and tested on the results of the Monte Carlo code NUBEAM for the database of experimental discharges taken during the first operational campaign of NSTX-U. By projecting flux surface quantities onto empirically derived basis functions, the model is able to efficiently and accurately reproduce the behavior of both scalars, like the total neutron rate and shine through, and profiles, like beam current drive and heating. With this being said, the model has been tested on the NSTX-U real-time computer, demonstrating a rapid execution time orders of magnitude faster than the Monte Carlo code that is well suited for the iterative calculations needed to interpret experimental results, optimization during scenario development activities, and real-time plasma control applications. Simulation results of a proposed design for a nonlinear observer that embeds the neural network calculations to estimate the poloidal flux profile evolution, as well as Z eff and fast ion diffusivity, are presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Real-time capable modeling of neutral beam injection on NSTX-U using neural networks

A new model of heating, current drive, torque and other effects of neutral beam injection on NSTX-U that uses neural networks has been developed. The model has been trained and tested on the results of the Monte Carlo code NUBEAM for the database of experimental discharges taken during the first operational campaign of NSTX-U. By projecting flux surface quantities onto empirically derived basis functions, the model is able to efficiently and accurately reproduce the behavior of both scalars, like the total neutron rate and shine through, and profiles, like beam current drive and heating. The model has been tested on the NSTX-U real-time computer, demonstrating a rapid execution time orders of magnitude faster than the Monte Carlo code that is well suited for the iterative calculations needed to interpret experimental results, optimization during scenario development activities, and real-time plasma control applications. Simulation results of a proposed design for a nonlinear observer that embeds the neural network calculations to estimate the poloidal flux profile evolution, as well as effective charge and fast ion diffusivity, are presented.

Neural networks↗
DOE OSTI2018

Integrated Boosting and Hybridization for Extreme Fuel Economy and Downsizing

The objective of this project was to develop, demonstrate, and evaluate commercialization of a highly efficient downsized engine by electrification of the air delivery and waste heat recovery system and optimizing energy usage to achieve significant fuel economy improvement at a commercially viable cost. The system consists of an Electrically Assisted Variable speed Supercharger (EAVS), driven by an electric motor and the engine through a planetary gear train, that provides engine boost pressure and provides the mild hybrid functions of engine start/stop, torque assist, and brake energy recovery. In the exhaust path of the engine is the electric Waste Heat Recovery (eWHR) system, a roots-based expander driven by another electric motor, that enables exhaust gas energy recovery along with controlled back pressure on the engine. The two electric motors are powered by a 48V rechargeable lithium-ion battery. Further, the EAVS system coupled to an EGR valve enables very precise high exhaust recirculation rates to control the NOx emissions. Through two budget periods, the project team of Eaton, Isuzu, Southwest Research Institute and AVL designed and developed the EAVS and eWHR systems, integrated with an Isuzu diesel engine, and validated the target fuel economy performance and emissions by engine dynamometer testing and vehicle level simulations. GT Power model-based analyses results were used to size the EAVS and eWHR systems for the 1.9L Isuzu Spark engine. The two systems were built and the functional testing was carried out to verify the boosting performance of the superchargers. Following the baseline engine dynamometer testing, the two systems were integrated with the engine and the fuel economy performance and emissions were determined by combined steady state and transient testing over three drive cycles, namely, FTP75, NEDC and HWFET. The EAVS/eWHR system demonstrated 4% improvement in fuel economy for the NEDC cycle in engine dyno testing, correlating well with vehicle simulation results (5.3%). The simulation results indicated that the combination of hybrid functions and drivetrain optimization, fuel economy improvement of more than 20% was feasible with the system. The commercialization study to evaluate the cost of the system and the scalability for different engine/vehicle classes was planned for the final budget period but not completed as the project was closed at the end of budget period two.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Continued Investigations of Respirable Release Fractions for Stress Corrosion Crack-Like Geometries

The formation of a stress corrosion crack (SCC) in the canister wall of a dry cask storage system (DCSS) has been identified as a potential issue for the long-term storage of spent nuclear fuel. The presence of an SCC in a storage system could represent a through-wall flow path from the canister interior to the environment. Modern, vertical DCSSs are of particular interest due to the commercial practice of using relatively high backfill pressures (up to approximately 800 kPa) in the canister to enhance internal natural convection. This pressure differential offers a comparatively high driving potential for blowdown of any particulates that might be present in the canister. In this study, the rates of gas flow and aerosol transmission of a spent fuel surrogate through an engineered microchannel with dimensions representative of an SCC were evaluated experimentally using coupled mass flow and aerosol analyzers. The microchannel was formed by mating two gage blocks with a linearly tapering slot orifice nominally 13 μm (0.005 in.) tall on the upstream side and 25 μm (0.0010 in.) tall on the downstream side. The orifice is 12.7 mm (0.500 in.) wide by 8.89 mm (0.350 in.) long (flow length). Surrogate aerosols of cerium oxide, CeO 2 , were seeded and mixed with either helium or air inside a pressurized tank. The aerosol characteristics were measured immediately upstream and downstream of the simulated SCC at elevated and ambient pressures, respectively. These data sets are intended to demonstrate a new capability to characterize SCCs under well-controlled boundary conditions. Modeling efforts were also initiated that evaluate the depletion of aerosols in a commercial dry storage canister. These preliminary modeling and ongoing testing efforts are focused on understanding the evolution in both size and quantity of a hypothetical release of aerosolized spent fuel particles from failed fuel to the canister interior and ultimately through an SCC.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

ActiveBAS: A Low-cost, Scalable Control Solution for Grid-Interactive Small and Medium Sized Commercial Buildings

This project aims to develop and enhance a low-cost, highly scalable control solution for Small and Medium-Sized Commercial Buildings (SMCB), assess the business potential at multiple sites, and perform commercialization efforts. The technology can be applied to any buildings served by multiple units, with the benefits being greatest for open-spaced buildings, such as banks, retail stores, restaurants, and factories. This project aims to develop an affordable control solution for: 1) SMCB grid responsiveness, 2) reduction of GHG by changing unit operations, 3) greater reduction in utility costs, and 4) rapid adoption in the marketplace. The proposed technology will be built on a previously developed and demonstrated MPC solution. The minimal sensor requirement and less need of control expertise are the unique feature of the algorithm that leads to low capital and maintenance costs, and short installation and implementation time. These attributes contribute to low capital and maintenance costs, as well as a short installation and implementation time. However, these advantages come with a trade-off: increased difficulties and unreliability when applying traditional modeling and MPC control approaches due to limited information. This final report describes the modeling approaches developed and tested to overcome these challenges. It begins by outlining the modeling challenge posed by minimal sensor requirements, then delves into the proposed modeling approaches, which primarily involve system identification. Finally, preliminary test results for a simulation case study are presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

EGS Collab Project Experiment 1 Overview and Progress

Enhanced Geothermal Systems (EGS) offer the potential to extract and use large quantities of clean energy, but questions remain on reservoir creation and sustainability. The EGS Collab project, supported by the US Department of Energy’s Geothermal Technologies Office, is establishing a suite of highly monitored and well-characterized intermediate-scale (~10-20 m) field test beds along with fracture stimulation and interwell flow tests to better understand processes that control formation of effective subsurface heat exchangers. EGS Collab tests will provide a means of testing tools and concepts that could later be employed under geothermal reservoir conditions at DOE’s Frontier Observatory for Research in Geothermal Energy (FORGE) or enhanced geothermal systems. Key to the project is using numerical simulations in the experiment design and interpretation of results. Our first set of experiments is underway at the Sanford Underground Research Facility (SURF) in South Dakota. To date, stepwise stimulations have been performed at two locations, with the final stimulation connecting our injection and production wells. Numerous data have been collected and are currently being analyzed.

Enhanced Geothermal Systems, EGS Collab, Stimulati↗
DOE OSTI2020

Tuning the melting point of selected ionic liquids through adjustment of the cation’s dipole moment.

In prior research with thermally robust salts [Cassity et al., PCCP, 2017, 19, 31560] it was noted that an increase in the dipole moment of the cation generally led to a decrease in the melting point. Molecular dynamics simulations of the liquid state revealed that an increased dipole moment reduces cation-cation repulsions through dipole-dipole alignment. This was believed to reduce the liquid phase enthalpy, which would tend to lower the melting point of the IL. Here, we also test this principle by replacing hydrogen atoms with fluorine atoms at selected positions within the cation. This allows us to alter the electrostatics of the cation without substantially affecting the sterics. Furthermore, the strength of the dipole moment can be controlled by choosing different positions within the cation for replacement. We studied variants of four different parent cations paired with bistriflimide and determined their melting points, and enthalpies and entropies of fusion through DSC experiments. The decreases in the melting point were determined to be enthalpically driven. We found that the dipole moment of the cation, as determined by quantum chemical calculations, is inversely correlated with the melting point of the given compound. Molecular dynamics simulations of the crystalline and solid states of two isomers showed differences in their enthalpies of fusion that closely matched those seen experimentally. Moreover, this reduction in the enthalpy of fusion was determined to be caused by an increase in the enthalpy of the crystalline state. We provide evidence that dipole-dipole interactions between cations leads to the formation of cationic domains in the crystalline state. These cationic associations partially block favourable cation–anion interactions, which are recovered upon melting. If, however, the dipole- dipole interactions between cations is too strong they have a tendency to form glasses. This study provides a design rule for lowering the melting point of structurally similar ILs by altering their dipole moment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Robust Distribution System Load Restoration With Time-Dependent Cold Load Pickup

Service restoration is one of the critical functions to enable the future self-healing distribution system. To restore the distribution system in a timely and reliable manner, the realistic system operating conditions need to be accurately characterized. Here, two main factors that have great impacts on distribution system restoration (DSR) in practice are investigated. First, cold load pickup (CLPU), generally caused by thermostatically controlled loads (TCLs), is a common phenomenon after an outage and shaped by the outage duration. However, the time-dependent behaviors of CLPU are rarely considered in literature. In this paper, the operating state evolution of TCLs after an outage is analyzed to characterize time-dependent CLPU. And the time-dependent CLPU is analytically embedded in DSR to accurately represent the actual behaviors of the restored loads. Second, it is difficult to predict loads that fluctuate during DSR due to the lack of real-time measurement data. Accordingly, a robust DSR based on the information gap decision theory (IGDT) is proposed to address this challenge, fully considering the uncertainty of CLPU. The proposed models are tested in IEEE 13-node and 123-node test feeders. Simulation results demonstrate that the time-dependent CLPU model and the uncertainty modeling of CLPU can accurately capture the actual behaviors of loads with TCLs after an outage, which greatly improves DSR decisions in practice.

24 POWER TRANSMISSION AND DISTRIBUTION↗