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DOE OSTI2022

Optimal Gas-Electric Energy System Decarbonization Planning

As energy utilities implement climate change mitigation policies, system planners require strategies for achieving affordable emissions reductions. Coordinated planning of electric power and natural gas systems will allow synergistic investments to address cross-sector operational constraints, competing uses for net-zero emissions fuels, and shifts in energy demands across energy carriers. In this study, we develop a novel optimization program that finds the cost-minimizing mix of infrastructure expansion or reduction across gas and electric systems to satisfy sector-specific emissions constraints. Alongside energy supply resources, our framework allows for central-planning of end-use equipment stocks to allow switching between gas and electric appliances upon failure or premature replacement. The proposed model is used to simulate case study scenarios for a benchmark 24-pipe gas network coupled to a 24-node power system test network. We find that electrification of greater than 80% of core gas demands is a component of the least-cost solution for modeled energy systems. Despite this substitution, the gas system is maintained to service difficult-to-electrify customers and to deliver net-zero emissions gas to electricity generators in times of peak electricity demand. Restricting electrification of gas appliances increases reliance on power- to-gas technologies and increases annual costs by 15% in 2040. Neglecting constraints on pipeline blending of hydrogen can produce a misleading result that relies on hydrogen blend fractions of greater than 50%. In all cases, we find the average costs of delivered gas increase nearly 5-fold across the decarbonization transition, highlighting the importance of future work investigating cost-allocation strategies for ensuring an equitable energy transition.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Evaluating grid stress and reliability in future electricity grids across a range of demand, generation mix, and weather trends

The reliability of power grids in the future will depend on how system planners account for the integration of new technologies, extreme weather events, and uncertainties in demand growth from increased electrification and data centers. This study introduces an open-source, multisectoral, multiscale modeling framework that projects grid stress and reliability trends between 2020 and 2055 in the Western Interconnection of the United States. The framework integrates global to national energy-water-land dynamics with power plant siting and hourly grid operations modeling. We analyze future wholesale electricity price shocks and unserved energy events across eight scenarios spanning a range of population growth and economic change, generation mixes, and weather conditions. Our results show future grids with high percentage of non-renewable generation and strong economic growth are characterized by higher reliability and lower wholesale electricity prices than lower growth scenarios because of larger reliance on dispatchable generators and lower fossil fuel extraction costs. Scenarios with high percentage of renewable resources have lower median but more volatile wholesale electricity prices as well as more frequent and severe unserved energy events compared to scenarios relying more on dispatchable generators. These events occur because higher proportion of solar and wind energy causes net demand curves to deepen during midday (duck curves get progressively severe), exacerbating the challenge of meeting demand during summer evening peaks. This study suggests that robust and co-optimized transmission and energy storage planning could help maintain low wholesale electricity prices and high reliability levels in future electricity grids across uncertainties in generation mixes.

Electric grid reliability↗

DOE OSTI2022

3D-printed electrically conductive silicon carbide

The development of electrically conductive ceramics could achieve robust mechanical strength as well as practically high conductivity, offering applications in structural electrodes, conductors, catalyst supports, etc. However, its operating temperature is limited due to the intrinsic dense structures inevitably hindering the thermal management capability, thus resulting in a temperature-dependent electrical behavior in high-temperature environments. In this work, we report an additive manufacturing protocol through vat photopolymerization 3D printing to fabricate the architectured conductive silicon carbide (SiC) ceramics that simultaneously possess high electrical conductivity as well as low thermal conductivity, and demonstrate electric reliability under high-temperature environments above 600°C. The percolation of graphene into the ceramic scaffold establishes a uniform conductive network, exhibiting its electrical conductivity up to 1000 S m –1 . The bulk density of the 3D-printed ceramic is measured from 0.366 g cm –3 to 0.897 g cm –3 , with thermal conductivity ranging from 62 mW m –1 K –1 to 88 mW m –1 K –1 . Furthermore, the mechanical performance of conductive ceramic can be effectively reinforced by densifying the microstructures via spark plasma sintering treatment. The proposed additive manufacturing strategy widens the potential of ceramics as a structural and functional material, offering a promising pathway toward high-temperature electronics applications.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Characterizing patterns and variability of building electric load profiles in time and frequency domains

The rapid development of advanced metering infrastructure provides a new data source—building electrical load profiles with high temporal resolution. Electric load profile characterization can generate useful information to enhance building energy modeling and provide metrics to represent patterns and variability of load profiles. Such characterizations can be used to identify changes to building electricity demand due to operations or faulty equipment and controls. In this study, we proposed a two-path approach to analyze high temporal resolution building electrical load profiles: (1) time-domain analysis and (2) frequency-domain analysis. Furthermore, the commonly adopted time-domain analysis can extract and quantify the distribution of key parameters characterizing load shape such as peak-base load ratio and morning rise time, while a frequency-domain analysis can identify major periodic fluctuations and quantify load variability. We implemented and evaluated both paths using whole-year 15-minute interval smart meter data of 188 commercial office building in Northern California. The results from these two paths are consistent with each other and complementary to represent full dynamics of load profiles. The time- and frequency-domain analyses can be used to enhance building energy modeling by: (1) providing more realistic assumptions about building operation schedules, and (2) validating the simulated electric load profiles using the developed variability metrics against the real building load data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Data-Driven Simulation-Based Planning for Electric Airport Shuttle Systems: A Real-World Case Study

Many airports are adopting battery electric buses in their shuttle fleets due to concerns over air quality and regulations. This study proposes a simulation-based optimization modeling framework to help airport shuttle operators effectively deploy electric buses. We evaluated a planned airport electric shuttle system with an event-driven simulator. Empirical data collected from existing systems were used to drive the simulations. We then proposed a simulation-based optimization model to determine the battery capacity, charging power, and number of chargers so that predefined objective(s) (e.g., minimizing total capital cost, minimizing emissions) are optimized. Compared to existing studies, the primary contribution of the proposed method is that it can model the real-world stochastic nature of operations in an electric bus system with much higher fidelity. To demonstrate the proposed modeling framework, we study a real-world shuttle system at the Dallas-Fort Worth International Airport, and present extensive numerical studies. When considering partial fleet electrification, the model can provide a set of Pareto optimal solutions. When considering full fleet electrification, the optimal solution requires a 50-kWh battery capacity and four 210-kW chargers, resulting in a total capital cost of $26,744,000. The results demonstrate that the proposed modeling framework can effectively optimize the planning of electric airport shuttle systems with partial or full fleet electrification.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

DOE OSTI2025

Experimental validation of a co-simulation architecture for modeling whole-building and detailed electrical distribution performance

This article presents an experimental validation of a co-simulation architecture for simultaneously modeling whole-building energy performance and detailed building electrical distribution system performance. The co-simulation architecture consists of a whole-building energy model (EnergyPlus®) embedded within a Modelica-based building electrical distribution system library called the Building Electrical Efficiency Analysis Model (BEEAM) using the Functional Mock-up Interface standard. We validate the model using experimental data collected at a full-scale test cell within Lawrence Berkeley National Laboratory’s FLEXLAB® facility. In conclusion, we show that the co-simulation model accurately predicts the electrical, mechanical, and thermal performance of the test cell for typical loads with both an AC and a DC electrical distribution topology.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Hydrogen underground storage for grid electricity storage: An optimization study on techno-economic analysis

Here, this study performs a techno-economic analysis of hydrogen underground storage systems for grid electricity storage, evaluating their economic viability at the plant scale using dynamic optimization. It explores the feasibility of various system configurations and revenue models in the context of volatile electricity prices and the necessity for multiple revenue streams. The hypothesis tested is that large-scale hydrogen storage, despite its low round-trip efficiency, can be economically viable with the right mix of revenue streams. This study uses scenario-based analysis to assess the impacts of different system configurations, including engaging in time-shifting arbitrage, ancillary service markets and blending hydrogen with natural gas. Results indicate potential annual net cash flows of up to $\$$1.5 million from ancillary services integration and $\$$5.2 million from natural gas blending, contingent on specific system sizes. The study concludes that hydrogen underground storage for grid electricity storage can be profitable, and emphasizes that proper system design and precise electricity price forecasting are crucial for optimizing system performance and economic returns. This research sets the stage for further investigations into the scalability of hydrogen storage systems and their broader implications for grid electricity storage and energy market dynamics.

25 ENERGY STORAGE↗

DOE OSTI2020

Determination of neutron irradiation temperatures of SiC using electrical resistivity method

The irradiation temperature of silicon carbide (SiC) was determined post-irradiation by examination of the recovery of the electrical resistivity due to thermal annealing in a rapid heating/cooling optical furnace. High-purity, high-resistivity grade SiC is routinely used as a passive temperature monitor in neutron irradiation studies at the High Flux Isotope Reactor (HFIR), and this paper presents an alternative automated technique for determination of the irradiation temperature the SiC experienced. Neutron collisions with the atoms results in displaced lattice atoms (interstitials) that act as electron donors yielding a significant decrease in electrical resistivity. The irradiation defects become thermodynamically unstable and start to recombine, when annealed above the irradiation temperature, resulting in a recovery of the electrical resistivity. The resistivity is measured at a fixed elevated temperature above ambient, which is below the target irradiation temperature. When the resistivity is plotted as a function of annealing temperatures, a clear increase is observed due to the recovery of irradiation defects. We have demonstrated that this electrical resistivity measurement of SiC is effective to determine irradiation temperature of SiC. In conclusion, energy levels of various defects in SiC were calculated from Arrhenius plots of electrical conductivity versus inverse temperature.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Hydrogen effects on thermal diffusivity and electrical resistivity of zircaloy cladding

Thermal diffusivity measurements on Zirconium-based cladding materials have historically been a challenge due to the difficulty to measure on specimens with curved geometries, including nuclear grade Zircaloy cladding materials. Here, in this work, we first used laser flash analysis method and four-probe configuration method to measure the thermal diffusivity and electrical resistivity of Zircaloy tubes respectively, which show good agreement with Zircaloy plates in this work, as well as previously published data. The consistent results proved the applicability of the laser flash analysis setup and four-probe configuration method for investigating thermal diffusivity and electrical resistivity of Zircaloy tubes. We further investigated the hydrogen effect on thermal diffusivity and electrical resistivity of Zircaloy. Hydrogen plays significant roles in the thermal diffusivity of Zircaloy, which depends on the hydrogen concentration. For higher hydrogen contents (1130 and 1820 wppm in this work), where phase transformation (α-Zr + δ-hydride → α-Zr + β-Zr) occurs at 567 °C, thermal diffusivity decreases as a function of temperature at the α-Zr + δ-hydride phase regime, while increase at higher temperature at the α-Zr + β-Zr phase regime. For low hydrogen concentration, where hydride dissolved into α-Zr matrix phase at higher temperature, the thermal diffusivity is lower than non-hydrided Zircaloy-4 with similar temperature-dependent trends. Such observation demonstrates the hydrogen effects on reducing thermal diffusivity of α-Zr phase. Hydrogen increases the electrical resistivity of Zircaloy. Similar to thermal diffusivity results, the phase transformation causes a reversal of temperature-dependent trends in electrical resistivity results in Zircaloy-4 with higher hydrogen contents.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Charging needs for electric semi-trailer trucks

Battery-electric vehicles provide a pathway to decarbonize heavy-duty trucking, but the market for heavy-duty battery-electric semi-trailer trucks is nascent, and specific charging requirements remain uncertain. We leverage large-scale vehicle telematics data (>205 million miles of driving) to estimate the charging behaviors and infrastructure requirements for U.S. battery-electric semi-trailer trucks within three operating segments: local, regional, and long-haul. We model two types of charging - mid-shift (fast) and off-shift (slow) - and show that off-shift charging at speeds compatible with current light-duty charging infrastructure (i.e., =350 kW) can supply 35% to 77% of total energy demand for local and regional trucks with =300-mile range. Megawatt-level speeds are required for mid-shift charging, which make up 44% to 57% of energy demand for long-haul trucks with =500-mile range. However, demand shifts from mid-shift to off-shift charging as the range for battery-electric trucks increases and when off-shift charging is widely available. Finally, we observe geographic trends in charging demand, finding that local trucks have greater demand within urban areas, whereas long-haul trucks have more demand along rural interstate corridors. As the range for battery-electric trucks increases, we show that charging demand shifts from rural to urban locations due to observed vehicle dwell tendencies.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

Operational optimization for multi-functional charging station with electric and hydrogen-powered vehicles

The rapid adoption of electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs), combined with global efforts to reduce carbon emissions, has accelerated the development of EV charging and hydrogen refueling stations. In response to this demand, this paper introduces the concept of Multi-Functional Charging Station (MFCS) that integrates power generation, EV charging, battery swapping, and hydrogen refueling. A comprehensive operational model is developed for the MFCS that couples electricity and hydrogen conversion and storage technologies to enhance infrastructure utilization and improve overall system efficiency. The model also considers multiple revenue streams, including participation in energy and ancillary markets. To validate the effectiveness of the proposed model and evaluate its performance, a series of numerical experiments are conducted with different charger numbers, different electricity purchase limits, and different charger allocations. Numerical results demonstrate that shared charger configurations can lead to 8.11 % improvement in operational profit by improving resource utilization and reducing the number of depleted batteries at the end of operations compared to allocated charger setups. By varying the number of chargers, sensitivity analysis identifies diminishing marginal returns beyond about 45 chargers, suggesting it as an optimal sizing point under current settings. The integration of electricity and hydrogen conversion is also explored under scenarios with limited external electricity purchases. In conclusion, these findings indicate that optimizing charger allocation and energy management can significantly enhance station productivity and profitability, ultimately supporting the broader adoption of electrified and hydrogen-based transportation solutions.

Charging station↗

DOE OSTI2020

Refueling infrastructure planning in intercity networks considering route choice and travel time delay for mixed fleet of electric and conventional vehicles

The range anxiety has been a major factor that affects the market acceptance of electric vehicles. Even with the recent development of battery technologies, a lack of charging stations and range anxiety are still significant concerns, specifically for intercity trips. This calls for more investments in building charging stations and advancing battery technologies to increase the market share of electric vehicles and improve sustainability. This study suggests a configuration for plug-in electric vehicle charging infrastructure to support long-distance intercity trips of electric vehicles at the network level. A model is proposed to minimize the total system cost including infrastructure investment (building charging stations/spots) and travel time delays (charging time, waiting time in the queue, and detour time to access charging stations). This study fills existing gaps in the literature by capturing realistic patterns of travel demand and considering flow-dependent charging delays at charging stations. Furthermore, the proposed model, which is formulated as a mixed-integer program with nonlinear constraints, solves the optimization problem at the network level. At the network level, impacts of charging station locations on the traffic assignment problem with a mixed fleet of electric and conventional vehicles need to be considered. To this end, a traffic assignment module is integrated with a simulated annealing algorithm. The numerical experiments show a satisfactory application of the model for a full-scale case study (intercity network in Michigan). The solution quality and efficiency of the proposed solution algorithm are evaluated against those of an enumeration approach for a small case study. The results suggest that even for the current market share and charging stations’ setting, a significant investment is needed to support intercity trips without range anxiety issues and with acceptable delays. Additionally, through sensitivity analyses, the required infrastructure and battery investments to support intercity trips with acceptable delays are established for hypothetical increased market shares and battery size in the future.

42 ENGINEERING↗

DOE OSTI2022

Joint routing of conventional and range-extended electric vehicles in a large metropolitan network

Range-extended electric vehicles combine the higher efficiency and environmental benefits of battery-powered electric motors with the longer mileage and autonomy of conventional internal combustion engines. This combination is particularly advantageous for time-constrained delivery routing in dense urban areas, where battery recharging along routes can be too time-consuming to economically justify the use of all-electric vehicles. However, switching from electric to conventional fossil fuel modes also results in higher costs and emissions and lower efficiency. This paper analyzes this heterogeneous vehicle routing problem and describes two solution methods: an exact branch-price-and-cut algorithm and an iterated tabu search metaheuristic. From a methodological perspective, we find that the exact algorithm consistently obtains tight lower bounds that also serve to certify the metaheuristic solutions as near-optimal. From a policy standpoint, we examine a large-scale real-world case study concerning parcel deliveries in the Chicago metropolitan area and quantify various operational metrics including energy costs and vehicle miles traveled. We find that by deploying roughly 20% of range -extended vehicles with a modest all-electric range of 33 miles, parcel distributors can save energy costs by up to 17% while incurring less than 0.5% increase in vehicle miles traveled. Increasing the range to 60 miles further reduces costs by only 4%, which can alternatively be achieved by decreasing the average service time by 1 minute or increasing driver working time by 1 hour. In conclusion, our study reveals several key areas of improvement on which vehicle manufacturers, distributors, and policy makers can focus their attention.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2026

pyEF: A Python Framework for QM and QM/MM Atom-Wise Electric Field Analysis

We introduce pyEF, a software package for computing molecular electric fields, electrostatic interaction energies, and electrostatic potentials from quantum mechanical (QM) atom-centered multipole expansions with atom-wise decomposable contributions. We demonstrate the computational efficiency and accuracy of this QM-derived electric field evaluation tool through several tests. To assess the influence of the underlying QM method and charge partitioning scheme on these electrostatic quantities, we analyze over 250 configurations of an acetone solute molecule in five solvents of variable polarity. We find that electric field calculations are highly sensitive to the choice of charge partitioning method. Even among real-space charge schemes, acetone Stark tuning rates differ by up to a factor of 2. Benchmarking computed solvent dipole moments against experimental bulk values, we conclude that the CM5, ADCH, and Hirshfeld-I charge schemes most reliably capture solvent electrostatics and therefore provide a more faithful foundation for computing electric fields. When constructed from these real-space charges, electric fields are nearly insensitive to basis set size and monotonically increase in magnitude with higher Fock exchange. We also demonstrate efficient convergence of QM electrostatics when more distant molecules are represented solely by MM point charges, reducing computational overhead. Leveraging these findings, we demonstrate the use of pyEF to deduce environmental effects on a transition metal complex from a Ga 4 L 6 12– nanocage and quantify the dominant role of organic linkers in orchestrating electrostatic preorganization.

electric fields↗

DOE OSTI2024

Fabrication and Performance Evaluation of Double-Sided Copper Nanowire Arrays as Thermal and Electrical Interfacial Layers

Reducing contact interface thermal and electrical resistances is in great demand across various industries, particularly in the semiconductor industry. This study introduces an approach using double-sided copper nanowire (Cu NW) arrays on copper sheets as both thermal and electrical interfacial layers, designed to effectively accommodate the topographical inconsistencies between contact surfaces. Further, experimental outcomes reveal a significant reduction in thermal contact resistance (TCR), with a value of 2.5 mm 2 K W –1 , thereby exceeding the efficiency of reported nanostructural thermal interface materials (TIMs). Additionally, when utilized as an electrical interfacial layer, these double-sided Cu NWs arrays dramatically reduced electrical contact resistance (ECR), outperforming traditional conductive grease in applications necessitating separable bonding, though showing comparable performance to costly silver-based conductive epoxies required for permanent, inseparable bonds. The promising results of the double-sided Cu NWs arrays in reducing both TCR and ECR, confirmed by finite element simulation, highlight their substantial potential in advancing TIMs and electrical interconnection applications across various sectors.

42 ENGINEERING↗

DOE OSTI2024

Electrical Conductivity and Sound Velocities of Talc Under High Pressure and High Temperature Conditions and Application to the Subducting Cocos Plate

Talc is expected to be an important water carrier in Earth's upper mantle, and understanding its electrical and seismic properties under high pressure and temperature conditions is required to detect possible talc-rich regions in subduction zones imaged using geophysical observations. Here, we conducted acoustic and electrical experiments on natural talc aggregates at relevant pressure-temperature conditions. Compressional wave velocity (V p ) was measured using ultrasonic interferometry in a Paris-Edinburgh press at pressures up to 3.4 GPa and temperatures up to 873 K. Similar Vp values are obtained regardless of the initial crystallographic preferred orientation of the samples, which can be explained by talc grain reorientation during the experiment, with the (001) plane becoming perpendicular to the uniaxial compression axis. Electrical conductivity of the same starting material was determined using impedance spectroscopy in a multi-anvil press up to 6 GPa and 1263 K. Two conductivity jumps are observed, at ∼860–1025 K and ∼940–1080 K, depending on pressure, and interpreted as talc dehydroxylation and decomposition, respectively. Electrical anisotropy is observed at low temperature and decreases with increasing pressure (∼10 at 1.5 GPa and ∼2 at 3.5 GPa). Comparison of acoustic and electrical results with geophysical observations in central Mexico supports the presence of a talc-bearing layer atop the subducted Cocos plate.

Cocos plate↗

DOE OSTI2026

Bounding the costs of electric vehicle managed charging—supply curves for scenarios from 2025 to 2050

As electric vehicle (EV) adoption increases, the resulting EV battery charging will increase demand on the electric power grid. Through EV managed charging (EVMC) programs, charging can be shifted in time to support electric grid reliability and reduce electricity costs. EVMC can offer an alternative to additional supply-side generation, but the costs of EVMC implementation must be understood to evaluate the cost-benefits of EVMC. This paper presents bottom-up, forward-looking (from 2025 through 2050) estimates of the incremental costs associated with different EVMC dispatch mechanisms available to electric utilities. The costs of enabling EVMC for a range of customer participation levels are presented in the form of supply curves, which provide per-EV costs for a targeted level of participation. The largest drivers of cost variation are assumptions about future charging flexibility paradigms described in four scenarios. These supply curves can be used to quantify the expected costs of EVMC programs and enable comparison with supply-side or other demand flexibility alternatives.

25 ENERGY STORAGE↗

DOE OSTI2020

Pumped Thermal Electricity Storage with Supercritical CO2 Cycles and Solar Heat Input

Pumped Thermal Electricity Storage (PTES) is an energy storage device that uses grid electricity to drive a heat pump that generates hot and cold storage reservoirs. This thermal potential is later used to power a heat engine and return electricity to the grid. In this article, a PTES variant that uses supercritical carbon dioxide (sCO2) as the working fluid is introduced. sCO2-PTES cycles have higher work ratios and power densities than the systems based on ideal gases that have been investigated to date. Furthermore, sCO2- PTES cycles may achieve higher round-trip efficiencies for a given hot storage temperature (up to 78% at 560°C). The sensitivity of PTES cycles to loss factors such as isentropic efficiencies and temperature differences between the power cycle and storage fluid is investigated. A second concept whereby an sCO2- PTES cycle is integrated with concentrating solar power (CSP) is introduced. This concept ‘time-shifts’ the recompression of an sCO2 recompression cycle to a period of lower electricity prices and stores the heat. When solar heat is dispatched, the recompressor may be avoided as the required heat is obtained from storage, thereby leading to increased heat engine efficiencies. The net work output of this integrated system is 10-18% greater than the conventional recompression cycle. Combining PTES with a CSP power cycle is therefore shown to improve the dispatch of solar heat as well as providing electricity storage services.

41 EE - Solar Energy Technologies Office (EE-4S)↗