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DOE OSTI2020

Efficient compressive and Bayesian characterization of biphoton frequency spectra

Frequency-bin qudits constitute a promising tool for quantum information processing, but their high dimensionality can make for tedious characterization measurements. Here we introduce and compare compressive sensing and Bayesian mean estimation for recovering the spectral correlations of entangled photon pairs. Using a conventional compressive sensing algorithm, we reconstruct joint spectra with up to a 26-fold reduction in measurement time compared to the equivalent raster scan. Applying a custom Bayesian model to the same data, we then additionally realize reliable and consistent quantification of uncertainty. Finally, these efficient methods of biphoton characterization should advance our ability to use the high degree of parallelism and complexity afforded by frequency-bin encoding.

42 ENGINEERING↗

DOE OSTI2020

Estimating Subhourly Inverter Clipping Loss From Satellite-Derived Irradiance Data: Preprint

Photovoltaic system production simulations are conventionally run using hourly weather datasets. Hourly simulations are sufficiently accurate to predict the majority of long-term system behavior but cannot resolve high-frequency effects like inverter clipping caused by short-duration irradiance variability. Direct modeling of this subhourly clipping error is only possible for the few locations with high-resolution irradiance datasets. This paper describes a method of predicting the magnitude of this error using a machine learning model and 30-minute satellite irradiance data. The method predicts a correction for each 30-minute interval with the potential to roll up into 60-minute corrections to match an hourly energy model. The model is trained and validated at locations where the error can be directly simulated from 1-minute ground data. The validation shows low bias at most ground station locations. The model is also applied to gridded satellite irradiance to produce a heatmap of the estimated clipping error across the United States. Finally, the relative importance of each predictor satellite variable is retrieved from the model and discussed.

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

DOE OSTI2022

Consensus-Based Approach for Active Power Control and Reserve Estimation in Distributed PV Systems

With the increased adoption of distributed energy resources (DER), they are expected to contribute to power system reliability services and enhance power system stability. This paper presents a distributed consensus control approach for the real-time active power reserve estimation and power management in distributed PV (photovoltaic) systems. The proposed method estimates the cumulative active power reserve from numerous PV generators using only the sparse communication network for a DER aggregator to provide active power regulation services. The real-time active power reserve estimation using the proposed approach can be used by DER aggregators to manage curtailment in distributed PV systems to maintain stipulated reserves and further to provide power system frequency regulation. Using the proposed approach, the DER aggregator only requires measurements at the feeder substation and it does not require information from individual DER units, thereby improving system resiliency. The proposed distributed consensus control method is validated on IEEE 123 testbed using PSCAD simulations.

active power reserve↗

DOE OSTI2022

Consensus-Based Approach for Active Power Control and Reserve Estimation in Distributed PV Systems: Preprint

active power reserve↗

DOE OSTI2023

Exploration of Wire Array Metamaterials for the Plasma Axion Haloscope

A plasma haloscope has recently been proposed as a feasible approach to extend the search for dark matter axions above 10 GHz (≈40 μeV), whereby the microwave cavity in a conventional axion haloscope is supplanted by a wire array metamaterial. Since the plasma frequency of a metamaterial is determined by its unit cell, and is thus a bulk property, a metamaterial resonator of any frequency can be made arbitrarily large, in contrast to a microwave cavity which incurs a steep penalty in volume with increasing frequency. To assess the actual potential of this concept as a practical dark matter haloscope, the basic properties of wire array metamaterials have been investigated through an extensive series of S 21 measurements in the 10 GHz range. This report presents some new systematics of wire array metamaterials themselves including the approach to full plasmonic behavior, the applicability of the semianalytic theory of Belov, and estimates of the loss term which bode favorably for the plasmonic haloscope application. This present work constitutes the first precision test of the semianalytic theory of Belov et al., for which the predicted plasma frequency agrees with the experimental value at the 0.1% level.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Advanced Sensor Deployment for Distribution System State Estimation and Fault Identification

Distribution systems are currently facing steep operational challenges as a result of the rapidly increasing integration of renewables and other distributed energy resources (DERs) at both the primary and secondary circuit levels. Distribution utilities and system operators have traditionally had some visibility of their primary circuits using low-frequency supervisory control and data acquisition systems, and they have had very poor if not zero visibility of the secondary circuits where the presence of DERs is constantly increasing. Therefore, this paper presents simulation studies to demonstrate the benefits of an advanced, high-fidelity sensor technology, called as the Meta-Alert System (MAS), developed by Electrical Grid Monitoring, Ltd. (EGM), on the distribution grid. First, a reliable model of the EGM sensors is developed, and then two use cases, distribution system state estimation (DSSE) and fault identification are simulated to evaluate the performance of the MAS technology. Simulation results on the Electric Power Research Institute J1 feeder demonstrate that the MAS can effectively participate in system-level DSSE programs and can detect and locate faults faster than traditional distribution protection schemes.

distribution system↗

DOE OSTI2023

Market analysis for the integration of new power technologies: A case study of the deployment of hybrid fossil-based generator plus energy storage (ES-FE)

This study examines the national landscape of hybridized fossil energy (FE) power plants with energy storage (ES) technologies (“ES-FE”) and presents the compilation of an ES-FE dataset, which includes over 65 ES-FE projects and concepts in the United States, comprising approximately 500 MWh of co-located ES capacity with FE power plants. This study also estimates the economic feasibility of adding ES to existing FE power plants by characterizing the potential revenues that can be generated by the ES component through flexibility and capacity value. The analysis focuses on ES technologies with 2- to 10-h. durations located in four U.S. independent system operators (ISOs): Midcontinent ISO (MISO), Electric Reliability Council of Texas (ERCOT), PJM Interconnection (PJM), and California ISO (CAISO), which have +70,000 MW of combined FE power capacity that could add ES. Annual revenues are estimated for the ES component using a what-if-analysis approach, for capacity value, price arbitrage, or ancillary services provision. The results show that annual revenues depend on the end-use storage service, wholesale electricity and capacity market prices, and ES technology operation parameters such as discharging duration and cycling frequency. When performing a sensitivity analysis, ES accrues $7–178/kW-yr. via price arbitrage and ancillary services provision in the four ISOs, and $13–92/kW-yr. when providing capacity value only in MISO and PJM. A cash flow analysis is performed to estimate the net present value (NPV) of the ES addition using a range of ES costs. The study finds that for most ES technologies considered, these revenues alone are insufficient to achieve economic feasibility. In conclusion, of the 1645 total runs analyzed, 115 had positive NPVs (7%). Therefore, other revenue streams or monetizable benefits are necessary to achieve the break-even point.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

The Electromagnetic Characteristics of the Tianlai Cylindrical Pathfinder Array

A great challenge for 21 cm intensity mapping experiments is the strong foreground radiation which is orders of magnitude brighter than the 21 cm signal. Removal of the foreground takes advantage of the fact that its frequency spectrum is smooth while the redshifted 21 cm signal spectrum is stochastic. However, a complication is the non-smoothness of the instrument response. This paper describes the electromagnetic simulation of the Tianlai cylinder array, a pathfinder for 21 cm intensity mapping experiments. Due to the vast scales involved, a direct simulation requires a large amount of computing resources. We have made the simulation practical by using a combination of methods: first simulate a single feed, then an array of feed units, finally with the feed array and a cylindrical reflector together, obtain the response for a single cylinder. We studied its radiation pattern, bandpass response and the effects of mutual coupling between feed units, and compared the results with observation. Many features seen in the measurement result are reproduced well in the simulation, especially the oscillatory features which are associated with the standing waves on the reflector. The mutual coupling between feed units is quantified with S-parameters, which decrease as the distance between the two feeds increases. Based on the simulated S-parameters, we estimate the correlated noise which has been seen in the visibility data, and the results show very good agreement with the data in both magnitude and frequency structures. These results provide useful insights on the problem of 21 cm signal extraction for real instruments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Compact, high-power superconducting radio-frequency accelerators for environmental applications

Electron-beam irradiation has been proven to destructively reduce or eliminate a wide variety of organic chemicals, viruses and bacteria from wastewater, as well as reducing sulfur and nitrous oxides emission from coal-fired power plants. It is estimated that there are approximately 30,000 such particle accelerators in use worldwide for industrial processes including surface and bulk processing of material, medical sterilization, and environmental remediation. Maximum beam power from accelerators used in these applications is currently limited to less than 500 kW, and a higher beam power is needed to reduce treatment costs. The market availability of continuous-wave (CW) electron-beam accelerators with power of the order of ~100 kW is also very limited. Superconducting radio-frequency (SRF) linear accelerators (linacs) are commonly used at basic research laboratories throughout the world due to their exceptionally high efficiency as compared to current industrial varieties. Recent advances in cryogenics, SRF thin films and high-power magnetrons allow for the design of increasingly compact and efficient CW SRF electron linacs in the energy range 1-10 MeV, with up to 1 MW of beam power. A new class of compact, high-efficiency electron-beam accelerators may provide cost-effective solutions for a range of industrial and environmental remediation applications, particularly with respect to tackling one such class of contaminants so-called forever chemicals, including per- and polyfluoroalkyl substances (PFASs), which are ubiquitous in a wide range of products and for which there is currently no effective destruction technology. We have recently demonstrated the key technologies required for such accelerators by: 1) operating a Nb3Sn SRF accelerating cavity cooled by commercial cryocoolers up to an accelerating gradient of 12.4 MV/m and 2) demonstrating the phase-locking as well as a high-efficiency power combining scheme for industrial magnetron transmitters. In this presentation, we will introduce the principles and benefits of MW-class SRF linacs, based on the conduction-cooled SRF technology that we have demonstrated for environmental remediation. We propose the development of a 4 MeV, 20 kW prototype to be built at Jefferson Lab as a first accelerator demonstrator unit. We will also present the results from samples study on the effect of electron-beam irradiation on so-called forever chemicals such as 1,4-dioxane and PFAS, using an existing multi-purpose 10 MeV, low-power, CW SRF linac at Jefferson Lab.

Ciovati, Gianluigi↗

DOE OSTI2023

A Smart Silicon Carbide Power Module With Pulse Width Modulation Over Wi-Fi and Wireless Power Transfer-Enabled Gate Driver, Featuring Onboard State of Health Estimator and High-Voltage Scaling Capabilities

A wide range of utility applications require controllable switches with features such as high-voltage blocking and high-current carrying capacity, especially at high pulse width modulation (PWM) frequency. Low- and medium-voltage utility applications such as motor drives and flexible AC transmission systems as well as solid state transformers could also benefit from a low-cost high-voltage switching module. Wide-bandgap semiconductors such as silicon carbide (SiC) and gallium nitride (GaN) metal oxide semiconductor field effect transistors (MOSFETs) are considered to be the present and next-generation device choices, although they have limitations. For relatively high-voltage applications with demanding thermal management, SiC is still the only choice, and GaN dominates the low-voltage regime. This manuscript proposes a new half-bridge power MOSFET module that is suitable for conventional H-bridge of multilevel configurations used in high-voltage applications. Constructed from bare SiC dies, this half-bridge module takes advantage of (1) optimized MOSFET placement inside the module, (2) customized heat exchanger, manifold, and cooling, (3) integrated gate driver module with pulse width modulation (PWM) over wi-fi to eliminate the need for low-voltage signals, (4) wireless power transfer (WPT)-enabled gate driver and other ancillary circuits, (5) and the option to incorporate an onboard state-of-health (SOH) estimator module. The entire architecture has been designed and built at the National Renewable Energy Laboratory (NREL) in Golden, CO.

Ga2O3 devices↗

DOE OSTI2024

FLOWERS AEP: An Analytical Model for Wind Farm Layout Optimization

Annual energy production (AEP) is commonly used in objective functions for wind farm layout optimization. AEP is proportional to wind farm power production integrated over an annual distribution of free-stream wind conditions. Physics-based estimates of wind farm power production typically rely on low-fidelity engineering wake models that approximate the steady-state wind farm flow field. AEP estimates are then obtained by performing independent simulations for discrete wind conditions and using rectangular quadrature to account for each condition's expected frequency of occurrence. Depending on the number of simulated discrete wind conditions, this numerical integral could be hampered by poor accuracy or high computational costs. The FLOWERS AEP model instead poses an analytical integral of the engineering wake model over the variable wind conditions, yielding a closed-form, analytical function for wind farm AEP. This paper derives the analytical functions for FLOWERS AEP and its derivatives with respect to turbine position, which are useful for gradient-based wind farm layout optimization, in nondimensional form. We then analyze the benefits of the FLOWERS AEP model over conventional reference models, focusing on its low cost, adequate wake loss predictions, and smooth design space. Although the FLOWERS approach is found to predict the exact value of AEP with some error relative to the reference model (within 14% on average), it dramatically reduces computation time by an order of magnitude, produces a qualitatively similar design space at relatively low resolution, and yields comparable optimal layouts. This significant speed improvement is critical in layout optimization applications, where determining an optimal layout in an efficient manner is more important than precise AEP prediction.

17 WIND ENERGY↗

DOE OSTI2022

Assessing entropy for catalytic processes at complex reactive interfaces

When chemical reactions are accelerated by a catalyst, entropy differences between reactants and their transient intermediates can be the driving force behind the promotion or inhibition of desired and parasitic chemical pathways. Understanding and controlling catalytic processes therefore requires both a fundamental and practicable understanding of entropy in addition to enthalpy. In unstructured media such as the vapor phase equilibrated with sparsely covered surfaces, entropy can be adequately accounted for by well-established approaches based on translational, rotational, and harmonic vibrational partition functions. However, these approximations become inadequate in more complex condensed phase environments, e.g., solid liquid interfaces of confined reaction spaces. In this chapter, we provide an overview of the state-of-art in the computational quantification of entropy and its known ramifications on catalysis. The fundamental roles of thermodynamics and kinetics in catalysis are covered in enough detail to appreciate and contextualize the computational methods employed to compute chemically accurate estimates of entropy. These methods are discussed in appropriate detail and range from the ubiquitous harmonic oscillator approximation where entropy unrelated to high frequency oscillations is typically underestimated, to enhanced free energy sampling with molecular dynamics where the desired accuracy must be weighed against the associated computational cost of obtaining it. The rising importance of machine learning and artificial intelligence in accelerating methodological progress in this field is touched upon, as well. Finally, applications, successes, and pitfalls of using these methods are provided to showcase past and present accomplishments while clarifying where improvements in both understanding and methodology are still needed.

Kollias, Loukas↗

DOE OSTI2024

Revisiting the influence of Ni particle size on the hydrogenation of CO 2 to CH 4 over Ni/CeO 2

Nickel nanoparticles were supported on CeO 2 and evaluated in the hydrogenation of CO 2 to CH 4 at 538 K and 1 atm. Chemisorption of H 2 was used to estimate the average Ni particle size, which ranged from 1.3 to 17 nm. The apparent activation energy for CH 4 formation and turnover frequency for CO 2 conversion was independent of Ni particle size. The smallest Ni particles (1.3 nm) were less selective to CH 4 . Comparisons to alumina-supported Ni reveal the same performance as Ni/CeO 2 when normalized to active Ni atoms counted by H 2 chemisorption. A beneficial effect of ceria relative to alumina is the enhanced reducibility of Ni as evaluated by H 2 temperature-programmed reduction. The constancy of the turnover frequency on Ni particles suggests the acid-base and/or redox properties of the support do not play a significant role in the CO 2 methanation reaction under the conditions of study, which contrasts many earlier works.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Theory of molecular emission power spectra. I. Macroscopic quantum electrodynamics formalism

In this work, we study the emission power spectrum of a molecular emitter with multiple vibrational modes in the framework of macroscopic quantum electrodynamics. The theory we present is general for a molecular spontaneous emission spectrum in the presence of arbitrary inhomogeneous, dispersive, and absorbing media. Moreover, the theory shows that the molecular emission power spectra can be decomposed into the electromagnetic environment factor and lineshape function. In order to demonstrate the validity of the theory, we investigate the lineshape function in two limits. In the incoherent limit (single molecules in a vacuum), the lineshape function exactly corresponds to the Franck–Condon principle. In the coherent limit (single molecules strongly coupled with single polaritons or photons) together with the condition of high vibrational frequency, the lineshape function exhibits a Rabi splitting, the spacing of which is exactly the same as the magnitude of exciton–photon coupling estimated by our previous theory [S. Wang et al., J. Chem. Phys. 151, 014105 (2019)]. Finally, we explore the influence of exciton–photon and electron–phonon interactions on the lineshape function of a single molecule in a cavity. The theory shows that the vibronic structure of the lineshape function does not always disappear as the exciton–photon coupling increases, and it is related to the loss of a dielectric environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Framework for Quantitative Evaluation of Resilience Solutions: An Approach to Determine the Value of Resilience for a Particular Site

The paper provides the approach to providing a benefit cost analysis of energy and water alternatives to provide resilience to extreme events. The approach estimates the costs and returns of providing greater resilience of water and energy infrastructure. Extreme events are defined as high impact, low-frequency events such as, but not limited to, hurricanes, floods, storm surges and earthquakes. The provides justification for hardening water and energy infrastructure. Resilience is defined as “the ability to prepare for and to withstand an extreme event with little or no damage, or to recover more quickly from an extreme event.” The approach can be summarized as follows. The approach requires the development of a baseline with which to compare alternatives. The baseline is used to evaluate the baseline’s resilience to hazards through the probability of the hazard(s), the likelihood of damage from that the hazard through a vulnerability analysis, and the consequence to calculate a cost of the damage. The approach then evaluates proposed mitigation alternatives that would improve the resilience of the system. Each alternative is evaluated based on probability of the hazard, probability of vulnerability and consequence to determine the reduced damage that each alternative presents. The approach includes any monetary and non-monetary benefits that can quantified for each of the alternatives. Non-quantifiable benefits are evaluated based on the relative importance of each alternative to the criteria used to determine how well the alternative meets the goals and objectives of the site/facility. Then, a life cycle cost analysis should be conducted for the baseline and alternatives. Finally, the results of the life cycle analysis should be presented in a decision matrix with cost, net present value, benefit/cost ratios, and any non-monetary criteria ranked to show how well the alternatives met the criteria, weighted with the decision maker’s weights and the results presented.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Estimation of High-Altitude Electromagnetic Pulse Signal Leakage into Power Generation Facilities: Simulations and Measurements

The coupling of early-time high-altitude electromagnetic pulse signals into a power generation facility was investigated. This study encompasses both electromagnetic simulation and on-site experimental efforts that are relevant to shielding effectiveness estimation with a passive technique. As an initial step in understanding the attenuation models involved, simulations were carried out as a function of frequency, building properties, and signal incidence angle. Testing was then performed at the US Department of Energy’s Oak Ridge National Laboratory campus to identify the equipment needed for signal collection and to fine-tune the experimental procedure. Finally, as an application of the models and methods presented, measurements were conducted at a power generation plant to derive the field transfer functions and coupled high-altitude electromagnetic pulse waveforms for various locations within the facility.

42 ENGINEERING↗

DOE OSTI2025

Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series

The COVID-19 pandemic has underscored the need for accurate epidemic forecasting to predict pathogen spread, evolution, and evaluate intervention strategies. Forecast reliability hinges on detailed knowledge of disease transmission across population segments, which may be inferred from contact surveys or mobility data. However, these indirect approaches make it difficult to estimate rare transmissions between socially or geographically distant communities. We show that the steep ramp-up of genome sequencing surveillance during the pandemic can be leveraged to directly identify transmission patterns between geographically defined communities. Our approach uses a hidden Markov model to infer the fraction of infections a community imports from others based on how rapidly allele frequencies in the focal community converge to those in the donor communities. Applying this method to SARS-CoV-2 sequencing data from England and the United States, we uncover networks of intercommunity transmission that reflect geographical relationships while exposing significant long-range interactions. The scaling of importation rate with distance is consistent across both countries, yet weaker than expected based on mobility data, highlighting limitations of indirect inference. We show that transmission patterns can change between waves of variants of concern and analyze how the inferred heterogeneity in intercommunity transmission impacts evolutionary forecasts. While applied here to geographically defined communities, our approach could be applied to those defined by other traits (e.g., age, socioeconomic status), provided time-series data can be stratified accordingly. Overall, our study highlights population genomic time series data as a crucial record of epidemiological interactions, which can be deciphered using tree-free inference methods.

Okada, Takashi [Department of Physics; University ↗

DOE OSTI2022

Non-Parametric Statistical Analysis of Current Waveforms through Power System Sensors

The protection, control, and monitoring of the power grid is not possible without accurate measurement devices. As the percentage of renewable energy sources penetrating the existing grid infrastructure increases, so do uncertainties surrounding their effects on the everyday operation of the power system. Many of these devices are sources of high-frequency transients. These transients may be useful for identifying certain events or behaviors otherwise not seen in traditional analysis techniques. Therefore, the ability of sensors to accurately capture these phenomena is paramount. In this work, two commercial-grade power system distribution sensors are investigated in terms of their ability to replicate high-frequency phenomena by studying their responses to three events: a current inrush, a microgrid “close-in”, and a fault on the terminals of a wind turbine. Kernel density estimation is used to derive the non-parametric probability density functions of these error distributions and their adequateness is quantified utilizing the commonly used root mean square error (RMSE) metric. It is demonstrated that both sensors exhibit characteristics in the high harmonic range that go against the assumption that measurement error is normally distributed.

47 OTHER INSTRUMENTATION↗