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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Semi-Supervised Disaggregation of Load Profiles at Transmission Buses with Significant Behind-the-Meter Solar Generations

It is of imperative interests for regional transmission organizations (RTOs) to effectively extract daily load profiles at transmission buses, which remains a gap in existing technology paradigm. This digest proposes an explicit yet efficient linear estimator, to disaggregate metered load profiles at buses with significant behind-the-meter (BTM) solar generations in a data driven manner. The proposed estimator is based on utility zonal load profiles and proxy solar irradiance profiles, which in reality is the aggregated waveform at each transmission bus and equivalent to the mix of summed load profiles minus actual BTM solar generation. To overcome technical challenges in the lack of “ground truth” and validate the performance of supervised learning algorithms, we propose semi-supervised mechanisms with parameter tuning, and leverage the unique characteristics of zero-crossing points in BTM solar peaking behaviors.

machine leaning, behind-the-meter, power grid anal↗

DOE OSTI2024

Bilevel Nodal Behind-the-meter Solar Disaggregation Under Unexpected Extreme Weather Conditions

As the power grid undergoes significant paradigm shift due to the increasing penetration of renewable generation, the ever-growing installation of behind-the-meter (BTM) solar generation in the power grid also has a significant impact on nodal loads, posing challenges on transmission operators. Furthermore, increasing frequent and severe extreme weather events intertwine with ubiquitous BTM solar generations and have amplified the challenges of accurately model nodal load profiles, especially under the lack of ground-truth information for verification. To tackle these challenges, this paper introduces a bilevel model that utilizes year-long data (e.g., proxy solar, zonal load, and individual node load profiles) to disaggregate metered profiles into actual demand and BTM solar generation at each transmission node. The proxy solar not only scales the BTM solar generation of individual nodes but also create a compensation term for enhancing performance on days with unexpected extreme weather events. The proposed algorithm is validated with real-world PJM Interconnection data during unexpected events like the recent Winter Storm Elliott. For quantitative evaluations, a novel Score error is introduced, which is based on mean percentages and load scales and offers a universal assessment method suitable for all nodes and different data formats (e.g., normalized or raw values).

behind-the-meter solar, load disaggregations, load↗

DOE OSTI2021

Design of Resilient Electric Distribution Systems for Remote Communities: Surgical Load Management using Smart Meters

This paper describes a systematic process of designing resilient electric distribution systems and microgrids using smart meters for surgical load management (SLM) as part of Advanced Metering Infrastructure (AMI). The work focuses on selection approach, integration, and interoperability aspects for AMI in microgrids. SLM is proposed as a granular control methodology for serving selective critical loads across different distribution feeders in the system during extreme events. The surgical load shedding as well as load pick-up provides a robust approach for maximizing critical load served in a resource-constrained electric distribution system or a microgrid. We present the case of a 20 MW islanded microgrid in Cordova, AK, USA, which is the demonstration site for field validation of resilience enhancement technologies for the DOE-funded Grid Modernization project RADIANCE. Cordova microgrid is an islanded distribution grid that provides an environment to prove the approach, and the techniques may also be applicable to other regional distribution systems.

microgrids↗

DOE OSTI2023

Loose Belt Fault Detection and Virtual Flow Meter Development Using Identified Data-driven Energy Model for Fan Systems

An energy model that correlates fan airflow, head, speed, and system power input is essential to detect device faults and optimize control strategies in fan systems. Since the application of variable-frequency drives (VFDs) makes the motor-efficiency data published by manufacturers inapplicable for VFD–motor–fan systems, the fan efficiency and drive (belt–motor–VFD) efficiency must be identified for each individual system to obtain accurate energy models. The objectives of this paper are to identify an energy model of existing VFD–motor–fan systems using available experimental data and demonstrate its applications in loose belt fault detection and virtual airflow meter development for optimal control. First, an approach is developed to identify the fan head, fan efficiency, and drive-efficiency curves using available fan head, speed, and system power input as well as temporarily measured airflow rate without measuring shaft power. Then, the energy model is identified for an existing VFD–motor–fan system. Finally, the identified model is applied to detect the slipped belt faults and develop the virtual airflow meter. The experiment results reveal that the developed approach can effectively obtain the energy model of VFD–motor–fan systems and the model can be applied to effectively detect slipped belt faults and accurately calculate the fan airflow rate.

42 ENGINEERING↗

DOE OSTI2021

Design of Resilient Electric Distribution Systems for Remote Communities: Surgical Load Management Using Smart Meters: Preprint

microgrids↗

DOE OSTI2024

Towards Non-Intrusive Real-Time Monitoring of Behind the Meter Residential Distributed Energy Resources

The growing adoption of residential distributed energy resources (DERs) introduces more uncertain variability in power grid operation. More importantly, the residential DERs operate behind customers’ energy meters, and therefore, the utility cannot “directly” monitor them. Prior approaches to enable visibility into behind-the-meter (BTM) DERs either depend on estimations or require intrusive instrumentation on the customer side. To address the critical need for direct real-time monitoring of BTM DERs, in this paper, we propose a novel approach for utility-side direct real-time monitoring of residential BTM DERs. We utilize high-frequency (> 10kHz) conducted electromagnetic interference (EMI) from residential DERs’ grid-tied inverters to monitor their power generation. We discuss the working principle of our approach and present supporting results using three of-the-shelf grid-tied inverters.

14 SOLAR ENERGY↗

DOE OSTI2024

Workshop: Advanced Metering for Decarbonization: Electric Vehicles and 24/7 Carbon-Free Electricity

The purpose of this workshop is to learn more about advanced metering best practices for meeting the goals of EO 14057. This will be a 2-part session, first part to include presentations on the FEMP best practice work related to metering: 1) Electric Vehicles (EVs) and EV charging station electricity use. 2) Integrating data sources to calculate hourly carbon pollution-free electricity (CFE). Second part will facilitate small group discussions with a problem-solving activity.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

DOE OSTI2022

An analytical method for identifying synergies between behind-the-meter battery and thermal energy storage

Electric utilities build generation capacity to meet the highest demand period, and they often pass on the costs associated with these peaking generators to building owners through demand charges. Building owners can minimize these demand charges by shifting energy use away from peak periods with behind-the-meter storage. This storage can include batteries, which can directly shift the metered load, or thermal energy storage, which can shift thermal-driven electric loads like air conditioning. However, there is a lack of research on how best to combine battery and thermal energy storage. In this study, we develop an analytical sizing method to calculate the potential demand reduction and annualized cost savings for different combinations of thermal and battery energy storage sizes. We show that adding batteries to a thermal energy storage system can increase the total system's load shaving potential. This is particularly true when the building has onsite photovoltaic generation or electric vehicle charging, which add significant variability to the load shape. We also show that for a given total storage size, selecting a higher fraction of thermal energy storage can significantly lower the cycling of the battery, and therefore extend the battery life. This, combined with the expected lower first cost of thermal energy storage materials compared to batteries, shows that hybrid energy storage systems can outperform a standalone battery or standalone thermal storage system. Assuming the thermal storage has a capital cost 6x lower than the battery, our analysis shows that the optimal system is 71% thermal energy storage and 29% battery energy storage for a scenario with electric vehicle charging. The annualized cost savings for this system are $48.6 k/yr, whereas an equivalently sized standalone thermal energy storage system would provide annualized cost savings of $28.5 k/yr and a standalone battery would lead to savings of $8.72 k/yr. The hybrid system also reduces battery cycling by 52% compared to a standalone battery, extending battery lifetime.

25 ENERGY STORAGE↗

DOE OSTI2024

The importance of sub-meter-scale snow roughness on conductive heat flux of Arctic sea ice

Abstract The conductive heat flux through the snow and ice is a critical component of the mass and energy budgets in the Arctic sea ice system. We use high horizontal resolution (3–15 cm) measurements of snow topography to explore the impacts of sub-meter-scale snow surface roughness on heat flux as simulated by the Finite Element method. Simulating horizontal heat flux in a variable snow cover modestly increases the total simulated heat flux. With horizontal heat flux, as opposed to simple 1D-vertical heat flux modeling, the simulated heat flux is 10% greater than that for uniform snow with the same mean snow thickness for a 31.5 × 21 m region of sea ice (the largest region we studied). Vertical-only (1D) heat flux simulates just a 6% increase for the same region. However, this is highly dependent on observation resolution. Had we measured the snow cover at 1 m horizontal spacing or greater, simulating horizontal heat flux would not have changed the net heat flux from that simulated with vertical-only heat flux. These findings suggest that measuring and modeling snow roughness at sub-meter horizontal scales may be necessary to accurately represent horizontal heat flux on level Arctic sea ice.

Geology↗

DOE OSTI2022

Development of a hardened THz energy meter for use on the kilojoule-scale, short-pulse OMEGA EP laser

A highly adaptable and robust terahertz (THz) energy meter is designed and implemented to detect energetic THz pulses from high-intensity (>10 18 W/cm 2 ) laser–plasma interactions on the OMEGA EP. THz radiation from the laser driven target is detected by a shielded pyrometer. A second identical pyrometer is used for background subtraction. The detector can be configured to detect THz pulses in the 1 mm to 30 μm (0.3- to 10-THz) range and pulse energies from joules to microjoules via changes in filtration, aperture size, and position. Additional polarization selective filtration can also be used to determine the THz pulse polarization. The design incorporates significant radiation and electromagnetic pulse shielding to survive and operate within the OMEGA EP radiation environment. We describe the design, operational principle, calibration, and testing of the THz energy meter. The pyrometers were calibrated using a benchtop laser and show linear sensitivity to up to 1000 nJ of absorbed energy. Furthermore, the initial results from four OMEGA EP THz experiments detected up to ~15 μJ at the detector, which can correspond to hundreds of mJ depending on THz emission and reflection models.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Generation of meter-scale hydrogen plasmas and efficient, pump-depletion-limited wakefield excitation using 10 GeV electron bunches

High repetition rates and efficient energy transfer to the accelerating beam are important for a future linear collider based on the beam-driven plasma wakefield acceleration scheme (PWFA-LC). This paper reports the first results from the Plasma Wakefield Acceleration Collaboration (E300) that are beginning to address both of these issues using the recently commissioned FACET-II facility at SLAC national accelerator laboratory. Here we have generated meter-scale hydrogen plasmas using time-structured 10 GeV electron bunches from FACET-II, which hold the promise of dramatically increasing the repetition rate of PWFA by rapidly replenishing the gas between each shot compared to the hitherto used lithium plasmas that operate at 1–10 Hz. Furthermore, we have excited wakes in such plasmas that are suitable for high gradient particle acceleration with high drive-bunch to wake energy transfer efficiency- a first step in achieving a high overall energy transfer efficiency. We have done this by using time-structured electron drive bunches that typically have one or more ultra-high current (> 30 kA) femtosecond spike(s) superimposed on a longer (~0.4 ps) lower current (< 10 kA) bunch structure. The first spike effectively field-ionizes the gas and produces a meter-scale (30–160 cm) plasma, whereas the subsequent beam charge creates a wake. The length and amplitude of the wake depends on the longitudinal current profile of the bunch and plasma density. We find that the onset of pump depletion, when some of the drive beam electrons are nearly fully depleted of their energy, occurs for hydrogen pressure ≥ 1.5Torr. We also show that some electrons in the rear of the bunch can gain several GeV energies from the wake. These results are reproduced by particle-in-cell simulations using the QPAD code. At a pressure of ~2Torr, simulation results and experimental data show that the beam transfers about 60% of its energy to the wake.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Deep-learning-based canopy height model generation from sub-meter resolution panchromatic satellite imagery

Canopy height models (CHMs) with sufficient resolution to distinguish individual trees are useful for a variety of applications. However, standard techniques to acquire such data, such as airborne lidar surveying, are often prohibitively expensive. Deep learning techniques for generating CHMs from high-resolution imagery are an attractive option to reduce costs. To date, success with these methods has been demonstrated using multichannel aerial photography and specialized satellite data products derived from multiple sensors, neither of which is commonly available at temporal resolutions finer than one year. Here we demonstrate a method to generate sub-meter resolution CHMs in three forests in California using a more abundant data source: sub-meter resolution, panchromatic satellite imagery from a single sensor. We show that phenology and species composition play important roles in model transferability; when trained using imagery from a single conifer forest in autumn, the model performs well on autumn imagery from a second conifer forest several hundred kilometers distant with no re-training. With modest additions to the training dataset, the same model generates minimally biased estimates of canopy height in both conifer and deciduous forests during multiple seasons. Because the model operates on satellite data with global coverage and a relatively short return interval, we propose its suitability to extrapolate tree-level canopy height data to remote regions and conduct high-temporal resolution monitoring of forest structure. We furthermore demonstrate the workflow’s applicability to fire modeling by conducting simulations in forests populated by trees measured using both this approach and airborne lidar surveying. We find minimal differences in fire behavior relative to a baseline case in which only statistical distributions of tree height and crown area are known. This result underscores the value of forest structural information derived from our workflow for improving the fidelity of wildland fire simulations, among other ecological applications.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Behind-the-Meter Energy Storage and Generation in Support of Electrified Rental Car Centers

Electrification of rental car centers at major airports is expected to generate tens of MW in additional power loads. The magnitude of these loads poses challenges including high utility costs, expensive and lengthy distribution capacity upgrades, and disruptions to traditional operation. Behind-the-meter stationary battery storage and onsite photovoltaic generation offer a viable solution to these challenges without impacting the operation and business model of rental car companies, defined by minimal fleet inventory and short vehicle dwell time. Using data-driven syn-thetic charging loads for the rental car center at the Dallas/Fort Worth airport in the United States, we show that optimally-designed and controlled behind - the- meter resources can reduce the lifecycle cost of electrified rental centers by an average 41 % and reduce peak grid demand by 64 %, deferring the need for distribution upgrades or potentially avoiding it altogether.

battery storage↗

DOE OSTI2020

NDX: Neutron Dose Rate Meters with Extended Capabilities

Particle accelerators, irradiation facilities, and nuclear power plants would benefit from using neutron dose rate meters featuring improved energy response covering full range of expected neutron energies, improved dynamic range of measured dose rates while providing the real-time data, and improved ability to operate in harsh radiation environments including heavy photon backgrounds and pulsed beams. The novel design of the neutron moderator for the NDX dose rate meter implements a layer of a Beryllium-loaded medium Z material which, similar to the earlier known WENDI detectors, allows the device to detect higher energy neutron flux and convert it to dose. Using Beryllium helps to fill the known dip in the response functions around 5-50 MeV. Optimized design parameter set, obtained using FLUKA Monte Carlo simulations, features the NDX moderator made of polyethylene embedding a layer of BeCu alloy inside, with the dose rate response constant within ±10% in the neutron energy range from about 100 keV to 500 MeV, and ±25% essentially in the full energy range above thermal. A new sensor technique implemented in the NDX is based on using the Ionization Chamber (IC) filled with 3He gas to capture the moderated neutron fluence, and includes a symmetric IC filled with regular 4He to evaluate the contributions due to the non-neutron ionizing radiation. Advantages of the method include large accessible dynamic range, relative insensitivity of the IC probes to photon radiation fields, and the ability to subtract their contribution. Two prototype NDX detectors were built, calibrated, and operated in various conditions at the CEBAF 12 GeV electron accelerator at JLab. The first results showed reliable neutron dose rate measurements in the presence of overwhelming photon radiation fields, and at practical high dose rate levels of up to approximately 10 Sv/h. Detector design, operation, first results, and further development plans are presented.

Degtiarenko, Pavel V.↗

DOE OSTI2021

End-to-End Simulations of a 3.4-Meter Detector Wall for Neutron-Diagnosed Subcritical Experiments

The Nevada National Security Site, together with Los Alamos National Laboratory and Lawrence Livermore National Laboratory, is developing a novel diagnostic to measure the reactivity of subcritical experiments. This capability is known as neutron-diagnosed subcritical experiments. The decay of the fission gamma rays from the neutron-interrogated subcritical experiment is measured as a function of time with a large (~3-meter diameter) detector wall consisting of 151 individual detector pixels. The data from this current mode measurement inform the neutron multiplication factor, keff, and thus the relative reactivity of the subcritical experiment. The Nevada National Security Site developed the Gamma Array Simulation Toolkit initially to help inform the design of the individual detector pixels and the 3.4-meter diameter detector wall to be fielded as part of neutron-diagnosed subcritical experiments. This toolkit is now being used to simulate and predict the performance of the final design of the individual detector pixels and the aggregate detector wall. Additionally, key detector characteristics evaluated from these simulations include impulse response, pulse height spectrum, number of photoelectrons per MeV, detector efficiency, and cross talk between detector pixels. Collectively, the results of these simulations inform how well the fission gamma ray die-off distribution from a neutron-diagnosed subcritical experiment measurement can be resolved. This is critical to determining the relative reactivity of the experiment. Furthermore, the Gamma Array Simulation Toolkit can be used to aid in the analysis of the experimental data from a neutron-diagnosed subcritical experiment measurement once the simulation has been benchmarked.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Microgrid Service Restoration Incorporating Unmonitored Automatic Voltage Controllers and Net Metered Loads

Islanded microgrids may experience voltage and frequency instability due to uncontrolled state changes of voltage regulation devices and inaccurate demand forecasts. Uncontrolled state changes can occur if optimal microgrid restoration and dispatch algorithms, used for generating control commands for distributed energy resources, do not incorporate the behavior of automatic controllers of voltage regulation devices. Inaccurate demand forecasts may be encountered since post-outage demand of behind-the-meter net metered (NM) loads can vary significantly from their historical NM profiles. Here, this paper proposes an optimization formulation which allows optimal control of voltage regulators and capacitor banks without remote control and communication capabilities. A generalized demand model for NM loads is proposed which incorporates the cold load pickup phenomenon and their time varying post-outage demand in accordance with the IEEE 1547 standard. The time dependent optimal control formulation and the NM demand model are integrated in a sequential microgrid restoration algorithm by linearization of the involved logic propositions. A detailed case study on the unbalanced IEEE 123-node test system in OpenDSS validates the effectiveness of the proposed approach.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2024

Electrolyte and Cutoff Potential Effects on Cycle Life of Li4Ti5O12/LiNi0.9Mn0.1O2 Batteries for Behind-the-Meter Storage Applications

Behind-the-Meter Storage (BTMS) is a stationary battery energy storage system that is connected to the electrical distribution system on the customer's side of the utility's service meter. BTMS systems are used to store electrical energy from the grid as well as inconstant, renewable energy, such as local solar and wind generation. A successful BTMS system will allow the customer to pair their energy generation and storage to optimize electrical consumption from the grid, improving reliability and minimizing cost. For BTMS applications, batteries must be designed and optimized with different set of criteria from other leading segments of the Li-ion battery market, like transportation, due the system being stationary and proximal to the residential or commercial building it's benefitting. BTMS applications prioritize safety, cost (low/no-critical materials), reliability (20-year calendar life), and durability (10,000 cycle life), while having the ability to (minimally) compromise energy density and rate capability. Lithium titanate (Li4Ti5O12-, LTO) is a promising anode candidate for BTMS applications due to its high safety and capacity retention, while maintaining a reasonable 160 mAhg-1 reversable capacity and composition of relatively abundant materials. (1) Specifically, LTO has a high working voltage which helps to prevent Li dendrite formation, improving safety. Furthermore, LTO also has negligible lithiation-based volume change, leading to less mechanical pulverization, or loss of active material, upon cycling. For the cathode, materials with little or no Co are of high interest due to the high cost and low abundance of Co. LiMn2O4 (LMO) has been paired with LTO for BTMS applications in the past due to its safety, low cost (abundancy), and reasonably high operating voltage. (2-4) However, the low capacity of LMO limits energy density and specific energy. While not the highest priority for BTMS applications, increasing energy density will enable deployment in space constrained BTMS applications and decrease total cost. LiNi0.9Mn0.1O2 (LN-MO) is a recently developed material with promise due to its high operating voltage and relatively low price. (5) However, Ni-rich layered oxides, including LNMO, tend to struggle with capacity retention during high-voltage cycling due to mechanical pulverization, irreversible phase transitions, and unstable solid-electrolyte interphase. The study presented here focuses on building an understanding of how electrolyte solvent and varied cutoff potentials will impact the cycle life of LTO/LN-MO cells. Specifically, a comparison is provided between ethylene carbonate (EC), ethyl methyl carbonate (EMC), fluoroethylene carbonate (FEC), and Gen2 electrolyte solvents with 1M Lithium hexafluorophosphate (LiPF6) salt, cycling to two upper termination potentials, 2.6V and 2.7V. Electrochemical testing and diagnostics (e.g., differential capacity analysis, area specific impedance, constant voltage hold, and rate capability) and post-mortem characterization will be used to understand the aging behavior and failure mechanisms of the 8 cell combinations (four electrolytes and two voltage cutoffs). Cells with FEC electrolyte showed a lower initial capacity compared to cells with Gen2, EMC, and EC cycling at both voltages; however, the cells with FEC showed consistent trends in capacity retention with 2.6V and 2.7V termination potentials, while the cells with the other electrolytes showed much higher rates of capacity loss when cycling to the higher voltage. These results indicate that FEC may play a role in improving durability of high-voltage, Ni-rich electrode systems for use in high-cycle applications, such as BTMS.

electrolyte↗

DOE OSTI2024

Behind-the-meter Infrastructure Costs for Electrification Progression (BICEP) Model

The Behind-the-meter Infrastructure Costs for Electrification Progression (BICEP) model quantifies the behind-the-meter (BTM) electrical upgrades required for decarbonization through electrification by comparing the expected change in capacity requirements from the electrification technologies to the existing capacity in distributed energy resources (DER) stock (including buildings).

Yoder, Tim↗