Quantifying the Environmental Sensitivity of SSTDR Signals for Monitoring PV Strings
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Energy & Fuels↗
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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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Intelligent Energy Optimizer for Residential Buildings
Demand-side management in the buildings is essential for meeting grid flexibility needs in a highly renewable energy scenario. Appliance load monitoring helps decision making for demand-side management by providing the information on operation status/power consumption from different appliances in the buildings. Nonintrusive load monitoring (NILM) is an attractive option for appliance load monitoring using because it has lower cost for sensors and helps mitigate privacy concerns. In this study, the team used an event detection technique followed by two different methods for event classification. The results from k-means clustering showed that the events from a single appliance are often distributed in multiple clusters. Thus, the unsupervised method of NILM using k-means clustering used in this study was not very suitable for load disaggregation. The results from NILM showed that the F1 score for event classification was 0.77 for a heat pump water heater and very low for other appliances using the rule-based classification.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Utah FORGE: Neubrex Well 16B(78)-32 Circulation Test Fiber Optics Monitoring Data and Reports - July, 2023
This dataset features Distributed Acoustic Sensing (DAS) and fiber optics monitoring data acquired by Neubrex Energy Services during the Utah FORGE Well 16B(78)-32 circulation test in July 2023. DAS and fiber optic monitoring data include absolute strain, strain change, strain change rate, distributed temperature sensing (DTS), and frequency band extraction (FBE). Data processing was completed between September and October 2023. The dataset includes the fiber optic sensing data collected during these operations, along with a data collection report, descriptions of the data, and instructions for reading the data files.
15 GEOTHERMAL ENERGY↗
Empirical Acoustic Source Model for Chemical Explosions in Air
Chemical explosions generate pressure disturbances in air that radiate as nonlinear shock waves near the source and transition into acoustic waves with distance. Because low-frequency acoustic waves generally travel large distances without significant loss of energy, they are often used for explosion monitoring and yield estimation. However, quantitative relationships between acoustic energy and explosion yields are required for accurate yield estimation. Here, we develop an empirical acoustic source model for chemical explosions from experimental data. The empirical model returns the acoustic pressure waveform for the detonation of 1 kg of trinitrotoluene, which is conventionally used to represent the explosive release of 4.184 MJ of explosion energy. The full-waveform model can be used to predict acoustic signals for an arbitrary yield of a high-explosive detonation based on the standard scaling law and to estimate acoustic energies in a specific frequency range. We evaluate the accuracy of the acoustic source model independently by estimating the yield of other explosive events that are not included in the model development. Finally, statistical characteristics of the model and their implications for the uncertainty quantification of estimated yields are discussed.
58 GEOSCIENCES↗
Hanford Site Raptor Nest Monitoring Report for Calendar Year 2022
The U.S. Department of Energy, Richland Operations Office (DOE-RL), conducts ecological monitoring on the Hanford Site to collect and track data needed to ensure compliance with an array of environmental laws, regulations, and policies governing DOE-RL activities. Ecological monitoring data provide baseline information about the plants, animals, and habitats under DOERL stewardship at the Hanford Site required for decision making under the National Environmental Policy Act of 1969 (NEPA) and Comprehensive Environmental Response, Compensation, and Liability Act of 1980. DOE/EIS-0222, Final Hanford Comprehensive Land Use Plan Environmental Impact Statement, (CLUP) evaluates the potential environmental impacts associated with implementing a comprehensive land-use plan for the Hanford Site for at least the next 50 years and ensures that DOE-RL, its contractors, and other entities conduct activities on the Hanford Site in compliance with NEPA.
54 ENVIRONMENTAL SCIENCES↗
Hanford Reach Fall Chinook Salmon Redd Monitoring Report for Calendar Year 2022
The U.S. Department of Energy, Richland Operations Office (DOE-RL) conducts ecological monitoring on the Hanford Site to collect and track data needed to ensure compliance with an array of environmental laws, regulations, and policies governing DOE-RL activities. Ecological monitoring data provide baseline information about the plants, animals, and habitats under DOE-RL stewardship at the Hanford Site required for decision making under the National Environmental Policy Act (NEPA) and Comprehensive Environmental Response, Compensation, and Liability Act. DOE/EIS-0222, Final Hanford Comprehensive Land-Use Plan Environmental Impact Statement, (CLUP) evaluates the potential environmental impacts associated with implementing a comprehensive land-use plan for the Hanford Site for at least the next 50 years, and ensures that DOE-RL, its contractors, and other entities conduct activities on the Hanford Site in compliance with NEPA.
54 ENVIRONMENTAL SCIENCES↗
Hanford Reach Fall Chinook Salmon Redd Monitoring Report for Calendar Year 2021
The U.S. Department of Energy, Richland Operations Office (DOE-RL), conducts ecological monitoring on the Hanford Site to collect and track data needed to ensure compliance with an array of environmental laws, regulations, and policies governing DOE-RL activities. Ecological monitoring data provide baseline information about the plants, animals, and habitats under DOE-RL stewardship at the Hanford Site required for decision making under the National Environmental Policy Act (NEPA) and Comprehensive Environmental Response, Compensation, and Liability Act. DOE/EIS-0222, Final Hanford Comprehensive Land-Use Plan Environmental Impact Statement, (CLUP) evaluates the potential environmental impacts associated with implementing a comprehensive land-use plan for the Hanford Site for at least the next 50 years, and ensures that DOE-RL, its contractors, and other entities conduct activities on the Hanford Site in compliance with NEPA.
54 ENVIRONMENTAL SCIENCES↗
Hanford Reach Fall Chinook Salmon Redd Monitoring Report for Calendar Year 2020
The U.S. Department of Energy, Richland Operations Office (DOE-RL) conducts ecological monitoring on the Hanford Site to collect and track data needed to ensure compliance with an array of environmental laws, regulations, and policies governing DOE-RL activities. Ecological monitoring data provide baseline information about the plants, animals, and habitats under DOE-RL stewardship at the Hanford Site required for decision making under the National Environmental Policy Act (NEPA) and Comprehensive Environmental Response, Compensation, and Liability Act. DOE/EIS-0222, Final Hanford Comprehensive Land Use Plan Environmental Impact Statement, (CLUP) evaluates the potential environmental impacts associated with implementing a comprehensive land-use plan for the Hanford Site for at least the next 50 years, and ensures that DOE-RL, its contractors, and other entities conduct activities on the Hanford Site in compliance with NEPA.
54 ENVIRONMENTAL SCIENCES↗
Hanford Reach Fall Chinook Salmon Redd Monitoring Report for Calendar Year 2019
The U.S. Department of Energy, Richland Operations Office (DOE-RL) conducts ecological monitoring on the Hanford Site to collect and track data needed to ensure compliance with an array of environmental laws, regulations, and policies governing DOE-RL activities. Ecological monitoring data provide baseline information about the plants, animals, and habitats under DOE-RL stewardship at the Hanford Site required for decision making under the National Environmental Policy Act (NEPA) and Comprehensive Environmental Response, Compensation, and Liability Act. DOE/EIS-0222, Final Hanford Comprehensive Land Use Plan Environmental Impact Statement (CLUP) evaluates the potential environmental impacts associated with implementing a comprehensive land-use plan for the Hanford Site for at least the next 50 years, and ensures that DOE-RL, its contractors, and other entities conduct activities on the Hanford Site in compliance with NEPA.
54 ENVIRONMENTAL SCIENCES↗
Hanford Reach Fall Chinook Redd Monitoring Report for Calendar Year 2018
The U.S. Department of Energy, Richland Operations Office (DOE-RL) conducts ecological monitoring on the Hanford Site to collect and track data needed to ensure compliance with an array of environmental laws, regulations, and policies governing DOE-RL activities. Ecological monitoring data provide baseline information about the plants, animals, and habitats under DOE-RL stewardship at the Hanford Site required for decision making under the National Environmental Policy Act (NEPA) and Comprehensive Environmental Response, Compensation, and Liability Act. DOE/EIS-0222, Final Hanford Comprehensive Land Use Plan Environmental Impact Statement (CLUP) evaluates the potential environmental impacts associated with implementing a comprehensive land-use plan for the Hanford Site for at least the next 50 years, and ensures that DOE-RL, its contractors, and other entities conduct activities on the Hanford Site in compliance with NEPA.
54 ENVIRONMENTAL SCIENCES↗
Hanford Reach Fall Chinook Redd Monitoring Report for Calendar Year 2017
The U.S. Department of Energy, Richland Operations Office (DOE-RL) conducts ecological monitoring on the Hanford Site to collect and track data needed to ensure compliance with an array of environmental laws, regulations, and policies governing DOE-RL activities. Ecological monitoring data provide baseline information about the plants, animals, and habitats under DOE-RL stewardship at the Hanford Site required for decision making under the National Environmental Policy Act (NEPA) and Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA). DOE/EIS-0222, Final Hanford Comprehensive Land Use Plan Environmental Impact Statement (CLUP) evaluates the potential environmental impacts associated with implementing a comprehensive land-use plan for the Hanford Site for at least the next 50 years, and ensures that DOE-RL, its contractors, and other entities conduct activities on the Hanford Site in compliance with NEPA.
54 ENVIRONMENTAL SCIENCES↗
Hanford Site Freshwater Mussel Monitoring Report for Calendar Year 2022
The U.S. Department of Energy, Richland Operations Office (DOE-RL) conducts ecological monitoring on the Hanford Site to collect and maintain data needed to ensure compliance with an array of environmental laws, regulations, and policies governing DOE-RL activities. Ecological monitoring data provides baseline information about the plants, animals, and habitats under DOE-RL stewardship at the Hanford Site that is required for decision making under the National Environmental Policy Act of 1969 and Comprehensive Environmental Response, Compensation, and Liability Act of 1980. In addition, ecological monitoring helps ensure that DOE-RL, its contractors, and other entities conducting activities on the Hanford Site are in compliance with the Hanford Site Comprehensive Land Use Plan (DOE/EIS-0222-F). DOE-RL places priority on monitoring those plant and animal species or habitats with specific regulatory protections or requirements that are rare and/or declining (federal or state listed endangered, threatened, or sensitive species) or are of significant interest to federal, state, or tribal governments or the public.
54 ENVIRONMENTAL SCIENCES↗
Online and Offline Identification of False Data Injection Attacks in Battery Sensors Using a Single Particle Model
The cells in battery energy storage systems are monitored, protected, and controlled by battery management systems whose sensors are susceptible to cyberattacks. False data injection attacks (FDIAs) targeting batteries’ voltage sensors affect cell protection functions and the estimation of critical battery states like the state of charge (SoC). Inaccurate SoC estimation could result in battery overcharging and over discharging, which can have disastrous consequences on grid operations. This paper proposes a three-pronged online and offline method to detect, identify, and classify FDIAs corrupting the voltage sensors of a battery stack. To accurately model the dynamics of the series-connected cells a single particle model is used and to estimate the SoC, the unscented Kalman filter is employed. FDIA detection, identification, and classification was accomplished using a tuned cumulative sum (CUSUM) algorithm, which was compared with a baseline method, the chi-squared error detector. Online simulations and offline batch simulations were performed to determine the effectiveness of the proposed approach. Throughout the batch simulations, the CUSUM algorithm detected attacks, with no false positives, in 99.83% of cases, identified the corrupted sensor in 97% of cases, and determined if the attack was positively or negatively biased in 97% of cases.
25 ENERGY STORAGE↗
Power modeling of degraded PV systems: Case studies using a dynamically updated physical model (PV-Pro)
Power modeling, widely applied for health monitoring and power prediction, is crucial for the efficiency and reliability of Photovoltaic (PV) systems. The most common approach for power modeling uses a physical equivalent circuit model, with the core challenge being the estimation of model parameters. Traditional parameter estimation either relies on datasheet information, which does not reflect the system's current health status, especially for degraded PV systems, or requires additional I-V characterization, which is generally unavailable for large-scale PV systems. Thus, we build upon our previously developed tool, PV-Pro (originally proposed for degradation analysis), to enhance its application for power modeling of degraded PV systems. PV-Pro extracts model parameters from production data without requiring I-V characterization. This dynamic model, periodically updated, can closely capture the actual degradation status, enabling precise power modeling. PV-Pro is compared with popular power modeling techniques, including persistence, nominal physical, and various machine learning models. The results indicate that PV-Pro achieves outstanding power modeling performance, with an average nMAE of 1.4 % across four field-degraded PV systems, reducing error by 17.6 % compared to the best alternative technique. Furthermore, PV-Pro demonstrates robustness across different seasons and severities of degradation. The tool is available as a Python package at https://github.com/DuraMAT/pvpro.
14 SOLAR ENERGY↗
Use of a 360-Degree Underwater Camera to Characterize Artificial Reef and Fish Aggregating Effects around Marine Energy Devices
Marine energy devices must be attached to the seafloor by their foundations, pilings, or anchors, and will have other parts in the water column like the devices themselves, mooring lines, and power export cables running along the seafloor. The installation and presence of these artificial structures will create physical changes that can disrupt or create new habitats, and potentially alter the behavior of mobile organisms such as fish around a device by attracting them to these new artificial reefs and fish aggregating devices. In this study, we tested a new approach for monitoring fish activity around a marine energy device anchor: a 360-degree underwater camera to keep the target (a wave energy converter’s anchor) in the field of view of the camera. The camera was deployed in three configurations (hand-held, tripod, video lander) at sites with different hydrodynamics and underwater visibilities. The video lander was the best configuration: very stable, versatile, and easy to handle. The 360-degree field of view enabled observing and counting fishes, which were more abundant at dusk than dawn or noon, around the anchor. Despite remaining challenges, 360-degree cameras are useful tools for monitoring animal interactions with marine energy devices.
360-degree camera↗
Measurement of Beam Energy in the Fermilab's Linac taken at the transfer Line
Linac is the first machine in the Accelerator chain at Fermilab where 𝐻− particles are accelerated from 35 keV to 400 MeV and travel to the Booster where they are stripped. of the extra electrons to become protons. The Booster requires stable beam energy at injection. The Linac extraction energy tuning has been performed using two Beam Velocity Monitors (a.k.a Griffin detectors) to maintain stable relative energy between the Booster and the Linac. Our goal is to control the Linac energy parameters using Machine Learning techniques to increase reliability and quality of beam delivered from Linac. The first step is to understand the data from the Linac extraction diagnostics; and develop reliable, accurate methods for energy measurement and control before implementing machine learning. There were two methods of energy measurement implemented, and the results of these are compared. The first method was time of flight measurements using the Phase probes inside B eam Position Monitors (BPM) that provide the beam’s phase of arrival data. The second method used the relation between beam position data from the BPMs and dispersion values from the 400MeV MAD-X model to calculate momentum variation. The results of these two energy measurement methods compare well as the Linac energy is varied.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Reinforcement Learning for Intelligent Building Energy Management System Control *
A building energy management system (BEMS) is a computer-based system designed to monitor and control a building's energy needs. Modern BEMS rely on the sensing and connectivity capabilities of Internet of Things (IoT) technology to intelligently adjust the energy consumption to reduce cost while respecting the consumers' preferences. Increasingly, control decisions are made based on predictions by models trained using supervised machine learning methods, which still requires control policies to be formulated in a rule-based fashion. When using reinforcement learning (RL) instead, control policies are learned by observing the utility in terms of cost and comfort associated with actions such as a change in the heating system's setpoint. The resulting RL-based controllers can capture not only the dynamics of the building and the associated electrical devices, but also fluctuations in electricity prices and user demand, avoiding the need to combine multiple predictive models with tailored control policies. This chapter will provide an overview of RL-based approaches for BEMS. After sketching the taxonomy of general RL methods, we discuss the implications of relying on the individual methods in a BEMS context. Existing work applying RL is presented along the key devices controlled by BEMS systems. Finally, we summarize the state-of-the-art and sketch limitations and open research directions.
Kotevska, Olivera↗
Colloidal Synthesis of Palladium Nanocluster‐Decorated Cs 3 Sb 2 Cl 9 Perovskite Heterostructural Nanorods for Enhanced CO 2 Photoreduction
Developing efficient and sustainable photocatalysts for CO 2 reduction remains a significant challenge, particularly with environmentally benign materials. Here, in this study, we report the first one-step synthesis of metal–lead-free perovskite heterostructural nanocrystals by decorating Cs 3 Sb 2 Cl 9 perovskite nanorods with size-controlled Pd nanoclusters via a one-step hot-injection method. The resulting Pd-Cs 3 Sb 2 Cl 9 heteronanorods (HNRs) exhibit strong interfacial electronic coupling, enhanced charge separation, and excellent colloidal stability. Transient absorption spectroscopy and DFT calculations reveal a built-in electric field that drives directional electron transfer from the perovskite host to the Pd domains. Under UV irradiation, the Pd-Cs 3 Sb 2 Cl 9 HNRs demonstrate excellent CO 2 photoreduction activity with high CH 4 selectivity, achieving a record apparent quantum yield (AQY) of 2.62% among halide perovskite nanocrystal-based systems with a large electronic yield of 689.3 ± 12.2 µmol·g cat −1 . In situ spectroscopic monitoring and Gibbs free energy analysis further unveil a Pd-facilitated reaction pathway involving stabilization of key intermediates. This work introduces a new class of lead-free perovskite-based heterostructures through a facile one-step synthesis strategy and offers a new design principle for next-generation photocatalysts for solar fuel production.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗