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At least 1,279 records · Page 71

Big Data Processing for Power Grid Event Detection

In this paper we present the application of big data processing for the development of machine learning (ML) models to detect relevant events in power grid operations. This is based on almost 20TB of phasor measurement unit data corresponding to up to two years of operation of three grid interconnections which provide power to most of the United States. A significant aspect of the work consists in having all data processing performed on a single standard GPU server, from pre-processing to ML model training and testing. We describe the data and computational infrastructure, challenges faced and methods used in data processing, main findings and results. The ML approach employed for best utilization of the big data is also discussed, including sample results.

Paes Leao, Bruno↗

OPFLearn.jl [SWR-21-109]

OPFLearn.jl is a Julia package for creating datasets for machine learning approaches to solving AC optimal power flow (AC OPF). It was developed to provide researchers with a standardized way to efficiently create AC OPF datasets that are representative of more of the AC OPF feasible load space compared to typical dataset creation methods. The OPFLearn dataset creation method uses a relaxed AC OPF formulation to reduce the volume of the unclassified input space throughout the dataset creation process. Over time this input space tightens around the relaxed AC OPF feasible region to increase the percentage of feasible load profiles found while uniformly sampling the input space. Load samples are processed using AC OPF formulations from PowerModels.jl. More information on the dataset creation method can be found in our publication, "OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets". To use OPFLearn.jl a PowerModels network data dictionary is required (can be loaded from Matpower ".m" files) to define the network the dataset is being created for.

Joswig-Jones, Trager↗

OPFLearn.jl v0.1.2 5/18/2023 [SWR-21-109]

OPFLearn.jl is a Julia package for creating datasets for machine learning approaches to solving AC optimal power flow (AC OPF). It was developed to provide researchers with a standardized way to efficiently create AC OPF datasets that are representative of more of the AC OPF feasible load space compared to typical dataset creation methods. The OPFLearn dataset creation method uses a relaxed AC OPF formulation to reduce the volume of the unclassified input space throughout the dataset creation process. Over time this input space tightens around the relaxed AC OPF feasible region to increase the percentage of feasible load profiles found while uniformly sampling the input space. Load samples are processed using AC OPF formulations from PowerModels.jl. More information on the dataset creation method can be found in our publication, "OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets". To use OPFLearn.jl a PowerModels network data dictionary is required (can be loaded from Matpower ".m" files) to define the network the dataset is being created for.

Joswig-Jones, Trager↗

Analysis of measurements from an array of radioxenon samplers near to Hartlepool Nuclear Power Station

As part of a scientific research and development project, the radionuclide fingerprint of an operating advanced gas-cooled reactor 25 (AGR) has been studied across several facets (Goodwin et al., 2024). One part of this project was to deploy an array of 26 radioxenon samplers to the region for a period of around 1 year, to measure any radioxenon emissions from the reactors of the 27 Hartlepool nuclear power station at a range of tens of kilometres away. The array of 3 sensors was operational for around 12 28 months from March 2022 and detected many occurrences of isotopes of radioxenon. Here we provide a detailed analysis and 29 interpretation of the data and where possible, attribution of detections to a source or region. Whilst a key part of this work is to 30 measure any emissions of radioxenon from Hartlepool, this work presents one of the most comprehensive efforts to determine the 31 source of a great number of (mostly) 133Xe detections. A combination of different types of atmospheric dispersion modelling 32 techniques, including the use of stack monitoring data from nearby civil radioxenon-emitting nuclear facilities has enabled the 33 majority of detections to be attributed to one or more possible sources. Whilst emissions from Hartlepool have been detected on 34 the systems, the majority of detections are associated with a medical isotope production facility in Fleurus, Belgium (IRE).

Advanced gas-cooled reactor↗

TEAMER – Enhanced Flow Measurement for Aquantis Tidal Turbine Test

The AQ10 is a floating, two-bladed, passive yawing tidal turbine developed by Aquantis that has a 10-meterrotor diameter, 160 kW rating, and employs reliable off-the-shelf powertrain and power conversion hardware. Aquantis is planning on-water turbine power performance and loads (blade loading and thrust)testing, where the turbine will be pushed through still water up to 4 knots and placed in a ‘station keeping’ tow in a tidal race up to its rated speed. On-water testing will be conducted using vessels and floating platforms on the sea surface to improve ease of testing and reduce disturbance to the environment. In this TEAMER project, Pacific Northwest National Laboratory (PNNL) will conduct water velocity and turbulence measurements in front of the turbine during on-water testing using acoustic Doppler instrumentation. By measuring both the tidal current flowing past the turbine and the resulting electrical power output, test results will provide a power curve (power vs flow speed) for the turbine up to rated power. Measurements of turbulence and velocity shear in front of the rotor will also provide information to assess the structural response of the rotor blades. With this analysis, Aquantis can use the performance and loads data to validate Tidal Bladed and OpenFAST simulations of the measured operating conditions. Measuring the power performance of a prototype turbine is a valuable step to improving device development and conducting a complete power performance assessment to IEC/TS 62600-200 standards in the future.

16 TIDAL AND WAVE POWER↗

Techno-Economic Analysis of a Concentrating Solar Power Plant Using Redox-Active Metal Oxides as Heat Transfer Fluid and Storage Media

We present results for a one-dimensional quasi-steady-state thermodynamic model developed for a 111.7 MW e concentrating solar power (CSP) system using a redox-active metal oxide as the heat storage media and heat transfer agent integrated with a combined cycle air Brayton power block. In the energy charging and discharging processes, the metal oxide CaAl 0.2 Mn 0.8 O 2.9-δ (CAM28) undergoes a reversible, high temperature redox cycle including an endothermic oxygen-releasing reaction and exothermic oxygen-incorporation reaction. Concentrated solar radiation heats the redox-active oxide particles under partial vacuum to drive the reduction extent deeper for increased energy density at a fixed temperature, thereby increasing storage capacity while limiting the required on sun temperature. Direct counter-current contact of the reduced particles with compressed air from the Brayton compressor releases stored chemical and sensible energy, heating the air to 1,200°C at the turbine inlet while cooling and reoxidizing the particles. The cool oxidized particles recirculate through the solar receiver subsystem for another cycle of heating and reduction (oxygen release). We applied the techno-economic model to 1) size components, 2) examine intraday operation with varying solar insolation, 3) estimate annual performance characteristics over a simulated year, 4) estimate the levelized cost of electricity (LCOE), and 5) perform sensitivity analyses to evaluate factors that affect performance and cost. Simulations use hourly solar radiation data from Barstow, California to assess the performance of a 111.7 MW e system with solar multiples (SMs) varying from 1.2 to 2.4 and storage capacities of 6–14 h. The baseline system with 6 h storage and SM of 1.8 has a capacity factor of 54.2%, an increase from 32.3% capacity factor with no storage, and an average annual energy efficiency of 20.6%. Calculations show a system with an output of 710 GWh e net electricity per year, 12 h storage, and SM of 2.4 to have an installed cost of $329 million, and an LCOE of 5.98 ¢/kWh e . This value meets the U.S. Department of Energy’s SunShot 2020 target of 6.0 ¢/kWh e ( U. S Department of Energy, 2012 ), but falls just shy of the 5.0 ¢/kWh e 2030 CSP target for dispatchable electricity ( U. S Department of Energy, 2017 ). The cost and performance results are minimally sensitive to most design parameters. However, a one-point change in the weighted annual cost of capital from 8 to 7% (better understood as a 12.5% change) translates directly to an 11% decrease (0.66 ¢/kWhe) in the LCOE.

Gorman, Brandon T.↗

Comparisons of Nodal diffusion and whole-core transport methods for multiple cycles of a small Light water reacto

As part of a cooperative research and development agreement between the US department of Energy's Oak Ridge National Laboratory and Holtec International subsidiary SMR LLC, core simulator models of the SMR-160, a light water-cooled and -moderated, natural circulation, small modular reactor, were developed and compared. The model results indicate pin-by-pin power histories, critical boron concentration, and other key performance indicators useful for developing multi-cycle core loading patterns. One model uses industry standard nodal methods with a simple thermal-hydraulics solution, and the other uses an advanced deterministic neutronics solver with a coupled subchannel calculation. The goals of the comparison are to provide the reactor designer with a detailed and coupled core physics reference solution, inform the reactor designer of nodal model best practices based on the code-to-code comparison, and set up a workflow for performing subsequent detailed core simulator calculations. The results of this work will be used in the development of coupled neutronic, thermal hydraulic, and fuel performance models for advanced analysis of the SMR-160. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Generation of strong magnetic fields for magnetized plasma experiments at the 1-MA pulsed power machine

Pulsed power technology provides a platform for investigating plasmas in strong magnetic fields using a university-scale machine. Presented here are methods for generating and measuring the 1–4-MG magnetic fields developed for the 1-MA Zebra pulsed power generator at the University of Nevada, Reno. A laser coupled with the Zebra generator produces a magnetized plasma, and experiments investigate how a megagauss magnetic field affects the two-plasmon decay and the expansion of the laser-produced plasma in both transverse and longitudinal magnetic fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

High-Temperature Particle Heat Exchanger for sCO2 Power Cycles [Award 30342]

This report describes the design, development, and testing of a prototype 100 kWt particle-to-supercritical CO 2 (sCO2) heat exchanger. An analytic hierarchy process was implemented to compare and evaluate alternative heat-exchanger designs (fluidized bed, shell-and-plate moving packed bed, and shell-and-tube moving packed bed) that could meet the high pressure (≥ 20 MPa) and high temperature (≥ 700 °C) operational requirements associated with sCO2 power cycles. Cost, heat-transfer coefficient, structural reliability, manufacturability, parasitics and heat losses, scalability, compatibility, erosion and corrosion, transient operation, and inspection ease were considered in the evaluation. A 100 kWt shell-and-plate design was selected for construction and integration with Sandia’s falling particle receiver system that heats the particles using concentrated sunlight. Sandia worked with industry to design and construct the moving packed-bed shell-and-plate heat exchanger. Tests were performed to evaluate its performance using both electrical heating and concentrated sunlight to heat the particles. Overall heat transfer coefficients at off-design conditions (reduced operating temperatures and only three stainless steel banks in the counter-crossflow heat exchanger) were measured to be approximately ~25 - 70 W/m 2 -K, significantly lower than simulated values of >100 W/m 2 -K. Tests using the falling particle receiver to heat the particles with concentrated sunlight yielded overall heat transfer coefficients of ~35 – 80 W/m 2 -K with four banks (including a nickel-alloy bank above the three stainless steel banks). The overall heat transfer coefficient was observed to decrease with increasing particle inlet temperatures, which contrasted the results of simulations that showed an increase in heat transfer coefficient with temperature due to increased effective particle-bed thermal conductivity from radiation. The likely cause of the discrepancy was particle-flow maldistributions and funnel flow within the heat exchanger caused by internal ledges and cross-bracing, which could have been exacerbated by increased particle-wall friction at higher temperatures. Additional heat loss at higher temperatures may also contribute to a lower overall heat-transfer coefficient. Design challenges including pressure drop, particle and sCO2 flow maldistribution, and reduced heat transfer coefficient are discussed with approaches for mitigation in future designs. Lessons learned regarding instrumentation, performance characterization, and operation of particle components and sCO2 flow loops are also discussed. Finally, a 200 MWt commercial-scale shell-and-plate heat-exchanger design based on the concepts investigated in this report is proposed.

14 SOLAR ENERGY↗

Powering the Blue Economy: Marine Energy at Kelp Farm Sites

Marine energy (ME) has the potential to power businesses in the blue economy. Kelp farms are an emerging maritime market of the blue economy and are predicted to grow, but they are not currently using ME for their power needs. As the number and size of kelp farms increase, more offshore power will be needed onsite for operations, monitoring, and harvesting. ME devices such as tidal current energy converters and wave energy converters (WECs) may be used to supply power for these needs. This article assesses the status of kelp farming in the continental United States, investigates the electricity needs of kelp farms, and examinesthe feasibility of generating the required electricity from wave and tidal current energy. The United States currently has 165 kelp farms that have either active or pending permits. The farms use electricity for boat operations, kelp drying, environmental monitoring, offshore lighting, and the raising and lowering of lines. Most kelp farms are in protected, nearshore waters that do not have significant wave energy resources. The limited available wave energy could be used to power small devices, but WECs have not yet been developed for that application. Some kelp farms are in locations that feature significant tidal energy resources, but small tidal current energy converters that are compatible with existing farm operations are not yet commercially available. As low-power WECs and tidal current energy converters are developed, kelp farms could be research partners and early adopters of the new technologies, which would encourage their broader use by other blue economy businesses.

16 TIDAL AND WAVE POWER↗

Report on the Creation and Progress of the Hydrogen Regulatory Research Review Group

The current U.S. nuclear generation fleet is increasingly recognized by governmental, scientific, public policy, and industrial communities as having a strategic role in support of the ongoing national transition to a clean energy future. Federal incentives and actions are aligning to expand the role of nuclear power as a viable and more flexible contributor to the evolving national clean energy mix through programs and initiatives such as nuclear power loan guarantees; the Inflation Reduction Act’s (IRA) clean nuclear electrical, steam, and hydrogen incentives; the Infrastructure Investment and Jobs Act (IIJA, also referred to as the Bipartisan Infrastructure Act or BIL); and near term Department of Energy (DOE) funding opportunities related to nuclear based hydrogen hubs and nuclear integrated hydrogen demonstration projects. . Additionally, leveraging clean nuclear electricity and steam is being explored by industries desiring to transition away from carbon-intensive energy sources. Even with all these emerging enablers, notable barriers remain for the widespread adoption of these opportunities within the U.S. nuclear fleet, including the following: • Assurance of the markets for alternate products needed to support decision-making for large capital modification investments • Electric utility mindset and business history centered solely on producing electricity • Design change complexity and regulatory uncertainty associated with plant modifications needed to support alternate product streams The DOE Light Water Reactor Sustainability (LWRS) Flexible Plant Operations and Generation (FPOG) Pathway is developing options to help U.S. nuclear power plants (NPP) in all these areas to enable NPPs designed for steady baseload operation to integrate with intermittent wind and solar capacity to assure reliable clean energy for the nation. Current and near-term laboratory research is focusing on the technical, regulatory, safety, demonstration, and economic elements in support of improving nuclear plant flexibility through hybrid production of electricity and other non-electric products such as hydrogen and energy arbitrage.

42 ENGINEERING↗

Northern California and Southern Oregon Offshore Wind Transmission Study: Volume 1 (Revised)

Offshore wind (OSW) power based on floating technology in the coastal waters of the U.S. Pacific Ocean has great potential to contribute to climate mitigation and renewable energy goals in California, Oregon, and other parts of the western U.S. To achieve development of OSW at scale, investments in transmission infrastructure are needed to deliver this power to major metropolitan areas because these are the primary electricity load centers. Currently the transmission infrastructure serving coastal regions where OSW is most likely to be developed has limited capacity and is designed to bring power from the east to serve modest coastal loads. The development of OSW generation and the interconnection of this resource to the bulk power grid will require major investments in new transmission infrastructure and upgrades to existing infrastructure. This study investigated the development of up to 25.8 GW of OSW energy on the northern coast of California and the southern coast of Oregon. The focus of the study was to assess various transmission alternatives that could deliver OSW power to distant load centers while also providing energy benefits to rural coastal communities near to where OSW power may be developed.

17 WIND ENERGY↗

Enabling Marine Energy Integration for Ocean Observing: Functional Requirements

Marine renewable energy (i.e., wave, tidal or ocean current, thermal gradient, and salinity gradient) or MRE can revolutionize ocean observing capabilities. Five use cases representing a range of ocean observing platforms were developed based on end-user feedback. Drawing from these use cases, common needs or functional requirements were developed to help guide the integration of MRE power delivery for ocean observation structures and functions. The functional requirements were determined from descriptions of the use cases, specifications of hardware that are used or closely associated with existing ocean observation platforms, and direct feedback from ocean observation sensor/platform developers and users. Twenty types of functional requirements were identified, including those associated with power and energy use; physical system requirements; temperature and depth; electrical, acoustic, and motion interference; and reliability. Each set of functional requirements is illustrated as features of the use cases. By defining functional requirements for MRE technology integration in ocean observing platforms, and focusing on end-user requirements, barriers to developing MRE-driven ocean observation missions can be reduced.

Cavagnaro, Robert J.↗

Low Cost High-Performance HRE-Free 3-in-1 Electric Drive Unit

The project team completed work to expand upon American Axle & Manufacturing’s (AAM) baseline technology and develop a high-speed, AC induction electric drive unit (EDU) with total direct-oil-cooling and integrated power electronics. The project accelerated advancements in EDU technology by allowing AAM to build upon the progress made in developing the underlying baseline technologies. The following seven improvements to AAM’s baseline technology were implemented in this research and development program: 1) Increased speed (30k RPM) AC induction motor, 2) Silver-sintering of discrete silicon carbide (SiC) metal-oxide-semiconductor field-effect transistors (MOSFET) to heat sinks, 3) Electrically insulated rotor bars, 4) Optimized lamination steel, 5) EDU-integrated 650VDC inverter package, 6) Over-molded stator with molded liners, and 7) 650VDC power-dense stator design. The successful development of the technology resulted in a meaningful cost reduction for EDU systems in the market. Coupled with falling battery system costs, lower EDU costs will likely accelerate the market acceptance and related production scaling of battery electric vehicles. The objective of this project was to research, develop, and test a Heavy Rare Earth (HRE)-free 3-In-1 electric drive unit (EDU) that has class leading power density and cost. The key technologies to be developed were anticipated to meet or exceed the Department of Energy (DOE) targets of a cost ≤ $\$$7/kilowatt (kW), power density ≥ 12 kW/liter, and operating voltage ≥ 600 VDC.

33 ADVANCED PROPULSION SYSTEMS↗

Unique nanotechnology converts carbon dioxide to valuable products

Carbon capture and management are increasing challenges associated with global warming. Current commercial-scale carbon dioxide (CO 2 ) capture technologies are associated with a heavy economic penalty – they require at least one-third of the plant’s steam and power to operate. The objective of this project was to develop and test an innovative nanotechnology that can utilize CO 2 , from coal-based power systems or other industrial sources, as the primary feedstock to produce commercially valuable products to potentially offset the cost of CO 2 capture. The scope of this project includes conversion of CO 2 to nanomaterials using two unique amino acids in synthetic flue gases and the completion of a process design and techno-economic and lifecycle analyses to demonstrate the economic feasibility and environmental impact of the developed technology. The International Energy Agency predicts that fossil fuels will continue to play a significant role in meeting global energy demand. The goal of the research is to lead to an affordable and transformational CO 2 capture and reuse technology that will reduce the release of CO 2 thereby reducing global climate variability and its enormous impact on our daily lives.

01 COAL, LIGNITE, AND PEAT↗

Physics-Based Feature Extraction from Bulk Time-Series PMU Datasets for Event Detection

In this work, two physics-based feature extraction techniques are developed for bulk time-series phasor measurement unit (PMU) datasets collected from the field to train the machine learning model for anomaly detection. Two approaches have been developed to extract useful features for different types of events. An admittance-based feature extraction technique is developed to detect events that involve line outages and system topology variations. The developed algorithm extracts the system equivalent admittance variation. Additionally, Fielder’s Theory is utilized to further reduce the potential computation burden by sectionalizing large-scale grids and datasets into smaller areas. Second, an oscillation-based feature extraction technique is developed to detect low-frequency oscillations in power grids. The dominant oscillation modes in the grids are extracted using energy-sorted Prony analysis. The extracted dominant oscillation modes by the developed work exhibit a high fitting resolution. Finally, the developed techniques have been validated using large-scale and real-world datasets.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Fueling the Future: The Emergence of Self-Powered Enzymatic Biofuel Cell Biosensors

Self-powered biosensors are innovative devices that can detect and analyze biological or chemical substances without the need for an external power source. These biosensors can convert energy from the surrounding environment or the analyte itself into electrical signals for sensing and data transmission. The self-powered nature of these biosensors offers several advantages, such as portability, autonomy, and reduced waste generation from disposable batteries. They find applications in various fields, including healthcare, environmental monitoring, food safety, and wearable devices. While self-powered biosensors are a promising technology, there are still challenges to address, such as improving energy efficiency, sensitivity, and stability to make them more practical and widely adopted. This review article focuses on exploring the evolving trends in self-powered biosensor design, outlining potential advantages and limitations. With a focal point on enzymatic biofuel cell power generation, this article describes various sensing mechanisms that employ the analyte as substrate or fuel for the biocatalyst’s ability to generate current. Technical aspects of biofuel cells are also examined. Research and development in the field of self-powered biosensors is ongoing, and this review describes promising areas for further exploration within the field, identifying underexplored areas that could benefit from further investigation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Time Delay of Wide Area Damping Control in Urban Power Grid: Model-Based Analysis and Data-Driven Compensation

Due to the rapid development of economies, large urban cities consume an increasing amount of energy and have a higher requirement for power quality. Voltage source converter based high voltage direct current (VSC-HVDC) is a promising device to transmit clean power from remote regions to urban power systems, while also providing wide area damping control (WADC) for frequency stabilization. However, the time-delay naturally existing in the VSC-HVDC system may degrade the performance of WADC and even result in instability. To address this issue, this paper develops a time-delay correction control strategy for VSC-HVDC damping control in urban power grids. First, a small signal model of WADC is built to analyze the negative impacts of time delay. Then, a data-driven approach is proposed to compensate for the inherent time delay in VSC-HVDC damping control. The extensive training data will be generated under various disturbances. After offline training, the long short-term memory network (LSTM) can be implemented online to predict the actual frequency deviation based on real-time measurements. Finally, the proposed method is validated through MATLAB-Simulink in a two-area four-machine system. The results indicate that the data-driven compensation has a strong generalization ability for random delay time constants and can improve the performance of WADC significantly.

24 POWER TRANSMISSION AND DISTRIBUTION↗