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At least 127 records · Page 7

Data Driven Online Learning of Power System Dynamics

With the advancement of sensing and communication in power networks, high-frequency real-time data from a power network can be used as a resource to develop better monitoring capabilities. In this work, a systematic approach based on data-driven operator theoretic methods involving Koopman operator is proposed for the online identification of power system dynamics. In particular, a new algorithm is provided, which unlike any previously existing algorithms, updates the Koopman operator iteratively as new data points are acquired. The proposed algorithm has three advantages: a) allows for real-time monitoring of the power system dynamics b) linear power system dynamics (this linear system is usually in a higher dimensional feature space and is not same as linearization of the underlying nonlinear dynamics) and c) computationally fast and less intensive when compared to the popular Extended Dynamic Mode Decomposition (EDMD) algorithm. The efficiency of the proposed algorithm is illustrated on an IEEE 9 bus system using synthetic data from the nonlinear model and on IEEE 39 bus system using synthetic data from the linearized model.

Sinha, Subhrajit↗

ReNew100: Reliable Power System Operation with 100% Renewable Generation

The ReNew100 project has developed and demonstrated an operator support system (OSS) to operate power systems with 100% renewable power generation from inverter-based resources (IBRs) like wind and solar that significantly reduces the risk of widespread power outages in a simulated operational environment at Technology Readiness Level (TRL) 6. The OSS achieves resilient operation for power systems under changing operation modes including varying combinations of conventional and renewable generation, including cases with 100% renewable generation from wind and solar IBRs. The OSS continuously monitors the N-1 security of the power system, which refers to the ability of the power systems to survive single outages of power system elements, like the loss of a generator or a power line, without causing widespread power outages beyond those expected and planned for. If the OSS identifies that the system is not N-1 secure, an automatic Controller Parameter Optimization (CoPO) developed within Renew100 is activated to optimize the N-1 security of the system by tuning controller parameters within different assets like batteries, wind, and solar plants. The core innovation of ReNew100 is the development of this CoPO as well as the demonstration of the OSS for a real-time simulation of the Hawai'i Island power system. Moreover, Renew100 has developed new model calibration techniques for dynamic power system models and demonstrated them for Hawai'i Island.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Development of an Innovative Inspection Tool for Superheater Tubes in Fossil Fuel Power Plants

Fossil fuel power plants are complex systems containing multiple components that require periodic health monitoring. Failures in these systems can lead to increased downtime for the plant, reduction of power, and significant cost for repairs. Inspections of the plant’s superheater tubes are typically manual, laborious, and extremely time-consuming. This is due to their small diameter size (between 1.3 and 7.6 cm) and the coiled structure of the tubing. In addition, the tubes are often stacked close to each other, limiting access for external inspection. This paper presents the development and testing of an electrically powered pipe crawler that can navigate inside 5 cm diameter tubes and provide an assessment of their health. The crawler utilizes peristaltic motion within the tubes via interconnected modules for gripping and extending. The modular nature of the system allows it to traverse through straight sections and multiple 90° and 180° bends. Additional modules in the system include an ultrasonic sensor for tube thickness measurements, as well as environmental sensors, a light detecting and ranging (LiDAR) sensor, and camera. Furthermore, these modules utilize a gear system that allows for 360° rotation and provides a means to inspect the entire internal circumference of the tubes.

36 MATERIALS SCIENCE↗

A Cable Condition Monitoring Strategy for Safe and Reliable Plant Operation

Electrical cables provide essential functions, such as delivery of power or instrumentation signals for monitoring systems. Most cables installed in industrial applications are constructed with organic polymer insulations that can become brittle, crack, or degrade over time from exposure to harsh environmental conditions, such as elevated temperatures, moisture, vibration, mechanical shock, and radiation. This paper describes an overall strategy for assessing the health and managing the aging of cables during the operating life of an industrial facility. This strategy involves performing condition assessments and monitoring of electrical cables using both in situ and laboratory testing techniques. It includes in situ testing to identify anomalies in the circuits, such as degraded terminations, splices, connections, and degraded sections of cable insulation, as well as as-found evaluations to determine the current condition of installed cables. Furthermore, these cable condition evaluations provide important information about the current state of the cable circuits. Moreover, the test results can be used to trend/monitor age-related degradation and estimate the remaining useful life of installed cables.

36 MATERIALS SCIENCE↗

Design and Construction of a High Field Cable Test Facility at Fermilab

Fermi National Accelerator Laboratory, together with Lawrence Berkeley National Laboratory, is building a new High Field Vertical Magnet Test Facility (HFVMTF) to be situated in the Magnet Test Facility at Fermilab. The HFVMTF is jointly funded by the US DOE Offices of Science, High Energy Physics, and Fusion Energy Sciences, and will serve as a superconducting cable test facility for both communities. The background magnetic field for test samples is 15 T and will be produced by a magnet provided by LBNL operating at 1.9 K in superfluid helium. The samples will be placed in the background magnetic field, cooled to between 4.5 K and a user-specified upper limit, and will be powered with a super-conducting transformer at up to 100 kA. Additionally, this facility will be used to test high-field superconducting magnet models and demonstrators, including hybrid magnets, produced by the US Magnet Development Program. Presently, the various tasks of the project are at different stages of execution, from conceptual to ready-for-construction designs. Here, this paper describes the parameters and design status of the pit construction, cryostat, heat exchanger, lambda plate, power system, and quench protection and monitoring systems of the facility.

43 PARTICLE ACCELERATORS↗

Current Status of the High Field Cable Test Facility at Fermilab

Fermi National Accelerator Laboratory (FNAL) and Lawrence Berkeley National Laboratory (LBNL) are collaborating to construct a new High Field Vertical Magnet Test Facility (HFVMTF) designed for testing superconducting cables in high magnetic fields. This state-of-the-art facility will be situated at Fermilab and will provide capabilities comparable to EDIPO at PSI and FRESCA2 at CERN. The HFVMTF’s background magnetic field, reaching 15 T, will be generated by a magnet supplied by LBNL. The HFVMTF is a collaborative effort supported by the US DOE Offices of Science, High Energy Physics, and Fusion Energy Sciences. It will serve as a vital testbed for superconducting HTS cables, subjecting them to high magnetic fields and a wide range of temperatures, benefiting both scientific communities. Additionally, this facility will play a key role in testing high-field superconducting magnet models and demonstrators, including hybrid magnets, developed by the US Magnet Development Pro gram (MDP). These hybrid magnets, utilizing both LTS and HTS superconductors, are significant advancements toward achieving 18+ T dipoles for future hadron-hadron colliders. The presentation outlines the current status of the facility, covering aspects such as construction progress, cryostat designs, top and lambda plates, and systems for powering, quench protection, and monitoring.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

New Technologies for Power System Operation and Analysis, 1st Edition

New Technologies for Power System Operation and Analysis considers the very latest developments in renewable energy integration and system operation, including electricity markets and wide-area monitoring systems and forecasting. Helping readers quickly grasp the essential information needed to address renewable energy integration challenges, this new book looks at basic power system mathematical models, advanced renewable integration and system optimizations from transmission and distribution system sides. Sections cover wind, solar, gas and petroleum, making this a useful reference for all engineers interested in power system operation.

electricity markets↗

Low-Power, Flexible Sensor Arrays with Solderless Board-to-Board Connectors for Monitoring Soil Deformation and Temperature: Supporting Data

This dataset was used to assess the potential of a Soil Deformation and Temperature Monitoring System developed and presented in the article named "Low-Power, Flexible Sensor Arrays with Solderless Board-to-Board Connectors for Monitoring Soil Deformation and Temperature" and published in Sensors. There are 21 comma-delimited data files (.csv). 14 files contain current measurements performed in a lab setting, enabling the electrical evaluation of the sensor probe. These files are generated by the Keithley DMM6500 multimeter, and list the measured supply current (first column) as a function of time (3rd column). Another set of 6 files is also acquired in lab experiments, but contain soil temperature an deformation measurements, enabling an assessment of the developed device's accuracy. In these files, the first column contains the time (UTC), followed by the sensor's battery voltage and temperature and acceleration values (X, Y, Z) in subsequent columns. The measurements were acquired every 5 seconds. Another .csv file contains field data in a similar format (time, temperature, acceleration) collected at the Teller road (mile 27) site near Nome, Alaska with one probe. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Adding power of artificial intelligence to situational awareness of large interconnections dominated by inverter‐based resources

Abstract Large‐scale power systems exhibit more complex dynamics due to the increasing integration of inverter‐based resources (IBRs). Therefore, there is an urgent need to enhance the situational awareness capability for better monitoring and control of power grids dominated by IBRs. As a pioneering Wide‐Area Measurement System, FNET/GridEye has developed and implemented various advanced applications based on the collected synchrophasor measurements to enhance the situational awareness capability of large‐scale power grids. This study provides an overview of the latest progress of FNET/GridEye. The sensors, communication, and data servers are upgraded to handle ultra‐high density synchrophasor and point‐on‐wave data to monitor system dynamics with more details. More importantly, several artificial intelligence (AI)‐based advanced applications are introduced, including AI‐based inertia estimation, AI‐based disturbance size and location estimation, AI‐based system stability assessment, and AI‐based data authentication.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Power system model parameter conditioning tool

A power system model parameter conditioning tool including a server control processor in communication with phasor measurement unit monitored data records of multiple disturbance events, a model calibration unit providing event screening, power system model simulation, and simultaneous tuning of model parameters. The model calibration performing a simulation using default model parameters, the processor comparing the simulation results to the monitored data. If the prediction is within threshold, then terminating conditioning; else performing parameter identifiability analysis to determine differing effects of various model parameters on power system model accuracy, selecting a parameter set causing a degradation in power system model prediction, and updating the default model parameters corresponding to members of the parameter set with values selected to reduce the degradation. A method and a non-transitory computer readable medium are also disclosed.

Baone, Chaitanya Ashok↗

A Localized Cyber Threat Mitigation Approach For Wide Area Control of FACTS

We propose a localized oscillation amplitude monitoring (OAM) method for the mitigation of cyber threats directed at the wide area control (WAC) system used to coordinate control of Flexible AC Transmission Systems (FACTS) for power oscillation damping (POD) of active power flow on inter-area tie lines. The method involves monitoring the inter-area tie line active power oscillation amplitude over a sliding window. We use system instability - inferred from oscillation amplitudes growing instead of damping - as evidence of an indication of a malfunction in the WAC of FACTS, possibly indicative of a cyber attack. Monitoring the presence of such a growth allows us to determine whether any destabilizing behaviors appear after the WAC system engages to control the POD. If the WAC signal increases the oscillation amplitude over time, thereby diminishing the POD performance, the FACTS falls back to POD using local measurements. The proposed method does not require an expansive system-wide view of the network. We simulate replay, control integrity, and timing attacks for a test system and present results that demonstrate the performance of the OAM method for mitigation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Technology Maturation of Wireless Harsh Environment Sensors For Improved Condition Based Monitoring Of Coal Fired Power Generation

The overall goal of this project was to demonstrate and develop the usage of high-temperature (HT) harsh-environment (HE) wireless surface acoustic wave resonator (SAWR) sensor technology to promote reliable maintenance through condition-based maintenance (CBM) for field applications in harsh service conditions associated with power plant environments. The project aimed to advance the HT HE wireless SAWR sensor technology from TRL 5 to TRL 7. In addition to HT HE wireless temperature sensing, efforts were dedicated during this project to investigate, develop and increase the TRL from 3 to 5 for the following technologies: (a) HT HE strain sensors to address additional CBM monitoring needs, such as boiler tube mechanical / thermal stresses, which can provide early indications for boiler tube cracking and failure; and (b) HT aluminum nitride (AlN) and scandium aluminum nitride (ScAlN) based piezoelectric thin film fabrication and implementation of SAW sensors, with the goal of releasing the need to use single crystal piezoelectric materials for SAWRs and thus broaden possible technology applications to non-planar and harder to modify surfaces. To achieve the goals mentioned above, UMaine and its partner, Environetix Technologies Corporation, established partnerships with the following power plants: Longview Power (Maidsville, WV), a coal-fired power plant; Penobscot Energy Recovery Corp (PERC, Orrington, ME), a waste-to-energy power plant; and the UMaine Steam Plant (Orono, ME), an oil / natural gas power plant. To realize wireless HT HE SAWR sensor systems in these harsh service conditions, the University of Maine research team worked with Environetix and these power plants to define, design, fabricate, test and validate a mature prototype wireless temperature SAWR sensor system for boiler tube applications within the HT HE of the reheater pass damper chamber to directly and wirelessly monitor the temperature at eighteen independent boiler tube locations. The system included three levels, or “tiers”, of wireless communication to enable remote monitoring: Tier 1, the wireless link in the reheater pass damper chamber directly accessing the sensors on the boilers; Tier 2, the wireless local area network link, transmitting processed sensor information within the power plant to the Tier 3, a commercial wireless signal carrier company for secure remote data monitoring outside of the power plant. Regarding the wireless sensor system installed at Longview Power, temperature information from the boilers was continuously transmitted from the Longview boilers at Maidsville, WV, to Environetix headquarters, Orono, ME, over a 34 month period, when the system was finally decommissioned. Strain sensors and piezoelectric ScAlN thin film sensors were successfully installed on the exhaust duct at the UMaine Steam Power plant. The advances in wireless strain sensors and thin film piezoelectric film fabrication and testing were performed mostly in UMaine laboratories and field tested at the UMaine Steam Plant, due to its close proximity to UMaine/Environetix, access to the plant facility, and due to difficulties in accessing the other power plants during the COVID shut-down period. The project accomplished the TRL level increase of the targeted CBM technologies through the successful fabrication, installation, test, and validation of dedicated and commercial wireless sensor systems, utilizing the three different power plants. The outcomes of this project, including the wireless sensor data capability, are expected to yield an advance for CBM in harsh power plant environments. The reduction of maintenance costs, improved safety during plant operation, and increased power plant efficiency will lead to increased revenues (i.e., fewer forced outages) due to better process monitoring enabled by the wireless HT HE SAWR temperature sensor technology.

20 FOSSIL-FUELED POWER PLANTS↗

An all-electronic fail-safe for stimulated Brillouin scattering suppression

The mitigation of transverse stimulated Brillouin scattering (SBS) via phase modulation is mandatory to avoid damage in high-energy laser systems. A novel fail-safe system that indirectly monitors the optical bandwidth applied to suppress SBS by monitoring the input, reflected, and through rf power of the SBS-suppression lithium-niobate phase modulator is demonstrated. The fail-safe system has high sensitivity and reliability provided by optimized redundant circuits for power monitoring and fail-safe decision logic. Calibration of the fail-safe’s thresholds is straightforward. Furthermore, the fail-safe circuitry reacts within 45 ns to stop an incorrectly modulated pulse by blocking the propagation of an electronic timing trigger.

fail-safe↗

2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)

Recent proliferation of distributed energy sources in distribution or sub-transmission systems necessitates close monitoring of these three-phase power grids which typically operate under unbalanced loading conditions. Unlike the transmission systems where the network equations are commonly based on the positive sequence component models, a detailed three phase model will have to be used in implementing network applications for these systems. In the specific case of the state estimator, where measurement and parameter errors may bias the solution, bad data and parameter error detection algorithms should also be incorporated. Implementing the state estimator and error detection algorithms for three-phase systems impose additional computational burden and modifications to the state estimation code. This paper proposes a practical solution to avoid these issues by using synchronized phasor measurements and modal decoupling. The previously developed parameter error detection algorithm based on the normalized Lagrange multipliers (NLM) test is applied to the measurements independently in each mode in parallel, not only saving CPU time but also avoiding new code development for a three-phase estimator. Different parameter error scenarios are created and tested to verify the effectiveness of the proposed error detection approach.

Khalili, Ramtin↗

Enabling Power at Sea: Opportunities for Expanded Ocean Observations through Marine Renewable Energy Integration

The blue economy is a dynamic and rapidly growing movement that captures the interplay between economic, social, and ecological sustainability of the ocean and encompasses numerous maritime sectors and activities (e.g., commerce and trade; living resources; renewable energy; minerals, materials, and freshwater; and ocean health and data). The demand for ocean data to inform scientific, risk reduction, and national security needs is leading to a large increase in the number of deployed ocean observation and monitoring systems, most of which require increased power. Because ocean observation systems are often placed in remote locations, they primarily rely on energy storage (or in some cases in situ energy generation) to power instruments and equipment, which imposes limits on sampling rates, deployment times, and spatiotemporal resolution of data. The U.S. Department of Energy Water Power Technologies Office is exploring the potential for marine renewable energy (MRE) devices (largely wave and tidal energy converters) to provide power to support multiple blue economy opportunities. A portion of these opportunities focus on power at sea markets for providing power in off-grid and offshore locations to support a variety of ocean-based activities, including ocean observation and navigation, underwater vehicle charging, marine aquaculture, marine algae farming, and seawater mining. Initially, research has focused on better understanding how and where MRE can provide a consistent source of reliable power to extend ocean observing missions, including operation of autonomous underwater vehicles. Online surveys as well as phone and in-person interviews were conducted with experts in the field of ocean observing systems and observatories to gather end-user requirements, determine energy needs, identify opportunities for codevelopment, and pinpoint constraints for MRE to meet those needs. The surveys and interviews provided feedback on the potential for powering devices and vehicles using MRE, including identifying common themes and challenges that will inform foundational research and development steps needed to advance the integration of MRE with ocean observing systems. In most cases, additional power generation on the order of watts was identified as significantly beneficial to enhancing ocean observations capabilities.

16 TIDAL AND WAVE POWER↗

Powering the Blue Economy: Progress Exploring Marine Renewable Energy Integration With Ocean Observations

The blue economy is a dynamic and rapidly growing movement that captures the interplay between economic, social, and ecological sustainability of the ocean and encompasses numerous maritime sectors and activities (e.g., commerce and trade; living resources; renewable energy; minerals, materials, and freshwater; and ocean health and data). The demand for ocean data to inform scientific, risk reduction, and national security needs is leading to a large increase in the number of deployed ocean observation and monitoring systems, most of which require increased power. Because ocean observation systems are often placed in remote locations, they primarily rely on energy storage (or in some cases in situ energy generation) to power instruments and equipment, which imposes limits on sampling rates, deployment times, and spatiotemporal resolution of data. The U.S. Department of Energy Water Power Technologies Office is exploring the potential for marine renewable energy (MRE) devices (largely wave and tidal energy converters) to provide power to support multiple blue economy opportunities. A portion of these opportunities focus on power at sea markets for providing power in off-grid and offshore locations to support a variety of ocean-based activities, including ocean observation and navigation, underwater vehicle charging, marine aquaculture, marine algae farming, and seawater mining. Initially, research has focused on better understanding how and where MRE can provide a consistent source of reliable power to extend ocean observing missions, including operation of autonomous underwater vehicles. Online surveys as well as phone and inperson interviews were conducted with experts in the field of ocean observing systems and observatories to gather end-user requirements, determine energy needs, identify opportunities for codevelopment, and pinpoint constraints for MRE to meet those needs. The surveys and interviews provided feedback on the potential for powering devices and vehicles using MRE, including identifying common themes and challenges that will inform foundational research and development steps needed to advance the integration of MRE with ocean observing systems. In most cases, additional power generation on the order of watts was identified as significantly beneficial to enhancing ocean observations capabilities.

marine renewable energy, powering the blue economy↗

Leveraging Optimal Sparse Sensor Placement to Aggregate a Network of Digital Twins for Nuclear Subsystems

Nuclear power plants (NPPs) require continuous monitoring of various systems, structures, and components to ensure safe and efficient operations. The critical safety testing of new fuel compositions and the analysis of the effects of power transients on core temperatures can be achieved through modeling and simulations. They capture the dynamics of the physical phenomenon associated with failure modes and facilitate the creation of digital twins (DTs). Accurate reconstruction of fields of interest (e.g., temperature, pressure, velocity) from sensor measurements is crucial to establish a two-way communication between physical experiments and models. Sensor placement is highly constrained in most nuclear subsystems due to challenging operating conditions and inherent spatial limitations. This study develops optimized data-driven sensor placements for full-field reconstruction within reactor and steam generator subsystems of NPPs. Optimized constrained sensors reconstruct field of interest within a tri-structural isotropic (TRISO) fuel irradiation experiment, a lumped parameter model of a nuclear fuel test rod and a steam generator. The optimization procedure leverages reduced-order models of flow physics to provide a highly accurate full-field reconstruction of responses of interest, noise-induced uncertainty quantification and physically feasible sensor locations. Accurate sensor-based reconstructions establish a foundation for the digital twinning of subsystems, culminating in a comprehensive DT aggregate of an NPP.

42 ENGINEERING↗

Rapid Monitoring and Defense Approach for Resilience Improvement of Grid Cyber Security

Cyber-physical systems and electric utilities significantly depend on the reliability and efficiency of information and operational technology. However, false data injection attacks based on synchrophasor measurement data pose a serious threat to the safe and reliable operation of modern power systems. Here, to mitigate this problem, a rapid monitoring and defense approach is proposed to defend against cyber attacks. Initially, the Time and Frequency based Convolutional neural Network (TFCN) is proposed to detect different types of attacks. Within the TFCN, the advances are that both time and frequency domain information can be fused without extra spectrum analysis methods, and can save detection time to speed the calculation efficiency using the developed time-frequency block. Next, a comprehensive defense strategy is developed for multiple cyber attacks to ensure the stability and resilience of the power system according to the feedback detection results. The advances of this strategy are that different control strategies can be automatically selected to recover the stability to the greatest extent according to the detected attacks. To verify the effectiveness of the proposed approach, the high-speed frequency measurements collected from the wide-area monitoring system are used. The results demonstrate that the cyber attack detection performance can reach 95.57% accuracy, outperforming both traditional and some advanced neural networks. Importantly, the defense strategy is conducted and verified in a modified IEEE 39 bus system as well, which illustrates profound performance in faster stability restoration.

Comprehensive defense strategy↗