Robustness of Power Distribution System: A Comparative Study of Network and Performance Based Metrics
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Utilities and stakeholders need a standardized mechanism for evaluating how future climate and hydrologic conditions translate to water-related risks for power grid assets and systems to support planning decisions. Yet, no such mechanism exists. To address this need, our goals are to: (1) Develop and execute a state-of-the-art multi-model framework to assess future climate-water impacts and risks to the grid, including sensitivities to varying hydrologic drivers and infrastructure scenarios. (2) Create a standardized interactive visualization platform, using data from the climate-water risk assessments, that enables stakeholders to evaluate climate-water impacts, risks, and adaptation measures for power systems.
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Schweitzer Engineering Laboratories (SEL) and Oregon State University (OSU) received over 27 terabytes of electrical power system phasor measurement unit (PMU) data for the Eastern, Western, and ERCOT interconnections. The dataset includes measurements spread across 446 PMUs from early 2016 to mid 2018 depending on the interconnect. The full dataset was split into a training and test (holdout) dataset by PNNL. All data was received in the Apache Parquet format. The overarching goal of this project is to develop and execute a strategy to mitigate data anomalies, perform analysis on the dataset, and detect anomalous events in the data.
Phasor measurement units (PMUs) provide high temporal-resolution synchrophasor measurements for power system monitoring and control. The frequent data quality issues, such as missing and bad data, prevent the incorporation of synchrophasor data in real-time operations. Most existing data-driven data recovery methods assume the power system dynamics can be approximated by a linear dynamical system, and the recovery performance degrades significantly when the power system is experiencing nonlinear dynamics during significant events. Here, this paper proposes a data-driven Bayesian nonlinear synchrophasor data recovery method (Ba-NSDR) that can recover a consecutive time period of simultaneous data losses or errors across all channels, even when the underlying system is highly nonlinear. The idea is to lift the Hankel matrix of the spatial-temporal synchrophasor data to a higher dimension such that the lifted Hankel matrix is low-rank in that space and can be processed with the kernel trick. Our proposed Bayesian method then infers the probabilistic distributions of synchrophasor from the partial observations. Some distinctive features of Ba-NSDR include an uncertainty index to measure the accuracy of the recovery result and the robustness to parameter selections. Our method is verified on both synthetic and recorded event datasets.
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While Global Positioning System signals are widely used as the synchronized timing Sources for wide-area measurement systems for power grid monitoring and control, they are vulnerable to failures and malicious attacks. To address this Problem, an alternative kind of timing sources, the millisecond pulsars, were proposed to serve the power grid as they are more precise and physically indestructible. Millisecond pulsars are a kind of neutron stars that emit radio pulse signals that have extremely stable periods of milliseconds. However, the observed pulse Signals from pulsars cannot be directly used for timing because of their low signal-to-noise ratio and the dispersion effects of interstellar medium. In this paper, the precise timing method based on pulsar observation data is proposed to interpret the pulsar observation data and therefrom to generate precise timing signal for the power grid synchronization. In our proposed method,. incoherent de-dispersion is used on the observation data to mitigate the effect of interstellar medium. dispersion. Then spectrum analysis and segment folding are used to precisely estimate the local pulsar period. Finally the standard pulse per second signal is generated from. the estimated pulsar period and its precision. is analyzed. Experiments with the observation data of the pulsar based timing signal can be more accurate compared to GPS timing signals.
Power electronics are increasingly being used to condition electricity for a wide array of applications, such as transportation (on land, air, and water), data centers, radio frequency, directed energy, wind, solar, and grid-tied applications. To increase power density, performance, efficiency, and reliability and reduce cost, innovations and developments are needed in the multiphysics packaging of power electronics at a die, module, and converter level. This includes fundamental research and development related to emerging high-voltage, high-temperature, and high-switching-frequency power electronics; packaging materials; thermal materials and interfaces; fluid-based thermal management technologies; reliability; condition monitoring; and prognostics. To address these important aspects, this Special Section on Multiphysics Aspects of Power Electronics Packaging includes several articles to be published in two parts. More details are given below on the articles included in the first part.
Solar cell spacecraft power systems, and measurements of Mariner-type and Surveyor batteries
Emerging microelectromechanical sculpturing technology is presently extended, in conjunction with the use of deep semiconductor impurities having extreme flow sensitivities, small masses for shortest time response, and unconventional electrode schemes for elevated-temperature operation, for rocket-engine fuel flow sensing tasks. The radiation component of heat transfer is negligible, so that the device operates on the basis of conduction and convection loss.
Varactor diode multipliers are a critical part of many THz measurement systems. The power and efficiencies of these devices limit the available power for THz sources. Varactor operation is determined by the physics of the varactor device and a careful doping profile design is needed to optimize the performance. Higher doped devices are limited by junction breakdown and lower doped structures are limited by current saturation. Higher doped structures typically have higher efficiencies and lower doped structures typically have higher powers at the same operating frequency and impedance level. However, the device material properties are also a function of the operating temperature. Recent experimental evidence has shown that the power output of a multiplier can be improved by cooling the device. We have used a particle Monte Carlo simulation to investigate the temperature dependent velocity vs. electric field in GaAs. This information was then included in a nonlinear device circuit simulator to predict multiplier performance for various temperatures and device designs. This paper will describe the results of this analysis of temperature dependent multiplier operation.
Techniques are described for disaggregation of renewable energy generation on an electricity distribution system. Aggregate power measurements are identified a distribution substation. Active power load of the distribution substation and active power generated by renewable energy sites can be disaggregated from the aggregate power measurements.
Background and purpose: Magnetic resonance imaging (MRI) scanners are a major contributor to greenhouse gas emissions from the healthcare sector, and efforts to improve energy efficiency and reduce energy consumption rely on quantification of the characteristics of energy consumption. The purpose of this work was to develop a semi-automatic analytical methodology for the characterization of the energy consumption of MRI systems using only the load duration curve (LDC). LDCs are a fundamental tool used across various fields to analyze and understand the behavior of loads over time. Methods: An electric current transformer sensor and data logger were installed on two 3T MRI scanners from two vendors, termed M1 (outpatient scanner) and M2 (inpatient/emergency scanner). Data was collected for 1 month (7/11/2023 to 8/11/2023). Active power was calculated, assuming a balanced three-phase system, using the average current measured across all three phases, a 480 V reference voltage for both machines, and vendor-provided power factors. An LDC was constructed for each system by sorting the active power values in descending order and computing the cumulative time (in units of percentage) for each data point. The first derivative of the LDC was then computed (LDC’), smoothed by convolution with a window function (sLDC’), and used to detect transitions between different system modes including (in descending power levels): scan, prepared-to-scan, idle, low-power, and off. The final, segmented LDC was used to measure time (% total time), total energy (kWh), and mean power (kW) for each system mode on both scanners. The method was validated by comparing mean power values, computed using the segmented 1-month LDC, for each nonproductive system mode (i.e., prepared-to-scan, idle, lower-power, and off) against power levels measured after a deliberate system shutdown was performed for each scanner (1 day worth of data). Results: The validation revealed differences in mean power values <1.4% for all nonproductive modes and both scanners. In the scan system mode, the mean power values ranged from 29.8 to 37.2 kW and the total energy consumed for 1 month ranged from 11 106 to 14 466 kWh depending on the scanner. Over the course of 1 month, the portion of time the scanners were in nonproductive modes ranged from 76% to 80% across scanners and the nonproductive energy consumption ranged from 8010 to 6722 kWh depending on the scanner. The M1 (outpatient) scanner consumed 99.9 and 183.9 kWh/day in idle mode for weekdays and weekends, respectively, because the scanner spent 23% more time proportionally in idle mode on the weekends. Conclusions: A semi-automatic method for quantifying energy consumption characteristics of MRI scanners was introduced and validated. This method is relatively simple to implement as it requires only power data from the scanners and avoids the technical challenges associated with extracting and processing scanner log files. Finally, the methodology enables quantitative evaluation of the power, time, and energy characteristics of MRI scanners in scan and nonproductive system modes, providing baseline data and the capability of identifying potential opportunities for enhancing the energy efficiency of MRI scanners.
The measurement of reactive power has been challenging for over a century. By the 1920s, the IEC and the AIEE were seeking new definitions for reactive power, specifically to handle distorted waveforms and unbalanced systems. Solutions had not and have not been found. This paper shows there are two aspects to the problem. First, the conceptual underpinning of reactive power provides a very shaky foundation for the design of an instrument. Second, the kind of instrument needed is one that has been largely unrecognized in the power engineering field. It is an operational measurement. These aspects of the measurement have been taken into account in IEEE Standard 1459, presently undergoing revision by a working group of the IEEE PES Power System Instrumentation and Measure¬ments Committee.
A control system for autonomous distribution and control of electrical power during space missions is being developed. This system should free the astronauts from localizing faults and reconfiguring loads if problems with the power distribution and generation components occur. The control system uses an object-oriented simulation model of the power system and first principle knowledge to detect, identify, and isolate faults. Each power system component is represented as a separate object with knowledge of its normal behavior. The reasoning process takes place at three different levels of abstraction: the Physical Component Model (PCM) level, the Electrical Equivalent Model (EEM) level, and the Functional System Model (FSM) level, with the PCM the lowest level of abstraction and the FSM the highest. At the EEM level the power system components are reasoned about as their electrical equivalents, e.g, a resistive load is thought of as a resistor. However, at the PCM level detailed knowledge about the component's specific characteristics is taken into account. The FSM level models the system at the subsystem level, a level appropriate for reconfiguration and scheduling. The control system operates in two modes, a reactive and a proactive mode, simultaneously. In the reactive mode the control system receives measurement data from the power system and compares these values with values determined through simulation to detect the existence of a fault. The nature of the fault is then identified through a model-based reasoning process using mainly the EEM. Compound component models are constructed at the EEM level and used in the fault identification process. In the proactive mode the reasoning takes place at the PCM level. Individual components determine their future health status using a physical model and measured historical data. In case changes in the health status seem imminent the component warns the control system about its impending failure. The fault isolation process uses the FSM level for its reasoning base.
NASA Glenn Research Center is developing flywheels for space systems. A single axis laboratory version of an integrated power and attitude control (IPACs) system has been experimentally demonstrated. This is a significant step on the road to a flight qualified three axes IPACS system. The presentation outlines the flywheel development process at NASA GRC, the experimental hardware and approach, the IPACS control algorithm that was formulated and the results of the test program and then proposes a direction for future work. GRC has made progress on flywheel module design in terms of specific energy density and capability through a design and test program resulting in three flywheel module designs. Two of the flywheels are used in the 1D-IPACS experiment with loads and power sources to simulate a satellite power system. The system response is measured in three power modes: charge, discharge, and charge reduction while simultaneously producing a net output torque which could be used for attitude control. Finally, recommendations are made for steps that should be taken to evolve from this laboratory demonstration to a flight like system.
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New submount technology is essential for the development of conductively cooled high power diode laser. The simulation and experimental results indicate that thermal conductivity of submount for high power laser-diode must be at least 600 W/m/k or higher for stable operation. We have simulated several theoretical thermal model based on new submount designs and characterized high power diode lasers to determine temperature effects on the performances of laser diodes. The characterization system measures the beam power, output beam profile, temperature distribution, and spectroscopic property of high power diode laser. The characterization system is composed of four main parts: an infrared imaging camera, a CCD camera, a monochromator, and a power meter. Thermal characteristics of two commercial-grade CW 20-W diode laser bars with open heat-sink type were determined with respect to the line shift of emission spectra and beam power stability. The center wavelength of laser emission has a tendency to shift toward longer wavelength as the driving current and heat sink temperature are increased. The increase of heat sink temperature decreases the output power of the laser bar too. Such results lay the guidelines for the design of new submount for high power laser-diodes.