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AMTEC power systems are designed for use on extended space missions. During the lifetime of such missions the power available for the spacecraft will depend on the degradation of the system performance. Development of a tool that allows monitoring of the system degradation will provide an aid in dtermining the condition of the power source.
Advanced solar cell power systems to reduce weight and withstand thermal stress conditions of Interplanetary Monitoring Platform /IMP-D/
Modern power grids are fast-changing and thus require real-time monitoring and online stability assessment. With the rapid development of machine learning (ML) techniques, using data-driven models to provide fast and accurate estimations of power system stability marginal information, such as frequency nadir for frequency stability and critical clearing time (CCT) for transient stability, have become possible. However, despite the numerous research on ML-based methods for frequency nadir and CCT prediction, there is limited work on the impact of different network topology changes. Furthermore, most previous studies only focused on small or synthetic systems, and there is a lack of research on actual large power system models. In this paper, the above issues are addressed by studying the actual U.S. Western Electricity Coordinating Council (WECC) system model with more than 20,000 buses. Massive simulations are conducted in PowerWorld Simulator to study the impact of various topology change scenarios on both frequency stability and transient stability. System operating information is extracted from the success dispatch cases of various network topologies to generate a comprehensive dataset for ML-based models. Two ML methods, random forest (RF) and multilayer perceptron (MLP) neural network, are trained and tested for both frequency nadir prediction and CCT prediction. Test results have proven the models are capable of online stability assessment for large power networks such as the WECC system with sufficient accuracy.
Energetic particle instruments on board Global Positioning System (GPS) satellites form a powerful global prompt proton sensor network (GPPSn) that provides an unprecedented opportunity to monitor and characterize solar energetic protons targeting the Earth. The medium-Earth orbits of the GPS constellation have the unique advantage of allowing solar energetic protons to be simultaneously measured from multiple points in both open- and closed-field line regions. Examining two example intervals of solar proton events, we showcase in this study how GPS proton data are prepared, calibrated, and utilized to reveal important features of solar protons, including their source, acceleration/scattering by interplanetary shocks, the relative position of Earth when impinged by these shocks, the shape of solar particle fronts, the access of solar protons inside the dynamic geomagnetic field, and temporally varying proton distributions in both energy and space. By comparing to Van Allen Probes data, GPS proton observations are further demonstrated not only to be useful for qualitatively monitoring the dynamics of solar protons but also for quantitative scientific research including determining cutoff L-shells. Finally, our results establish that this GPPSn can join forces with other existing solar proton monitors and contribute to observing, warning, understanding, and ultimately forecasting the incoming solar energetic proton events.
In this work, a distributed frequency divider is proposed to estimate power system bus frequency with a limited number of PMUs while considering the inertial contributions from double-fed induction generators (DFIGs). The key idea is to reformulate the original frequency divider by modeling the contributions of DFIGs with inertia emulation and external regional power system through Thevenin equivalents. The distributed frequency divider is general and able to estimate local bus frequencies in a distributed manner. Besides, only the knowledge of the rotor speeds of synchronous generator, boundary bus frequencies and terminal bus frequencies of DFIGs as well as the admittance matrix are required to estimate the frequencies at all buses. This is drastically different from existing approaches that require system observability by PMUs to monitor all bus frequencies. Numerical results carried out on the IEEE 39-bus and modified 118-bus power systems with DFIGs demonstrate and effectiveness and robustness of the proposed method.
Estimates of the power level of a nuclear reactor based on measurements from an independent monitoring sensor system can help in the compliance verification of its declared operations. We present a three-level fusion method to estimate the power level of a nuclear reactor using features derived from infrared, electromagnetic, and acoustic sensor measurements collected in proximity to the reactor. Based on a simplified analytical model of the secondary coolant system of the reactor, we identify partial regression functions of the power level in terms of the temperature difference between inlet and outlet of coolant pipes, and the activity levels of four fans and four pumps, which are estimated as features from the sensor measurements. The power level estimator employs a combination of aggregate and complementary fusion steps at three levels to incorporate the multi-modal features in a structure that reflects the secondary cooling system and its partial regression functions. Using the measurements from a test campaign at an operational reactor, we show that this estimator achieves 3.47% or lower root mean square error under 5-fold cross validation. More generally, these results illustrate a progressive reduction in estimation error as additional modalities are appropriately incorporated, and that the fuser outperforms single modality features and their sub-combinations.
Topics covered include: Amperometric Solid Electrolyte Oxygen Microsensors with Easy Batch Fabrication; Two-Axis Direct Fluid Shear Stress Sensor for Aerodynamic Applications; Target Assembly to Check Boresight Alignment of Active Sensors; Virtual Sensor Test Instrumentation; Evaluation of the Reflection Coefficient of Microstrip Elements for Reflectarray Antennas; Miniaturized Ka-Band Dual-Channel Radar; Continuous-Integration Laser Energy Lidar Monitor; Miniaturized Airborne Imaging Central Server System; Radiation-Tolerant, SpaceWire-Compatible Switching Fabric; Small Microprocessor for ASIC or FPGA Implementation; Source-Coupled, N-Channel, JFET-Based Digital Logic Gate Structure Using Resistive Level Shifters; High-Voltage-Input Level Translator Using Standard CMOS; Monitoring Digital Closed-Loop Feedback Systems; MASCOT - MATLAB Stability and Control Toolbox; MIRO Continuum Calibration for Asteroid Mode; GOATS Image Projection Component; Coded Modulation in C and MATLAB; Low-Dead-Volume Inlet for Vacuum Chamber; Thermal Control Method for High-Current Wire Bundles by Injecting a Thermally Conductive Filler; Method for Selective Cleaning of Mold Release from Composite Honeycomb Surfaces; Infrared-Bolometer Arrays with Reflective Backshorts; Commercialization of LARC (trade mark) -SI Polyimide Technology; Novel Low-Density Ablators Containing Hyperbranched Poly(azomethine)s; Carbon Nanotubes on Titanium Substrates for Stray Light Suppression; Monolithic, High-Speed Fiber-Optic Switching Array for Lidar; Grid-Tied Photovoltaic Power System; Spectroelectrochemical Instrument Measures TOC; A Miniaturized Video System for Monitoring Drosophila Behavior; Hydrofocusing Bioreactor Produces Anti-Cancer Alkaloids; Creep Measurement Video Extensometer; Radius of Curvature Measurement of Large Optics Using Interferometry and Laser Tracker n-B-pi-p Superlattice Infrared Detector; Safe Onboard Guidance and Control Under Probabilistic Uncertainty; General Tool for Evaluating High-Contrast Coronagraphic Telescope Performance Error Budgets; Hidden Statistics of Schroedinger Equation; Optimal Padding for the Two-Dimensional Fast Fourier Transform; Spatial Query for Planetary Data; Higher Order Mode Coupling in Feed Waveguide of a Planar Slot Array Antenna; Evolutionary Computational Methods for Identifying Emergent Behavior in Autonomous Systems; Sampling Theorem in Terms of the Bandwidth and Sampling Interval; Meteoroid/Orbital Debris Shield Engineering Development Practice and Procedure; Self-Balancing, Optical-Center-Pivot, Fast-Steering Mirror; Wireless Orbiter Hang-Angle Inclinometer System; and Internal Electrostatic Discharge Monitor - IESDM.
For several years the TechEdSat flight series (TES-n), developed by the Nano Orbital Workshop (NOW) group at NASA Ames, has relied upon an in-house developed unit to serve both EPS (Electrical Power System) and C&DH (Command and Data Handling) roles along with low data-rate telemetry functions, i.e., serving as the ‘core’ of the spacecraft bus. This ‘core’ has a considerable task given the rapid cadence of the TES program and the typically low-TRL of payloads; configurability and compatibility are key to prevent mission-specific hardware. However, at only 15 watts the current core has become insufficient to support the program’s growing missions and increasingly demanding payloads. To this end, the NOW program is developing new cores to support two TES mission classes: a single-PCB ‘MiniCore’ designed to support 80-watt missions 6U or smaller in LEO, and a three-PCB, radiation-tolerant ‘StackCore’ designed to support 6U and larger missions over 500 watts in LEO and beyond. The ‘MiniCore’ design consists of three main segments: a processor-agnostic C&DH, a software-configured EPS, and a backup low data-rate radio. The design philosophy was to enable rapid-manufacture in a turbulent supply chain, hence the design consists of COTS parts with a focus on those able to be drop-in replaced with radiation-tolerant versions when demanded by the mission. As a single PC-104 sized circuit board, power density and ease of integration also dominated design, demanding the use of modern features such as single-point USB-C for easy charging and monitoring of the spacecraft on the ground. The ‘MiniCore’ can support 80 watts of load, 140 watt-hours of storage, and over 20 watts of optimized solar generation with extensive power monitoring throughout. The ‘MiniCore’ supports one battery pack, six solar-panels, six loads, five actuators, Iridium SBD, and an internal 802.15.4 network. Additionally, the processor-agnostic design can accept any PJRC Teensy 3.x or Adafruit Feather microcontroller unit to enable processor scaling with mission requirements or environment. It is expected a development unit of this design will be completed before conference. The ‘StackCore’ design consists of three stacked PC-104 sized circuit boards: one dedicated to power generation and storage, one dedicated to power distribution, and one dedicated to C&DH tasks. This delineation is necessary to support the transition from highly integrated ICs to discrete analog circuitry, enabling a primarily analog control power system able to operate without software in a radiation environment with finer monitoring compared to the ‘MiniCore’ design. The planned base architecture supports over 500 watts of load, 250 watt-hours of storage, and over 80 watts of optimized solar generation. The power distribution board allows for the use of daughter cards hosting custom converters or interfaces for payloads, in addition to the software-configured supplies used on the ‘MiniCore’. This core stack will be managed by a Vorago ARM M4 microcontroller and support the same wireless communications as the ‘MiniCore’, with optional integration of a NOW S-band radio and attitude determination sensors for ‘black box’ functionality. It is expected the prototype will still be in development during conference.
The ongoing rapid transformation of our energy supply challenges the operation and stability of electric power grids and other supply networks. This focus issue comprises new ideas and concepts in the monitoring and control of complex networks to address these challenges.
Phasor Measurement Units (PMUs) are critical for the Wide Area Measurement System (WAMS), especially for real-time grid monitoring, disturbance location, and situation awareness. Once they are damaged, the stable operation of power system will be affected directly and greatly. As new electronic devices in power system, their immunity to electromagnetic pulse (EMP) events needs to be studied. In this paper, an effective impedance measurement scheme is proposed for port impedance measurement of PMU. A non-uniform transmission line model is established to eliminate the impact of fixture in the de-embedding process. Then circuit of pulse current generator is established to generate damping sinusoid and double exponential wave applied to the port. Finally, by using measured impedance as load of the generator, the voltage and current responses of different ports are calculated in the pulsed current injection (PCI) simulation. Results shows the characteristics of port impedance, voltage and current waveforms. The relation between port impedance and the waveforms is discussed.
The main objective of the TOPEX Spacecraft is to monitor the World's oceans for both scientific.
As the power grid continues to evolve with advanced wide-area monitoring, protection, and control (WAMPAC) algorithms, there is an increasing need for realistic testbed environments with industry-grade software and hardware-in-the-loop (HIL) to perform verification and validation studies. Such testbed environments serve as ideal platforms to perform WAMPAC prototyping, operator training, and also to study the impacts of different types of cyberattack scenarios on the operation of the grid. In this paper, we introduce PRIME (PNNL cybeR physIcal systeMs tEstbed): the testbed that integrates real-time transmission system simulator with commercial industry grade energy management system (EMS) software and remote hardware-in-the-loop (RHIL). PRIME is an end-to-end, modular testbed that allows high-fidelity RHIL experimentation of a power system. We present two detailed case studies (fault location and clearing in transmission system, and operator training) to showcase the capabilities of our PRIME testbed. Finally, we briefly discuss some of the potential limitations of our testbed in terms of scalability and flexibility to setup larger test systems and identify directions for future work to address those limitations.
One of the most important contributions to neural networks comes from Kohonen, Helsinki/Espoo, Finland, who had the idea of self-organizating maps in 1981. He verified his idea by an algorithm of which many applications make use of. The impetus for this idea came from biology, a field where the Europeans have always been very active at several research laboratories. The challenge was to model the self-organization found in the brain. Today one goal is the development of more sophisticated neurons which model the biological neurons more exactly. They should come to a better performance of neural nets with only a few complex neurons instead of many simple ones. A lot of application concepts arise from this idea: Kohonen himself applied it to speech recognition, but the project did not overcome much more than the recognition of the numerals one to ten at that time. A more promising application for self-organizing maps is process control and process monitoring. Several proposals were made which concern parameter classification of semiconductor technologies, design of integrated circuits, and control of chemical processes. Self-organizing maps were applied to robotics. The neural concept was introduced into electric power systems. At Dortmund we are working on a system which has to monitor the quality and the reliability of gears and electrical motors in equipment installed in coal mines. The results are promising and the probability to apply the system in the field is very high. A special feature of the system is that linguistic rules which are embedded in a fuzzy controller analyze the data of the self-organizing map in regard to life expectation of the gears. It seems that the fuzzy technique will introduce the technology of neural networks in a tandem mode. These technologies together with the genetic algorithms start to form the attractive field of computational intelligence.
NASA’s Prediction of Worldwide Energy Resource (POWER) project facilitates the use of NASA Earth Science data holdings within the renewable energy, agricultural, and building heating/cooling design industries. POWER packages solar and meteorological data at various temporal levels from several NASA projects in a user friendly GIS-enabled web services system (https://power.larc.nasa.gov). Data users can access these data either through an intuitive data viewer, image services fully integrable with GIS analysis, connections in the cloud through an Amazon Web Services S3 Bucket, or fully customizable access through an API. Data provided by POWER has been successfully used by decision makers to support actions that address climate change. For example, POWER data has been used to remotely monitor solar array fields and integrated in a sizing tool for off-grid solar and storage systems. POWER data has also been coupled with key building decision tools to support design and retrofitting of building energy systems for energy efficiency and reduction of greenhouse gases. POWER is now developing climate services to provide time series of the projected future evolution of key quantities that interest our users, such as heating/cooling degree days, temperature, wind speed, and downwelling solar flux. We demonstrate the potential of the new climate services by presenting here a range of possible future changes in these quantities at different NASA centers across the continental United States. These data services are based on downscaled climate model data from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) data set. We highlight the important insights that new climate services can provide. Our climate services will help our user communities quantify the impacts of climate change to support their key decisions in planning for the future, both inside and outside the Federal Government, especially for decisions in renewable energy and in building heating and cooling.
With ongoing automation and digitization of the electric power system, several Phasor Measurement Units(PMUs) have been deployed for monitoring and control. PMU data can have multiple anomalies, and many of the researchers in the past have concentrated on training machine/deep learning algorithms offline for anomaly detection over PMU data (i.e., not in real time). These machine/deep learning algorithms, when trained offline on a sample rather than a population of the dataset, fail to consider the dynamic behavior of the power grid in real-time, resulting in low accuracy. Considering the dynamic behavior of the power grid (e.g., change in load, generation, distributed energy resources (DERs) switching, network, controls), the definition of data anomalies varies in time and requires online training. A fundamental challenge is to enable online (i.e., real-time) training of machine/deep learning algorithms for anomaly detection over streaming PMU data. While machine/deep learning is often desirable to manage data streams, training a deep learning algorithm over streaming PMU data is nontrivial due to changes in data statistics caused by dynamic streaming data. This paper proposes PMUNET: a novel device-level deep learning-based data-driven approach for anomaly detection, localization, and classification over streaming PMU data, using online learning and multivariate data-drift detection algorithm .Two variants of PMUNET, Dynamic data Change Driven Learning (DCDL) and Continuity Driven Learning (CDL), are proposed and compared. DCDL aims to train the deep learning algorithm whenever the definition of anomaly changes due to the power grid dynamics. On the other hand, CDL continuously trains the deep learning algorithm over the PMU data-stream. The experimental results verify that DCDL outperforms CDL and other efficient anomaly detection methods over multiple events such as faults and load/ generator/capacitor/DERs variations/switching for IEEE 14 and 39 Bus test system as well as real PMU industrial data. The result verifies that DCDL variant of PMUNET improves over existing approach with a gain of 2% - 10% in terms of accuracy, false-positive rate, and false-negative rate.
Sometimes referred to as regenerative life support systems, the concept includes an enclosed self-sufficient habitat that can independently support life for years on end. Such a system aims not only to produce its own food and water but to purify air and convert waste into useful byproducts. In the early 1990s, NASA was planning for an extended stay on Mars, and Bubenheim and his Ames colleagues were concentrating efforts on creating a complete ecological system to sustain human crewmembers during their time on the Red Planet. The main barrier to developing such a system, he says, is energy. Mars has no power plants, and a regenerative system requires equipment that runs on electricity to do everything from regulating humidity in the atmosphere to monitoring the quality of recycled water. The Ames group started looking at how to best make power on a planet that is millions of miles away from Earth and turned to a hybrid concept combining wind and solar power technologies. The reason was that Mars experiences frequent dust storms that can block nearly all sunlight. When theres a dust storm and the wind is blowing, the wind system could be the dominant power source. When the wind is not blowing and the sun is out, photovoltaics could be the dominant source, says Bubenheim.To develop and test the wind power technology, Ames turned to a remote, harsh environment here on Earth: the South Pole. The South Pole was a really good analog for Mars, says Bubenheim. The technology features for going to Mars were the same technology features needed to make something work at the South Pole.Around the same time that NASA started investigating energy technologies for the Red Planet, the National Science Foundation (NSF) was working on a redesign of their station at the South Pole. To power its operations, NSF used fuel that it flew to the remote location, but the Foundation recognized the benefits of also using onsite renewable energy technologies. In the winter they have small crews and their power requirements are less, says Bubenheim. In the summers, they bring in larger groups and photovoltaics could supply a lot of power. Using renewable energy technology could be a way of reducing the amount of fuel they have to fly in.Technology TransferTo advance wind turbine technology to meet the requirements of extremely harsh environments like that on Mars, Ames partnered with NSF and the Department of Energy. It was clear that a lot of the same features were also desirable for the cold regions of the Earth, says Bubenheim. NASA took the leadership on the team because we had the longest-term technology a Mars turbine. Years before, NSF had worked with a company called Northern Power Systems (NPS), based in Barre, Vermont, to deploy a 3-kilowatt wind turbine on Black Island off the coast of Antarctica.Sometimes referred to as regenerative life support systems, the concept includes an enclosed self-sufficient habitat that can independently support life for years on end. Such a system aims not only to produce its own food and water but to purify air and convert waste into useful byproducts. In the early 1990s, NASA was planning for an extended stay on Mars, and Bubenheim and his Ames colleagues were concentrating efforts on creating a complete ecological system to sustain human crewmembers during their time on the Red Planet. The main barrier to developing such a system, he says, is energy. Mars has no power plants, and a regenerative system requires equipment that runs on electricity to do everything from regulating humidity in the atmosphere to monitoring the quality of recycled water. The Ames group started looking at how to best make power on a planet that is millions of miles away from Earth and turned to a hybrid concept combining wind and solar power technologies. The reason was that Mars experiences frequent dust storms that can block nearly all sunlight. When there's a dust storm and the wind is blowing, the wind system could be the dominant power source. When the wind is not blowing and the sun is out, photovoltaics could be the dominant source, says Bubenheim.To develop and test the wind power technology, Ames turned to a remote, harsh environment here on Earth: the South Pole. The South Pole was a really good analog for Mars, says Bubenheim. The technology features for going to Mars were the same technology features needed to make something work at the South Pole.Around the same time that NASA started investigating energy technologies for the Red Planet, the National Science Foundation (NSF) was working on a redesign of their station at the South Pole. To power its operations, NSF used fuel that it flew to the remote location, but the Foundation recognized the benefits of also using onsite renewable energy technologies. In the winter they have small crews and their power requirements are less, says Bubenheim. In the summers, they bring in larger groups and photovoltaics could supply a lot of power. Using renewable energy technology could be a way of reducing the amount of fuel they have to fly in.Technology Transfer To advance wind turbine technology to meet the requirements of extremely harsh environments like that on Mars, Ames partnered with NSF and the Department of Energy. It was clear that a lot of the same features were also desirable for the cold regions of the Earth, says Bubenheim. NASA took the leadership on the team because we had the longest-term technology a Mars turbine.
Autonomous power management has been proposed as a method to perform optimization of power subsystem performance in connection with the management of multikilowatt space platforms. A concept for a 250-kW utility-type power subsystem was developed. A Cassegrain concentrator solar array primary source is conditioned by a solar array switching unit which supplies seventeen 220 +20 Vdc power channels. A power management subsystem provides the monitoring and control of the overall electrical power subsystem. The discussed system concept for autonomous management of high power space platforms utilizes on-board microprocessors in a decentralized data management architecture. A data bus protocol and a data bus contention resolution scheme were selected in conjunction with the dencentralized management architecture.
The design, fabrication, and testing of four power slip rings for synchronous orbit application are considered. Environmental and instrumentation systems necessary for monitoring electrical noise, friction, and brush wear in air and at less than 5 X 10 to the minus 8th power torr were developed. Composite brushes consisting of silver-molybdenum disulfide-graphite and silver-niobium diselenide-graphite were employed on rings of coin silver and rhodium plate. These four contact combinations were tested during ambient condition run-in at 150 and a humidity sequence at 0.1. The first nine months of a two year vacuum test performed at 0.1 rpm were completed.