Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Power System Operation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Orion Power Transfer: Impacts of a Battery-on-Bus Power System Architecture

The Orion Multi-Purpose Crew Vehicle (MPCV) has the capability to transfer power to a co-manifested payload (CPL) during transit from low-Earth orbit to the lunar vicinity. This paper discusses a time-phased parametric power analysis to determine the Orion power transfer capability limit. Charge and discharge curves were generated for various power transfer conditions and measured against various minimum system voltage limits. The Orion electrical power system (EPS) utilizes an unregulated bus architecture, which has important implications when the system is operating under very high load demand conditions, such as during power transfer. This analysis highlights three important effects of this architecture. First, increasing load demand decreases the maximum state of charge (SOC) the batteries can reach when charging. Second, increasing load demand also decreases the allowable battery depth of discharge. These two together can significantly reduce the effective useable capacity of the batteries. Finally, low battery voltage decreases the power generation of the solar arrays. This can lead to significantly longer recharge times or even push the system out of energy balance. These effects have important implications for mission design and vehicle operations and must be accounted for when conducting sizing and design of an unregulated spacecraft EPS.

Electrical Power System↗
DOE OSTI2023

Intra-hour Solar Irradiance Forecast in Multiple Locations using Deep Transfer Learning

In recent years, solar power system installation imposes several challenges on the operations of local and regional power grids due to the inherent variability of ground-level solar irradiance. This work proposes a novel real-time solar forecast methodology for intra-hour solar irradiance based on deep transfer learning from ground-based sky imager for time horizons ranging from 5-15 min. There are three unique aspects of the proposed methodology: (1) a Deep Learning based algorithm development which is modeled as a classification approach rather than a traditional regression approach; (2) the use of the Transfer Learning technique to show generalization capability, robustness, and portability of baseline model in the newly deployed location where availability of enough data for training is typically scarce, and (3) redefinition of point-based irradiation forecast error estimation technique with a window-based one that is more intuitive and user-friendly. The system is developed using multiple years of irradiance and sky image recording in New Jersey and one-year data from Colorado, USA. The method is validated against ground telemetry from these two locations of diverse geographic and climatic conditions. Results show that the forecasting method proposed in this work is robust and highly accurate (8% MAPE error) for multiple locations deployment.

Deep Learning, Convolution Neural Networks, transf↗
DOE OSTI2016

Preheating of fluid in a supercritical Brayton cycle power generation system at cold startup

Various technologies pertaining to causing fluid in a supercritical Brayton cycle power generation system to flow in a desired direction at cold startup of the system are described herein. A sensor is positioned at an inlet of a turbine, wherein the sensor is configured to output sensed temperatures of fluid at the inlet of the turbine. If the sensed temperature surpasses a predefined threshold, at least one operating parameter of the power generation system is altered.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

HTTR-GT/H2 test plant - system design - 18680

Pre-licensing basic design for a cogenerating HTGR test plant system is presented. The plant to be coupled to JAEA s existing 30 MWt 950 deg. C test reactor HTTR is intended as a system technology demonstrator for JAEA s commercial Gas turbine High Temperature Reactor Cogeneration (GTHTR300C) plant design. More specifically the test plant of HTTR-GT/H2 aims to 1) demonstrate the licensability of the GTHTR300C for electricity production by gas turbine and hydrogen cogeneration by thermochemical process and 2) confirm the operation control and safety of such cogeneration system. With construction and operation completion by 2025, the test plant is expected to be the first of a kind HTGR-powered cogeneration plant operating on the two advanced energy conversion systems of closed cycle helium gas turbine for power generation and thermochemical iodine-sulfur water-splitting process for hydrogen production. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Low Temperature CO2 Capture from an NGCC Flue Gas Using a Magnetically Stabilized, Inductively Heated Fluidized Bed Reactor

The lab sorbent testing finalized the sorbent composition and operating conditions for the integrated unit. The bench unit design included COMSOL simulation to finalize the coil design and select initial operating conditions of the power supply system. Fluidized bed testing with the induction heating verified that a heating efficiency of up to 90% can be achieved. The integrated bench unit operations provided valuable data confirming the feasibility of using induction heating for the desorption of CO2. Major challenge observed was the limited working capacity of the sorbent, requiring additional development in future projects. In addition, a large-scale reactor demonstration is required to mitigate the risk of uniform temperature distribution and heating efficiency over a large cross-sectional area when using induction heating.

Tong, Andrew↗
DOE OSTI2026

Primary Heat Transport System Design Considerations for Xcimer Energy’s Athena Fusion Pilot Plant

Fusion energy promises a reliable, carbon-free source of power; however, significant challenges remain before it can be deployed as an economical energy source. In addition to achieving fusion conditions, power plants must operate under extreme temperatures, radiation, and mechanical loads while maintaining high efficiency and availability. These requirements place strong demands on engineering design and plant operation. This work focuses on the engineering challenges associated with balance of plant analysis for inertial fusion energy systems. In particular, this paper examines the design considerations for primary heat transfer systems in fusion pilot plants employing molten fluoride salt coolants, with particular emphasis on system layout optimization and the balance between competing design objectives using the Xcimer Energy Athena inertial pilot plant design as a case study. Through systematic analysis of candidate system configurations and parametric sensitivity studies, we identify key engineering trade-offs governing salt inventory, pumping power requirements, and operational flexibility. The analysis employs system-level modeling tools to explore the design space and establish relationships between geometric parameters and system performance metrics.

Greenwood, Scott [ORNL] (ORCID:0000000333480736)↗
DOE OSTI2017

Apparatus for performing oil field laser operations

A system, apparatus and methods for delivering high power laser energy to perform laser operations in oil fields and to form a borehole deep into the earth using laser energy. A laser downhole assembly for the delivery of high power laser energy to surfaces and areas in a borehole, which assembly may have laser optics and a fluid path.

04 OIL SHALES AND TAR SANDS↗
NASA NTRS1990

Nuclear power technology requirements for NASA exploration missions

It is pointed out that future exploration of the moon and Mars will mandate developments in many areas of technology. In particular, major advances will be required in planet surface power systems. Critical nuclear technology challenges that can enable strategic self-sufficiency, acceptable operational costs, and cost-effective space transportation goals for NASA exploration missions have been identified. Critical technologies for surface power systems include stationary and mobile nuclear reactor and radioisotope heat sources coupled to static and dynamic power conversion devices. These technologies can provide dramatic reductions in mass, leading to operational and transportation cost savings. Critical technologies for space transportation systems include nuclear thermal rocket and nuclear electric propulsion options, which present compelling concepts for significantly reducing mass, cost, or travel time required for Earth-Mars transport.

Bloomfield, Harvey S.↗
NASA NTRS2017

The Challenge Posed by Geomagnetic Activity to Electric Power Reliability: Evidence from England and Wales

This paper addresses whether geomagnetic activity challenged the reliability of the electric power system during part of the declining phase of solar cycle 23. Operations by National Grid in England and Wales are examined over the period of 11 March 2003 through 31 March 2005. This paper examines the relationship between measures of geomagnetic activity and a metric of challenged electric power reliability known as the net imbalance volume (NIV). Measured in megawatt hours, NIV represents the sum of all energy deployments initiated by the system operator to balance the electric power system. The relationship between geomagnetic activity and NIV is assessed using a multivariate econometric model. The model was estimated using half-hour settlement data over the period of 11 March 2003 through 31 December 2004. The results indicate that geomagnetic activity had a demonstrable effect on NIV over the sample period. Based on the parameter estimates, out-of-sample predictions of NIV were generated for each half hour over the period of 1 January to 31 March 2005. Consistent with the existence of a causal relationship between geomagnetic activity and the electricity market imbalance, the root-mean-square error of the out-of-sample predictions of NIV is smaller; that is, the predictions are more accurate, when the statistically significant estimated effects of geomagnetic activity are included as drivers in the predictions.

Forbes, Kevin F.↗
DOE OSTI2016

An introduction to optimal power flow: Theory, formulation, and examples

The set of optimization problems in electric power systems engineering known collectively as Optimal Power Flow (OPF) is one of the most practically important and well-researched subfields of constrained nonlinear optimization. OPF has enjoyed a rich history of research, innovation, and publication since its debut five decades ago. Nevertheless, entry into OPF research is a daunting task for the uninitiated--both due to the sheer volume of literature and because OPF's ubiquity within the electric power systems community has led authors to assume a great deal of prior knowledge that readers unfamiliar with electric power systems may not possess. This article provides an introduction to OPF from an operations research perspective; it describes a complete and concise basis of knowledge for beginning OPF research. The discussion is tailored for the operations researcher who has experience with nonlinear optimization but little knowledge of electrical engineering. Topics covered include power systems modeling, the power flow equations, typical OPF formulations, and common OPF extensions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1976

Operations research investigations of satellite power stations

A systems model reflecting the design concepts of Satellite Power Stations (SPS) was developed. The model is of sufficient scope to include the interrelationships of the following major design parameters: the transportation to and between orbits; assembly of the SPS; and maintenance of the SPS. The systems model is composed of a set of equations that are nonlinear with respect to the system parameters and decision variables. The model determines a figure of merit from which alternative concepts concerning transportation, assembly, and maintenance of satellite power stations are studied. A hybrid optimization model was developed to optimize the system's decision variables. The optimization model consists of a random search procedure and the optimal-steepest descent method. A FORTRAN computer program was developed to enable the user to optimize nonlinear functions using the model. Specifically, the computer program was used to optimize Satellite Power Station system components.

Cole, J. W.↗
NASA NTRS2013

Impact of Total Ionizing Dose Radiation Testing and Long-Term Thermal Cycling on the Operation of CMF20120D Silicon Carbide Power MOSFET

Power systems designed for use in NASA space missions are required to work reliably under harsh conditions including radiation, thermal cycling, and extreme temperature exposures. Silicon carbide devices show great promise for use in future power electronics systems, but information pertaining to performance of the devices in the space environment is very scarce. A silicon carbide N-channel enhancement-mode power MOSFET called the CMF20120 is of interest for use in space environments. Samples of the device were exposed to radiation followed by long-term thermal cycling to address their reliability for use in space applications. The results of the experimental work are presentd and discussed.

thermal cycling tests↗
NASA NTRS1977

Satellite Power System (SPS) microwave subsystem impacts and benefits

The impacts and benefits to society of the microwave subsystem resulting from the developing, construction and operating of a space solar power to earth, electric power delivery system are presented and discussed. The primary benefit (usable energy) is conveyed mainly in the fundamental frequency portion of the RF radiation beam that is intercepted and converted to electric power output. The small fraction of the microwave and other electromagnetic energy that does not end up in the electric utility grid, yields most of the subsystem impacts. The impacts range from harmonics and noise radiated by the transmitting antenna, through potential interference with ionospheric communications and navigation caused by the power beam heating the ionosphere, to the potential large land area requirements for the rectennas and low level microwave radiation around the rectennas. Additional benefits range from a very low level of waste heat liberated and lack of atmospheric emissions including noise while operating to having no residual ionizing radiation from the rectenna when it is deactivated.

Dickinson, R. M.↗
DOE OSTI2019

Monte Carlo fuel burnup analyses of the Accelerator-Driven Subcritical systems

Here, we discuss the Monte Carlo fuel burnup analysis performed for the Argonne National Laboratory (ANL) Accelerator-Driven Subcritical (ADS) conceptual design. The ANL ADS conceptual design was determined to dispose of the 131 tons of Minor Actinides (MA) fuel of the current United States Spent Nuclear Fuel (SNF) inventory. It uses a neutron source from 1 GeV 25MW proton beam with the liquid lead target to drive the subcritical fission assembly. It utilizes the liquid metal slurry fuel concept to load the MAs fuel. The subcritical fission assembly has a neutron multiplication factor of 0.98. The total fission power generated in the system is about 2.67 GW. The system is designed to operate for 35 full power years. Monte Carlo fuel burnup analyses were performed to calculate the amount of MAs consumed by the ANL ADS conceptual design. The MCNP6 computer program was used to simulate the high energy physics of the protons striking the liquid lead target for generating the neutron source. The MCB5 and SERPENT Monte Carlo burnup computer programs were used to simulate the fuel burnup during the ADS operation. In the ANL ADS conceptual configuration, the reactivity loss during the fuel burnup is compensated by adding fresh fuel into the subcritical assembly. In this paper, both batch and continuous fueling modes are examined. The fresh fuel particles are loaded into the slurry fuel carrier at the beginning of each burnup step of the batch-fueling mode and loaded continuously into the slurry fuel carrier during the operation in the continuous fueling mode. Monte Carlo fuel burnup analyses show that one ANL ADS conceptual design can consume about 25.7 tons of MAs fuel during the 35 full power years with the continuous fueling mode. About five units is required to dispose of the 131 tons of MAs

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

A Fast and Scalable Genetic Algorithm-Based Approach for Planning of Microgrids in Distribution Networks

As a result of climate change, extreme weather events are occurring more frequently and with increasing impact. This trend poses a significant challenge for distribution utilities and system operators to ensure that there is uninterrupted power supply to critical loads in their networks; thus, the level of proactive preparation of the distribution system to be able to handle severe impacts of extreme weather events represents the system's resilience. One method that distribution system planners can use to prepare for future extreme events is to plan multiple microgrids which can use local generation as much as possible to supply critical loads. But partitioning an existing distribution system such that multiple feasible islands are planned and which are capable of supporting critical loads is still challenging for distribution systems - first, because of the size of the network graph partitioning problem and, second, because of the difficulty in properly formulating the desired attributes of such islands or microgrids. Therefore, this paper presents a genetic algorithm based approach that facilitates incorporating multiple objectives for grid partitioning by formulating two types of problems - node allocation and edge elimination - and it considers multiple topological and resilience-enhancing objectives. The performance of the proposed genetic algorithm-based approach is numerically evaluated on multiple test systems as well as on a real distribution feeder in Colorado, United States.

genetic algorithm↗
NASA NTRS2011

Power and Propulsion System Design for Near-Earth Object Robotic Exploration

Near-Earth Objects (NEOs) are exciting targets for exploration; they are relatively easy to reach but relatively little is known about them. With solar electric propulsion, a vast number of interesting NEOs can be reached within a few years and with extensive flexibility in launch date. An additional advantage of electric propulsion for these missions is that a spacecraft can be small, enabling a fleet of explorers launched on a single vehicle or as secondary payloads. Commercial, flight-proven Hall thruster systems have great appeal based on their performance and low cost risk, but one issue with these systems is that the power processing units (PPUs) are designed for regulated spacecraft power architectures which are not attractive for small NEO missions. In this study we consider the integrated design of power and propulsion systems that utilize the capabilities of existing PPUs in an unregulated power architecture. Models for solar array and engine performance are combined with low-thrust trajectory analyses to bound spacecraft design parameters for a large class of NEO missions, then detailed array performance models are used to examine the array output voltage and current over a bounded mission set. Operational relationships between the power and electric propulsion systems are discussed, and it is shown that both the SPT-100 and BPT-4000 PPUs can perform missions over a solar range of 0.7 AU to 1.5 AU - encompassing NEOs, Venus, and Mars - within their operable input voltage ranges. A number of design trades to control the array voltage are available, including cell string layout, array offpointing during mission operations, and power draw by the Hall thruster system.

Near Earth Object (NEO)↗
NASA NTRS1999

Hybrid Modeling for Testing Intelligent Software for Lunar-Mars Closed Life Support

Intelligent software is being developed for closed life support systems with biological components, for human exploration of the Moon and Mars. The intelligent software functions include planning/scheduling, reactive discrete control and sequencing, management of continuous control, and fault detection, diagnosis, and management of failures and errors. Four types of modeling information have been essential to system modeling and simulation to develop and test the software and to provide operational model-based what-if analyses: discrete component operational and failure modes; continuous dynamic performance within component modes, modeled qualitatively or quantitatively; configuration of flows and power among components in the system; and operations activities and scenarios. CONFIG, a multi-purpose discrete event simulation tool that integrates all four types of models for use throughout the engineering and operations life cycle, has been used to model components and systems involved in the production and transfer of oxygen and carbon dioxide in a plant-growth chamber and between that chamber and a habitation chamber with physicochemical systems for gas processing.

Malin, Jane T.↗
DOE OSTI2017

Real-Time Cyber-Physical False Data Attack Detection in Smart Grids Using Neural Networks

Attacks on cyber-physical systems have recently increased in frequency, impact, and publicity. In this paper, a cyber-physical false data attack detection mechanism is proposed to protect the operation of power transmission and distribution systems by automatically inferring underlying physical relationships using cross-sensor analytics in order to detect sensor failures, replay attacks, and other data integrity issues in real-time. We investigate a neural network based mechanism acting on voltage and current readings resulting from a wide variety of load conditions on the IEEE 30-bus power system standard and compare its performance with a support vector machine based mechanism. Experiments showed that 99% detection accuracy of replay attacks was achieved using the proposed neural network mechanism. More importantly, we showed that the best approach was to not create physics-based features using what we knew about the system, but rather to use a neural network to automatically learn the laws, and then use the outputs of that to build a classifier to identify whether and where data spoofing occurs. Thus, it is preferable to infer and exploit the physics using a single machine learning solution

Ferragut, Erik M.↗