Transforming Power Systems Through Global Collaboration
This fact sheet provides an annual update on 21st Century Power Partnership activities in each of our partner countries.
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This fact sheet provides an annual update on 21st Century Power Partnership activities in each of our partner countries.
Purpose: To investigate the applicability of feasibility-seeking cyclic orthogonal projections to the field of intensity modulated proton therapy (IMPT) inverse planning. Feasibility of constraints only, as opposed to optimization of a merit function, is less demanding algorithmically and holds a promise of parallel computations capability with non-cyclic orthogonal projections algorithms such as string-averaging or block-iterative strategies. Methods: A virtual 2D geometry was designed containing a C-shaped planning target volume (PTV) surrounding an organ at risk (OAR). The geometry was pixelized into 1 mm pixels. Four beams containing a subset of proton pencil beams were simulated in Geant4 to provide the system matrix A whose elements a-ij correspond to the dose delivered to pixel i by a unit intensity pencil beam j. A cyclic orthogonal projections algorithm was applied with the goal of finding a pencil beam intensity distribution that would meet the following dose requirements: D-OAR < 54 Gy and 57 Gy < D-PTV < 64.2 Gy. The cyclic algorithm was based on the concept of orthogonal projections onto half-spaces according to the Agmon-Motzkin-Schoenberg algorithm, also known as ‘ART for inequalities’. Results: The cyclic orthogonal projections algorithm resulted in less than 5% of the PTV pixels and less than 1% of OAR pixels violating their dose constraints, respectively. Because of the abutting OAR-PTV geometry and the realistic modelling of the pencil beam penumbra, complete satisfaction of the dose objectives was not achieved, although this would be a clinically acceptable plan for a meningioma abutting the brainstem, for example. Conclusion: The cyclic orthogonal projections algorithm was demonstrated to be an effective tool for inverse IMPT planning in the 2D test geometry described. We plan to further develop this linear algorithm to be capable of incorporating dose-volume constraints into the feasibility-seeking algorithm.
Enhancements to the real-time processing and display systems of the NASA Western Aeronautical Test Range are described. Display processing has been moved out of the telemetry and radar acquisition processing systems super-minicomputers into user/client interactive graphic workstations. Real-time data is provided to the workstations by way of Ethernet. Future enhancement plans include use of fiber optic cable to replace the Ethernet.
The goal of this final project report is to comprehensively summarize the work conducted on project DE-FE0026497. In accordance with the Statement of Project Objectives (SOPO), the University of Kentucky Center for Applied Energy Research (UKy-CAER) (Recipient) has developed an advanced, versatile, 10 MWe post-combustion CO 2 capture system (CCS) for a coal-fired power plant, Louisville Gas and Electric Company’s Trimble County Generating Station, using a heat integrated process combined with two-stage stripping and any advanced solvent to enhance the CO 2 absorber performance. The proposed project (Phase 1 and 2) will involve the design, fabrication, installation and testing of a large pilot scale facility that will demonstrate the UKy-CAER innovative carbon capture system integrated with an operating supercritical power plant. Specifically during Phase 1, the Recipient has provided all necessary documentation to support its Phase 2 down-selection including: the Project Narrative, the updated Project Management Plan (PMP), the preliminary engineering design, the Technical and Economic Analysis report (TEA) (including the Case 12 – Major Equipment List and submitted as a Topical Report), a Phase 1 Technology Gap Analysis (TGA), an Environmental Health and Safety (EH&S) Assessment on the 10 MWe unit, and updated Phase 2 cost estimates (including the detailed design, procurement, construction, operation, and decommissioning costs) with a budget justification. Furthermore, the Recipient has proposed a combined modular and freestanding column configuration with an advanced absorber gas/liquid distribution system, an advanced solvent, with the integration of discrete packing, a smart cross-over heat exchanger, and a load and ambient condition following control strategy, all to address ten of 12 technology gaps identified during the Phase I work. If successful, the proposed heat integrated post-combustion CCS will pave the way to achieve the United States Department of Energy National Energy Technology Laboratory (U.S. DOE NETL) CO 2 capture performance and cost target, as indicated in the submitted TEA and summarized in this report.
The presence of a permanent CO2 polar ice cap on Mars has important consequences for the planet's climate system. The heat balance of such a cap, which is determined mainly by atmospheric heat transport, and the downward solar in infrared radiative fluxes, determines its surface temperature, which through the vapor pressure relation sets the mean annual surface pressure. On Mars today, for example, the south residual CO2 cap is present year-round with a mean annual temperature of approximately 145 K which corresponds to a mean annual CO2 vapor pressure of approximately 600 Pa. On early Mars, permanent polar caps are also possible especially since the sun was less luminous 3.5-4.0 Gya. Thus, the existence of permanent polar caps on early Mars is central to understanding the nature of the planets climate system in those ancient times and whether or not the atmosphere might have been capable of sustaining conditions suitable for liquid water flowing over the surface as is indicated in the geological record. Forget et al [1] showed that for present orbital properties atmospheric collapse into permanent polar caps could only be prevented for surface pressures roughly between 500 - 3000 hPa. Though follow-on studies confirm and extend the Forget et al. results [2], the full sensitivity of this "window" of stability has not been explored. There are many factors to consider such the albedo of the caps, dust content of the atmosphere, and the presence of water ice clouds. However, we begin our exploration of the stability of the early Martian atmosphere by focusing on the role of CO2 ice clouds. In some preliminary simulations with the Ames Mars General Circulation Model (GCM) we found that atmospheric collapse depends on assumptions regarding the fate of CO2 ice clouds. If, for example, we assume the clouds immediately fall to the surface, then in some cases collapse is favored. On the other hand if the clouds are allowed to fall and evaporate, collapse can be averted. This implies that CO2 ice cloud microphysics is important to the overall stability of the atmosphere. Though the Ames GCM has a sophisticated CO2 cloud microphysics package that includes nucleation, growth, and sedimentation (see accompanying poster by Kahre et al. [3]), we have implemented a simpler scheme based on the Forget et al. [1] approach to CO2 ice clouds. Our goal is to reproduce and expand their study. The key parameter in this approach is the concentration and vertical distribution of cloud condensation nuclei (CCN), i.e., dust particles. Fewer CCN lead to larger particles which fall faster, while higher CCN concentrations lead to smaller particles and thicker clouds that remain suspended for longer periods of time. We plan to explore the stability of the atmosphere to CCN concentrations and distributions and then assess the capability of thick early atmospheres to loft and distribute dust particles (CCN) around the planet. Thus, our work will shed light on the nature of the coupling between the dust and CO2 cycles and the implications it has for the early Mars climate system.
Background: According to the World Health Organization, malaria surveillance is weakest in countries and regions with the highest malaria burden. A core obstacle is that the data required to perform malaria surveillance are fragmented in multiple data silos distributed across geographic regions. Furthermore, consistent integrated malaria data sources are few, and a low degree of interoperability exists between them. As a result, it is difficult to identify disease trends and to plan for effective interventions. Objective: We propose the Semantics, Interoperability, and Evolution for Malaria Analytics (SIEMA) platform for use in malaria surveillance based on semantic data federation. Using this approach, it is possible to access distributed data, extend and preserve interoperability between multiple dynamic distributed malaria sources, and facilitate detection of system changes that can interrupt mission-critical global surveillance activities. Methods: We used Semantic Automated Discovery and Integration (SADI) Semantic Web Services to enable data access and improve interoperability, and the graphical user interface-enabled semantic query engine HYDRA to implement the target queries typical of malaria programs. We implemented a custom algorithm to detect changes to community-developed terminologies, data sources, and services that are core to SIEMA. This algorithm reports to a dashboard. Valet SADI is used to mitigate the impact of changes by rebuilding affected services. Results: We developed a prototype surveillance and change management platform from a combination of third-party tools, community-developed terminologies, and custom algorithms. We illustrated a methodology and core infrastructure to facilitate interoperable access to distributed data sources using SADI Semantic Web services. This degree of access makes it possible to implement complex queries needed by our user community with minimal technical skill. We implemented a dashboard that reports on terminology changes that can render the services inactive, jeopardizing system interoperability. Using this information, end users can control and reactively rebuild services to preserve interoperability and minimize service downtime. Conclusions: We introduce a framework suitable for use in malaria surveillance that supports the creation of flexible surveillance queries across distributed data resources. The platform provides interoperable access to target data sources, is domain agnostic, and with updates to core terminological resources is readily transferable to other surveillance activities. A dashboard enables users to review changes to the infrastructure and invoke system updates. The platform significantly extends the range of functionalities offered by malaria information systems, beyond the state-of-the-art.
The results are described of a study on four pieces of flight hardware from the Saturn 1U and S-4B stages to determine whether the objectives of the formal qualification tests on that hardware could have been obtained within that program by methods other than performing the qualification tests. These methods include qualification by analyses, similarity and integrated testing, i.e., distribution of the objectives among the other tests in the program. It was found that it is feasible to delete the requirements for formal qualification testing provided that it is accomplished early in the program to allow adequate planning for accomplishing the qualification objectives by other means. Additionally, a scorekeeping system was defined that is simple, straightforward, easy to implement. This scorekeeping system provides complete visibility of equivalent qualification status at any point during the program. A set of groundrules for implementing this study was established as a result of findings on the specific items of hardware studied.
An environmentally oriented microwave technology exploratory research program aimed at reducing the uncertainty associated with microwave power system critical technical issues is described. Topics discussed include: (1) Solar Power Satellite System (SPS) development plan elements; (2) critical technology issues related to the SPS preliminary reference configuration; (3) pilot plant to demonstrate commercial viability of the SPS system; and (4) research areas required to demonstrate feasibility of the SPS system. Progress in the development of advanced GaAs solar cells is reported along with a power distribution subsystem.
One of the major concerns of any maintenance organization is to understand and estimate the cost of maintenance releases of software systems. Planning the next release so as to maximize the increase in functionality and the improvement in quality are vital to successful maintenance management. The objective of this paper is to present the results of a case study in which an incremental approach was used to better understand the effort distribution of releases and build a predictive effort model for software maintenance releases. This study was conducted in the Flight Dynamics Division (FDD) of NASA Goddard Space Flight Center(GSFC). This paper presents three main results: 1) a predictive effort model developed for the FDD's software maintenance release process; 2) measurement-based lessons learned about the maintenance process in the FDD; and 3) a set of lessons learned about the establishment of a measurement-based software maintenance improvement program. In addition, this study provides insights and guidelines for obtaining similar results in other maintenance organizations.
Submillimeter-wave cloud ice radiometry is a new and innovative technique for characterizing cirrus ice clouds. Cirrus clouds affect Earth's climate and hydrological cycle by reflecting incoming solar energy, trapping outgoing IR radiation, sublimating into vapor, and influencing atmospheric circulation. Since uncertainties in the global distribution of cloud ice restrict the accuracy of both climate and weather models, successful development of this technique could provide a valuable tool for investigating how clouds affect climate and weather. Cloud ice radiometry could fill an important gap in the observational capabilities of existing and planned Earth-observing systems. Using submillimeter-wave radiometry to retrieve properties of ice clouds can be understood with a simple model. There are a number of submillimeter-wavelength spectral regions where the upper troposphere is transparent. At lower tropospheric altitudes water vapor emits a relatively uniform flux of thermal radiation. When cirrus clouds are present, they scatter a portion of the upwelling flux of submillimeter-wavelength radiation back towards the Earth as shown in the diagram, thus reducing the upward flux o f energy. Hence, the power received by a down-looking radiometer decreases when a cirrus cloud passes through the field of view causing the cirrus cloud to appear radiatively cool against the warm lower atmospheric thermal emissions. The reduction in upwelling thermal flux is a function of both the total cloud ice content and mean crystal size. Radiometric measurements made at multiple widely spaced frequencies permit flux variations caused by changes in crystal size to be distinguished from changes in ice content, and polarized measurements can be used to constrain mean crystal shape. The goal of the cloud ice radiometry program is to further develop and validate this technique of characterizing cirrus. A multi-frequency radiometer is being designed to support airborne science and spacecraft validation missions. This program has already extended the initial millimeter-wave modeling studies to submillimeter-wavelengths and has improved the realism of the cloud scattering models. Additionally a proof-of-concept airborne submillimeter-wave radiometer was constructed and fielded. It measured a radiometric signal from cirrus confirming the basic technical feasibility of this technique. This program is a cooperative effort of the University of Colorado, Colorado State University, Swales Aerospace, and Jet Propulsion Laboratory. Additional information is contained in the original.
One of the strategic goals of the U.S. National Aeronautics and Space Administration (NASA) is to "Develop a balanced overall program of science, exploration, and aeronautics consistent with the redirection of the human spaceflight program to focus on exploration". An important sub-goal of this goal is to "Study Earth from space to advance scientific understanding and meet societal needs." NASA meets this subgoal in partnership with other U.S. agencies and international organizations through its Earth science program. A major component of NASA s Earth science program is the Earth Observing System (EOS). The EOS program was started in 1990 with the primary purpose of modeling global climate change. This program consists of a set of space-borne instruments, science teams, and a data system. The instruments are designed to obtain highly accurate, frequent and global measurements of geophysical properties of land, oceans and atmosphere. The science teams are responsible for designing the instruments as well as scientific algorithms to derive information from the instrument measurements. The data system, called the EOS Data and Information System (EOSDIS), produces data products using those algorithms as well as archives and distributes such products. The first of the EOS instruments were launched in November 1997 on the Japanese satellite called the Tropical Rainfall Measuring Mission (TRMM) and the last, on the U.S. satellite Aura, were launched in July 2004. The instrument science teams have been active since the inception of the program in 1990 and have participation from Brazil, Canada, France, Japan, Netherlands, United Kingdom and U.S. The development of EOSDIS was initiated in 1990, and this data system has been serving the user community since 1994. The purpose of this chapter is to discuss the history and evolution of EOSDIS since its beginnings to the present and indicate how it continues to evolve into the future. this chapter is organized as follows. Sect. 7.2 provides a discussion of EOSDIS, its elements and their functions. Sect. 7.3 provides details regarding the move towards more distributed systems for supporting both the core and community needs to be served by NASA Earth science data systems. Sect. 7.4 discusses the use of standards and interfaces and their importance in EOSDIS. Sect. 7.5 provides details about the EOSDIS Evolution Study. Sect. 7.6 presents the implementation of the EOSDIS Evolution plan. Sect. 7.7 briefly outlines the progress that the implementation has made towards the 2015 Vision, followed by a summary in Sect. 7.8.
DebriSat is a planned laboratory ]based satellite hypervelocity impact experiment. The goal of the project is to characterize the orbital debris that would be generated by a hypervelocity collision involving a modern satellite in low Earth orbit (LEO). The DebriSat project will update and expand upon the information obtained in the 1992 Satellite Orbital Debris Characterization Impact Test (SOCIT), which characterized the breakup of a 1960 's US Navy Transit satellite. There are three phases to this project: the design and fabrication of an engineering model representing a modern, 50-cm/50-kg class LEO satellite known as DebriSat; conduction of a laboratory-based hypervelocity impact to catastrophically break up the satellite; and characterization of the properties of breakup fragments down to 2 mm in size. The data obtained, including fragment size, area ]to ]mass ratio, density, shape, material composition, optical properties, and radar cross ]section distributions, will be used to supplement the DoD fs and NASA fs satellite breakup models to better describe the breakup outcome of a modern satellite. Updated breakup models will improve mission planning, environmental models, and event response. The DebriSat project is sponsored by the Air Force fs Space and Missile Systems Center and the NASA Orbital Debris Program Office. The design and fabrication of DebriSat is led by University of Florida with subject matter experts f support from The Aerospace Corporation. The major milestones of the project include the complete fabrication of DebriSat by September 2013, the hypervelocity impact of DebriSat at the Air Force fs Arnold Engineering Development Complex in early 2014, and fragment characterization and data analyses in late 2014.
The common theme of this dissertation is sampling-based motion planning with the two key contributions being in the area of replanning and spatial load balancing for robotic systems. Here, we begin by recalling two sampling-based motion planners: the asymptotically optimal rapidly-exploring random tree (RRT*), and the asymptotically optimal probabilistic roadmap (PRM*). We also provide a brief background on collision cones and the Distributed Reactive Collision Avoidance (DRCA) algorithm. The next four chapters detail novel contributions for motion replanning in environments with unexpected static obstacles, for multi-agent collision avoidance, and spatial load balancing. First, we show improved performance of the RRT* when using the proposed Grandparent-Connection (GP) or Focused-Refinement (FR) algorithms. Next, the Goal Tree algorithm for replanning with unexpected static obstacles is detailed and proven to be asymptotically optimal. A multi-agent collision avoidance problem in obstacle environments is approached via the RRT*, leading to the novel Sampling-Based Collision Avoidance (SBCA) algorithm. The SBCA algorithm is proven to guarantee collision free trajectories for all of the agents, even when subject to uncertainties in the knowledge of the other agents’ positions and velocities. Given that a solution exists, we prove that livelocks and deadlock will lead to the cost to the goal being decreased. We introduce a new deconfliction maneuver that decreases the cost-to-come at each step. This new maneuver removes the possibility of livelocks and allows a result to be formed that proves convergence to the goal configurations. Finally, we present a limited range Graph-based Spatial Load Balancing (GSLB) algorithm which fairly divides a non-convex space among multiple agents that are subject to differential constraints and have a limited travel distance. The GSLB is proven to converge to a solution when maximizing the area covered by the agents. The analysis for each of the above mentioned algorithms is confirmed in simulations.
A generalized approach is proposed to support integrated traffic flow management decision making studies at both the U.S. national and regional levels. It can consider tradeoffs between alternative optimization and heuristic based models, strategic versus tactical flight controls, and system versus fleet preferences. Preliminary testing was accomplished by implementing thirteen unique traffic flow management models, which included all of the key components of the system and conducting 85, six-hour fast-time simulation experiments. These experiments considered variations in the strategic planning look-ahead times, the replanning intervals, and the types of traffic flow management control strategies. Initial testing indicates that longer strategic planning look-ahead times and re-planning intervals result in steadily decreasing levels of sector congestion for a fixed delay level. This applies when accurate estimates of the air traffic demand, airport capacities and airspace capacities are available. In general, the distribution of the delays amongst the users was found to be most equitable when scheduling flights using a heuristic scheduling algorithm, such as ration-by-distance. On the other hand, equity was the worst when using scheduling algorithms that took into account the number of seats aboard each flight. Though the scheduling algorithms were effective at alleviating sector congestion, the tactical rerouting algorithm was the primary control for avoiding en route weather hazards. Finally, the modeled levels of sector congestion, the number of weather incursions, and the total system delays, were found to be in fair agreement with the values that were operationally observed on both good and bad weather days.
Multiple recent studies highlight significant benefits associated with expansion of interregional transfer capabilities for efficiently adapting to these changes. Despite these proposed benefits, few, if any, interregional transmission projects have been built in recent memory . The objective of this report is to confront the barriers to interregional transmission that exist today and address them with potential reforms and collaborative solutions. This report identifies solutions with the potential for immediate beneficial impact on interregional transmission with the ultimate goal of allowing more effective identification and advancement of interregional transmission projects that create the most positive net value to the participating systems . It distinguishes between states, federal government, and planning regions as key actors in implementing solutions designed to be flexible to accommodate regional differences.
Misforecasting the adoption of customer-owned distributed photovoltaics (DPV) can have operational and financial implications for utilities - forecasting capabilities can be improved, but generally at a cost.This paper informs this decision-space by quantifying the costs of misforecasting across a wide range of DPV growth rates and misforecast severities. Using a simplified probabilistic method presented within, an analyst can make a first-order estimate of the financial benefit of improving a utility's forecasting capabilities, and thus be better informed about whether to make such an investment. For example, we show that a utility with 10 TWh per year of retail electric sales who initially estimates that the increase in DPV's contribution to total generation could range from 2 percent to 7.5 percent over the next 15 years could expect total present-value savings of approximately 4 million if they could keep the severity of successive five-year misforecasts within +/- 25 percent. We also have more general discussions about how misforecasting DPV impacts the buildout and operation of the bulk power system - for example, we observed that misforecasting DPV most strongly influenced the amount of utility-scale PV that gets built, due to the similarity in the energy and capacity services offered by the two solar technologies.
The City of Los Angeles has set ambitious goals to transform its electricity supply, aiming to achieve a 100% renewable energy power system by 2045, along with aggressive electrification targets for buildings and vehicles. To reach these goals, and assess the implications for jobs, electricity rates, the environment, and environmental justice, the Los Angeles City Council passed a series of motions directing the Los Angeles Department of Water and Power (LADWP) to determine the technical feasibility and investment pathways of a 100% renewable energy portfolio standard. The Los Angeles 100% Renewable Energy Study (LA100) is a first-of-its-kind objective, rigorous, and science-based power systems analysis to determine what investments could be made to achieve these goals. The LA100 final report is presented as a collection of 12 chapters and an executive summary, each of which is available as an individual download. This chapter summarizes the growth in distribution-connected energy resources and provides a detailed review of impacts to the distribution grid of growth in customer electricity demand, solar, and storage, as well as required distribution grid upgrades and associated costs.
The National Renewable Energy Laboratory (NREL) in collaboration with Massachusetts Institute of Technology (MIT), Universidad Pontificia Comillas (Comillas-IIT, Spain) and GE Grid Solutions, is working on an ARPA-E GRID DATA project, titled Smart-DS, to create: 1) High-quality, realistic, synthetic distribution network models, and 2) Advanced tools for automated scenario generation based on high-resolution weather data and generation growth projections. Through these advancements, the Smart-DS project is envisioned to accelerate the development, testing, and adoption of advanced algorithms, approaches, and technologies for sustainable and resilient electric power systems, especially in the realm of U.S. distribution systems. This talk will present the goals and overall approach of the Smart-DS project, including the process of creating the synthetic distribution datasets using reference network model (RNM) and the comprehensive validation process to ensure network realism, feasibility, and applicability to advanced use cases. The talk will provide demonstrations of early versions of synthetic models, along with the lessons learnt from expert engagements to enhance future iterations. Finally, the scenario generation framework, its development plans, and co-ordination with GRID DATA repository teams to house these datasets for public access will also be discussed.