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DOE OSTI2024

Carbon Management Projects (CONNECT) Database and Explorer

Overview The Carbon Management Projects (CONNECT) Toolkit is an online exploratory visualization tool developed by the U.S. Department of Energy's (DOE) Office of Fossil Energy and Carbon Management (FECM) with support from other federal agencies such as the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Transportation (DOT). It provides a single point of access to authoritative information on federal agency investment in a portfolio of research, development, and demonstration (RD&D) projects that have been publicly announced to advance technologies for point source carbon capture, carbon dioxide removal, transport, storage, and conversion, collectively referred to as carbon management. The RD&D programs covered in this tool are authorized by annual congressional appropriations ("Base Program") and the 2021 Infrastructure Investment and Jobs Act (IIJA). The tool also incorporates public information on other federal initiatives, such as the Regional Clean Hydrogen Hubs, and public information released by other government agencies, such as the Environmental Protection Agency's (EPA) and Primacy States’ Underground Injection Control Class VI permits and EPA’s facility level greenhouse gas (GHG) emissions. Developed in a geographic information system, the tool organizes carbon management projects into five groups based on the primary technology that a project aims to advance, each visually represented as a digital layer ("carbon management project layer"). Only federally funded projects are included, which can be awarded projects that are completed or ongoing, or projects that have been selected but are currently under negotiation. Project information can be viewed in the map or in the attribute table below it when turned on. In the map view, each project is displayed at either its host site (for field work), where available, or its performer site (project lead's location, further explained in the table below). Host sites and performer sites are represented in distinct icons. Several reference layers offer additional public information on infrastructural and natural resource environment for carbon management. These reference layers, combined with multiple geographical basemaps, enable users to visualize the carbon management project layers in context. Carbon management project information will be updated monthly based on feedback and information availability. Carbon management project layers Point Source Carbon Capture (PSC) This layer contains DOE-funded projects focused on capturing carbon dioxide (CO2) from power plants or industrial facilities. Carbon Dioxide Removal (CDR) This layer contains DOE-funded projects focused on capturing CO2 from the atmosphere, including direct air capture (DAC) and DAC hubs, direct ocean capture, enhanced mineralization, and biomass carbon removal and storage. For projects with multiple host sites, each of the sites are displayed individually with the project cost and cost sharing information representing the total for the entire project. Carbon Transport This layer contains DOE- and DOT-funded projects focused on CO2 transport. The Transport Research and Development sublayer contains projects that do not involve physical infrastructure; the Proposed Transport Corridor sublayer contains projects for which either a route for the transport infrastructure has been proposed or a general area for the transport infrastructure has been identified. Carbon Storage This layer contains DOE-funded key projects focused on CO2 storage. For projects with multiple field-work sites, each of the sites are displayed individually on the map with the project cost and cost sharing information representing the overall total for the entire project. Carbon Conversion This layer contains DOE-funded projects focused on converting CO2 into economically valuable products. Reference layers The following layers provide additional information in the geographic proximity of carbon management projects. Users should reference the original sources for more details (weblinks provided below and in pop-up windows on the map). Regional Clean Hydrogen Hub and Facility These layers illustrate the approximate areas of the Regional Clean Hydrogen Hubs announced by DOE's Office of Clean Energy Demonstrations (OCED) and the approximate locations of individual facilities that constitute the hubs (see "Where are the H2Hubs located?" on the webpage linked above). EPA Facility Level GHG Emissions (direct emitter) This layer shows direct CO2 emissions from stationary sources in 2022, using data extracted from EPA's Facility Level Information on GreenHouse gases Tool (FLIGHT). Captured and injected CO2 are not deducted from direct emitters’ total emissions. Contact EPA for additional details. Underground Injection Control Class VI permit/permit application This layer shows the locations of CO2 injection wells that are granted or in the process of applying for an Underground Injection Control Class VI permit by EPA or a Primacy State (currently Louisiana, North Dakota, and Wyoming). The URLs for the permits or permit applications are provided in the pop-up windows associated with the well locations. Contact EPA for additional details. Carbon Storage Resource This layer contains information on prospective CO2 storage resources in saline formations and oil and gas reservoirs provided by the National Carbon Sequestration Database and Geographic Information System (NATCARB) spatial database. Contact NETL for additional details. Existing CO2 pipeline This layer shows active CO2 pipelines based on information digitized from the map issued by the Pipeline and Hazardous Materials Safety Administration (PHMSA). Contact PHMSA for additional details.

Carbon Conversion↗
NASA NTRS2004

Improving Project Management with Simulation and Completion Distribution Functions

Despite the critical importance of project completion timeliness, management practices in place today remain inadequate for addressing the persistent problem of project completion tardiness. A major culprit in late projects is uncertainty, which most, if not all, projects are inherently subject to. This uncertainty resides in the estimates for activity durations, the occurrence of unplanned and unforeseen events, and the availability of critical resources. In response to this problem, this research developed a comprehensive simulation based methodology for conducting quantitative project completion time risk analysis. It is called the Project Assessment by Simulation Technique (PAST). This new tool enables project stakeholders to visualize uncertainty or risk, i.e. the likelihood of their project completing late and the magnitude of the lateness, by providing them with a completion time distribution function of their projects. Discrete event simulation is used within PAST to determine the completion distribution function for the project of interest. The simulation is populated with both deterministic and stochastic elements. The deterministic inputs include planned project activities, precedence requirements, and resource requirements. The stochastic inputs include activity duration growth distributions, probabilities for events that can impact the project, and other dynamic constraints that may be placed upon project activities and milestones. These stochastic inputs are based upon past data from similar projects. The time for an entity to complete the simulation network, subject to both the deterministic and stochastic factors, represents the time to complete the project. Repeating the simulation hundreds or thousands of times allows one to create the project completion distribution function. The Project Assessment by Simulation Technique was demonstrated to be effective for the on-going NASA project to assemble the International Space Station. Approximately $500 million per month is being spent on this project, which is scheduled to complete by 2010. NASA project stakeholders participated in determining and managing completion distribution functions produced from PAST. The first result was that project stakeholders improved project completion risk awareness. Secondly, using PAST, mitigation options were analyzed to improve project completion performance and reduce total project cost.

Cates, Grant R.↗
NASA NTRS2011

Project Management Using Modern Guidance, Navigation and Control Theory

Implementing guidance, navigation, and control (GN&C) theory principles and applying them to the human element of project management and control is not a new concept. As both the literature on the subject and the real-world applications are neither readily available nor comprehensive with regard to how such principles might be applied, this paper has been written to educate the project manager on the "laws of physics" of his or her project (not to teach a GN&C engineer how to become a project manager) and to provide an intuitive, mathematical explanation as to the control and behavior of projects. This paper will also address how the fundamental principles of modern GN&C were applied to the National Aeronautics and Space Administration's (NASA) Constellation Program (CxP) space suit project, ensuring the project was managed within cost, schedule, and budget. A project that is akin to a physical system can be modeled and managed using the same over arching principles of GN&C that would be used if that project were a complex vehicle, a complex system(s), or complex software with time-varying processes (at times nonlinear) containing multiple data inputs of varying accuracy and a range of operating points. The classic GN&C theory approach could thus be applied to small, well-defined projects; yet when working with larger, multiyear projects necessitating multiple organizational structures, numerous external influences, and a multitude of diverse resources, modern GN&C principles are required to model and manage the project. The fundamental principles of a GN&C system incorporate these basic concepts: State, Behavior, Feedback Control, Navigation, Guidance and Planning Logic systems. The State of a system defines the aspects of the system that can change over time; e.g., position, velocity, acceleration, coordinate-based attitude, and temperature, etc. The Behavior of the system focuses more on what changes are possible within the system; this is denoted in the state of the system. The behavior of a system, as captured in the system modeling, when properly done will aid in accurately predicting future system performance. The Feedback Control system understands the state and behavior of the system and uses feedback to adjust control inputs into the system. The feedback, which is the right arm of the Control system, allows change to be affected in the overall system; it therefore is important to not only correctly identify the system feedback inputs, but also the system response to the feedback inputs. The Navigation system takes multiple data inputs and based on a priori knowledge of the inputs, develops a statistically based weighting of the inputs and measurements to determine the system's state. Guidance and Planning Logic of the system, complete with an understanding of where the system is (provided by the Navigation system), will in turn determine where the system needs to be and how to get it there. With any system/project, it is critical that the objective of the system/project be clearly defined -- not only to plan but to measure performance and to aid in guiding the system or the project. The system principles discussed above, which can be and have been applied to the current CxP space suit development project, can also be mapped to real-world constituents, thus allowing project managers to apply systems theories that are well defined in engineering and mathematics to a discipline (i.e., Project Management) that historically has been based in personal experience and intuition. This mapping of GN&C theory to Project Management will, in turn, permit a direct, methodical approach to Project Management, planning and control providing a tool to help predict (and guide) performance and an understanding of the project constraints, how the project can be controlled, and the impacts to external influences and inputs. This approach, to a project manager, flows down to the three bottom-line variables of cost, schedule, and scope ando the needed control of these three variables to successfully perform and complete a project.

Hill, Terry R.↗
NASA NTRS2008

The Project Manager Who Saved His Country

George Meade defeated Robert E. Lee, one of the greatest military leaders of all time. How did he do it? By using the skills he had learned as a project manager and outperforming Lee in all aspects of project management. Most project managers are familiar with the Project Management Institute's "Guide to the Project Management Body of Knowledge" (PMBOK), which identifies the skills and knowledge crucial to successful project management. Project managers need to make sure that all the elements of a project work together. They must develop and execute plans and coordinate changes to those plans. A project manager must define the scope of the work, break it into manageable pieces, verify and control what work is being done, and make sure that the work being done is essential to the project. Every project manager knows the challenges of schedule and the value of schedule slack. Project managers must get the resources they need and use them effectively. Project managers get the people they need and use their talents to achieve mission success. Projects generate huge amounts of information. A key to project success is getting sufficient and accurate information to the people who need it when they need it. Project managers must identify and quantify the risks that jeopardize project success and make plans for dealing with them. Studying Meade and Lee's performances at Gettysburg can help modern project managers appreciate, develop, and use the skills they need to be good project managers. The circumstances may be different, but the basic principles are the same. This dramatic event in American history shows how the skills of project management can be used in almost any situation. Former project manager George Meade used those skills to change the tide of the Civil War.

Baniszewski, John↗
DOE OSTI2018

Utility-Scale Solar: Empirical Trends in Project Technology, Cost, Performance, and PPA Pricing in the United States – 2018 Edition

The utility-scale solar sector has led the overall U.S. solar market in terms of installed capacity since 2012. In 2017, the utility-scale sector accounted for nearly 60% of all new solar capacity, and is expected to maintain its market-leading position for at least another six years. Two-thirds of all states, representing all regions of the country, are now home to one or more utility-scale solar projects. This report—the sixth in an ongoing annual series—provides in-depth data-driven analysis of the utility-scale solar project fleet in the United States. Drawing on empirical project-level data from a wide range of sources, this report analyzes technology trends, installed project prices, operating costs, capacity factors, power purchase agreement ("PPA") prices, the levelized cost of solar energy (LCOE), and the market value of solar. Given its current preeminence in the market, utility-scale PV also dominates much of this report, though data from CPV and CSP projects are also presented where appropriate. Highlights from this year's edition include: -Installation and Technology Trends: The use of solar trackers dominated 2017 installations with nearly 80% of all new capacity. In a reflection of the ongoing geographic expansion of the market beyond California and the high-insolation Southwest, the median insolation level at newly built project sites declined again in 2017. While new fixed-tilt projects are now seen predominantly in less-sunny regions, tracking projects are increasingly pushing into these same regions. The median inverter loading ratio grew to 1.32 in 2017, allowing the inverters to operate closer to full capacity for a greater percentage of the day. -Installed Prices: Median installed PV project prices have steadily fallen by two-thirds since the 2007-2009 period, to $2.0/WAC (or $1.6/WDC) for projects completed in 2017. The lowest 20th percentile of projects within our 2017 sample were priced at or below $1.8/WAC, with the lowest-priced projects around $0.9/WAC. Overall price dispersion across the entire sample has decreased steadily every year since 2013; similarly, price variation across regions decreased in 2017. -Operation and Maintenance ("O&M") Costs: PV O&M costs were in the neighborhood of $16/kWAC-year, or $8/MWh, in 2017. These numbers include only those costs incurred to directly operate and maintain the generating plant. -Capacity Factors: The cumulative net AC capacity factors of individual projects vary widely, from 14.3% to 35.2%, with a sample median of 26.3%. This project-level variation is based on a number of factors, including the strength of the solar resource at the project site, whether the array is mounted at a fixed tilt or on a tracking mechanism, the inverter loading ratio, degradation, and curtailment. Changes in at least the first three of these factors drove mean capacity factors higher from 2010-vintage to 2013-vintage projects, where they've remained fairly steady among more-recent project vintages as an ongoing increase in the prevalence of tracking has been offset by a build-out of lower resource sites. -PPA Prices and LCOE: Driven by lower installed project prices and improving capacity factors, levelized PPA prices for utility-scale PV have fallen dramatically over time, by $20-$30/MWh per year on average from 2006 through 2012, with a smaller price decline of ~$10/MWh per year evident from 2013 through 2016. Most recent PPAs in our sample—including many outside of California and the Southwest—are priced at or below $40/MWh levelized (in real 2017 dollars), with a few priced as aggressively as ~$20/MWh. The median LCOE among operational PV projects in our sample has followed PPA prices lower, suggesting a relatively competitive market for PPAs. -Solar's Wholesale Energy Market Value: Falling PPA prices have been offset to some degree by a decline in the wholesale energy market value of solar within higher-penetration markets like California, where solar earned just 79% of the average price across all hours within CAISO's real-time wholesale energy market in 2017 (down from 125% back in 2012). In other markets with less solar penetration, however, solar's hourly generation profile still earns more than the average wholesale price (e.g., 127% in ERCOT, 112% in PJM). -Solar+Storage: Adding battery storage is one way to at least partially restore the value of solar, and three recent PV+storage PPAs in Nevada (each using 4-hour batteries sized at 25% of PV nameplate capacity) suggest that the incremental PPA price adder for storage has fallen to ~$5/MWh, down from ~$15/MWh just a year ago for a similarly configured project. As PV plus battery storage becomes more cost-effective, a number of developers are regularly offering it as a viable upgrade to standalone PV. At the end of 2017, there were at least 188.5 GW of utility-scale solar power capacity within the interconnection queues across the nation. The 2017 growth within these queues is widely distributed across all regions of the country, but is most pronounced in the up-and-coming Midwest region, which accounts for 27% of the 99.2 GW of new queue capacity. The widening geographic distribution is as clear of a sign as any that the utility-scale market is maturing and expanding outside of its traditional high-insolation comfort zones.

14 SOLAR ENERGY↗
DOE OSTI2017

Utility-Scale Solar 2016: An Empirical Analysis of Project Cost, Performance, and Pricing Trends in the United States

The utility-scale solar sector has led the overall U.S. solar market in terms of installed capacity since 2012. In 2016, the utility-scale sector installed more than 2.5 times as much new capacity as did the residential and commercial sectors combined, and is expected to maintain its dominant position for at least another five years. This report—the fifth edition in an ongoing annual series—provides data-driven analysis of the utility-scale solar project fleet in the United States. We analyze not just installed project prices, but also operating costs, capacity factors, and power purchase agreement ("PPA") prices from a large sample of utility-scale PV and CSP projects throughout the United States. Highlights from this year's edition include the following: Installation Trends: The use of solar tracking devices dominated 2016 installations, at nearly 80% of all new capacity. In a reflection of the ongoing geographic expansion of the market beyond California and the Southwest, the median long-term average insolation level at newly built project sites declined again in 2016. While new fixed-tilt projects are now seen predominantly in less-sunny regions, tracking projects are increasingly pushing into these same regions. The median inverter loading ratio has stabilized in 2016 at 1.3 for both tracking and fixed-tilt projects. Installed Prices: Median installed PV project prices within a sizable sample have fallen by two-thirds since the 2007-2009 period, to $2.2/WAC (or $1.7/WDC) for projects completed in 2016. The lowest 20th percentile of projects within our 2016 sample were priced at or below $2.0/WAC, with the lowest-priced projects around $1.5/WAC. Overall price dispersion across the entire sample and across geographic regions decreased significantly in 2016. Operation and Maintenance (“O&M”) Costs: What limited empirical O&M cost data are publicly available suggest that PV O&M costs were in the neighborhood of $18/kWAC-year, or $8/MWh, in 2016. These numbers include only those costs incurred to directly operate and maintain the generating plant. Capacity Factors: The cumulative net AC capacity factors of individual PV projects range widely, from 15.4% to 35.5%, with a sample median of 26.3%. This project-level variation is based on a number of factors, including the strength of the solar resource at the project site, whether the array is mounted at a fixed-tilt or on a tracking mechanism, the inverter loading ratio, degradation, and curtailment. Changes in at least the first three of these factors drove mean capacity factors higher from 2010- to 2013-vintage projects, where they’ve remained fairly steady among both 2014- and 2015-vintage projects as an ongoing increase in the prevalence of tracking has been offset by a build-out of lower resource sites. Meanwhile, several of the newer CSP projects in the United States are struggling to match long-term performance expectations. PPA Prices: Driven by lower installed project prices and improving capacity factors, levelized PPA prices for utility-scale PV have fallen dramatically over time. Most recent PPAs in our sample are priced at or below $50/MWh levelized, with a few priced as aggressively as ~$30/MWh. Though impressive in pace and scale, these falling PPA prices have been offset to some degree by declining wholesale market value within high penetration markets like California, where in 2016 a MWh of solar generation was worth just 83% of a MWh of flat, round-the-clock generation. At the end of 2016, there were at least 121.4 GW of utility-scale solar power capacity within the interconnection queues across the nation. The growth within these queues is widely distributed across all regions of the country: California and the Southeast each account for 23% of the 83.3 GW of solar that first entered the queues in 2016, followed by the Northeast (17%), the Southwest (16%), the Central region (12%), Texas (6%) and the Northwest (3%). The widening geographic distribution of solar projects is a clear sign that the utility-scale market is maturing and expanding outside of its traditional high-insolation comfort zones.

14 SOLAR ENERGY↗
DOE OSTI2015

Data consistency conditions for truncated fanbeam and parallel projections

Purpose: In image reconstruction from projections, data consistency conditions (DCCs) are mathematical relationships that express the overlap of information between ideal projections. DCCs have been incorporated in image reconstruction procedures for positron emission tomography, single photon emission computed tomography, and x-ray computed tomography (CT). Building on published fanbeam DCCs for nontruncated projections along a line, the authors recently announced new DCCs that can be applied to truncated parallel projections in classical (two-dimensional) image reconstruction. These DCCs take the form of polynomial expressions for a weighted backprojection of the projections. The purpose of this work was to present the new DCCs for truncated parallel projections, to extend these conditions to truncated fanbeam projections on a circular trajectory, to verify the conditions with numerical examples, and to present a model of how DCCs could be applied with a toy problem in patient motion estimation with truncated projections. Methods: A mathematical derivation of the new parallel DCCs was performed by substituting the underlying imaging equation into the mathematical expression for the weighted backprojection and demonstrating the resulting polynomial form. This DCC result was extended to fanbeam projections by a substitution of parallel to fanbeam variables. Ideal fanbeam projections of a simple mathematical phantom were simulated and the DCCs for these projections were evaluated by fitting polynomials to the weighted backprojection. For the motion estimation problem, a parametrized motion was simulated using a dynamic version of the mathematical phantom, and both noiseless and noisy fanbeam projections were simulated for a full circular trajectory. The fanbeam DCCs were applied to extract the motion parameters, which allowed the motion contamination to be removed from the projections. A reconstruction was performed from the corrected projections. Results: The mathematical derivation revealed the anticipated polynomial behavior. The conversion to fanbeam variables led to a straight-forward weighted fanbeam backprojection which yielded the same function and therefore the same polynomial behavior as occurred in the parallel case. Plots of the numerically calculated DCCs showed polynomial behavior visually indistinguishable from the fitted polynomials. For the motion estimation problem, the motion parameters were satisfactorily recovered and ten times more accurately for the noise-free case. The reconstructed images showed that only a faint trace of the motion blur was still visible after correction from the noisy motion-contaminated projections. Conclusions: New DCCs have been established for fanbeam and parallel projections, and these conditions have been validated using numerical experiments with truncated projections. It has been shown how these DCCs could be applied to extract parameters of unwanted physical effects in tomographic imaging, even with truncated projections.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Lesion insertion in the projection domain: Methods and initial results

Purpose: To perform task-based image quality assessment in CT, it is desirable to have a large number of realistic patient images with known diagnostic truth. One effective way of achieving this objective is to create hybrid images that combine patient images with inserted lesions. Because conventional hybrid images generated in the image domain fails to reflect the impact of scan and reconstruction parameters on lesion appearance, this study explored a projection-domain approach. Methods: Lesions were segmented from patient images and forward projected to acquire lesion projections. The forward-projection geometry was designed according to a commercial CT scanner and accommodated both axial and helical modes with various focal spot movement patterns. The energy employed by the commercial CT scanner for beam hardening correction was measured and used for the forward projection. The lesion projections were inserted into patient projections decoded from commercial CT projection data. The combined projections were formatted to match those of commercial CT raw data, loaded onto a commercial CT scanner, and reconstructed to create the hybrid images. Two validations were performed. First, to validate the accuracy of the forward-projection geometry, images were reconstructed from the forward projections of a virtual ACR phantom and compared to physically acquired ACR phantom images in terms of CT number accuracy and high-contrast resolution. Second, to validate the realism of the lesion in hybrid images, liver lesions were segmented from patient images and inserted back into the same patients, each at a new location specified by a radiologist. The inserted lesions were compared to the original lesions and visually assessed for realism by two experienced radiologists in a blinded fashion. Results: For the validation of the forward-projection geometry, the images reconstructed from the forward projections of the virtual ACR phantom were consistent with the images physically acquired for the ACR phantom in terms of Hounsfield unit and high-contrast resolution. For the validation of the lesion realism, lesions of various types were successfully inserted, including well circumscribed and invasive lesions, homogeneous and heterogeneous lesions, high-contrast and low-contrast lesions, isolated and vessel-attached lesions, and small and large lesions. The two experienced radiologists who reviewed the original and inserted lesions could not identify the lesions that were inserted. The same lesion, when inserted into the projection domain and reconstructed with different parameters, demonstrated a parameter-dependent appearance. Conclusions: A framework has been developed for projection-domain insertion of lesions into commercial CT images, which can be potentially expanded to all geometries of CT scanners. Compared to conventional image-domain methods, the authors’ method reflected the impact of scan and reconstruction parameters on lesion appearance. Compared to prior projection-domain methods, the authors’ method has the potential to achieve higher anatomical complexity by employing clinical patient projections and real patient lesions.

60 APPLIED LIFE SCIENCES↗