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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Investigation of Polyurethane and Fire-Retardant Foams as a Radiological Contamination Fixatives - 20202

Fixation of radiological contamination in decommissioning and deactivation can reduce worker risk, and mitigate potentially hazardous conditions; however, nearly every marketed contamination fixative has been found to be flammable, a significant concern in radiological facilities. Coupled with this, industry fixatives are normally used as a thin coating which can present problems when attempting to stabilize irregular void spaces or areas that are difficult to access and ensure full coverage. To this end, Savannah River National Laboratory (SRNL), in conjunction with Florida International University (FIU), have begun investigating the applicability of polyurethane based foaming materials, which will expand to fill a given asymmetric volume and provide fire retardancy to ensure no release of contamination in the event of a facility fire. Commercial foams undergo exothermic reactions resulting in gaseous release that subsequently causes the curing foam material to expand. Heat generation during curing can potentially compromise rubber parts of an enclosure, a significant concern in nuclear facilities. To mitigate large body heat generation, SRNL has also examined multiple layering of the material to ensure compatibility of the curing material with a previously cured body of the same material. Environmental studies were also completed in order to determine the influence on polyurethane based foams curing process. These studies showed that nearly half of the materials tested delaminated from a cured body of the same material, a property not discussed in commercially available documentation on the products. Of note was the compatibility of the foaming material with the substrate, depending on the type material that the foam was cured in/on, significant delamination could occur. Mechanical testing via tensile pull tester, dynamic mechanical analysis (DMA), and thermogravimetric analysis (TGA) was also performed. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Utility-Scale Solar, 2024 Edition: Empirical Trends in Deployment, Technology, Cost, Performance, PPA Pricing, and Value in the United States [Slides]

Berkeley Lab’s “Utility-Scale Solar, 2024 Edition” presents analysis of empirical plant-level data from the U.S. fleet of ground-mounted photovoltaic (PV), PV+battery, and concentrating solar-thermal power (CSP) plants with capacities exceeding 5 MWAC (PV plants of 5 MWAC or less, including residential rooftop systems, are covered separately in Berkeley Lab’s companion annual report, Tracking the Sun). Key findings from this year’s report include: -18.5 GWAC of new utility-scale PV capacity came online in 2023, bringing cumulative installed capacity to more than 80.2 GWAC across 47 states. Installed costs continued to fall in 2023. Relative to 2022, capacity-weighted averages decreased by 8% to -$\$1.43$/WAC (or $\$1.08$/WDC). Costs, based on a 7.1 GWAC sample of 76 plants completed in 2023, have fallen by 75% (averaging 10% annually) since 2010. Plant-level capacity factors vary widely, from 6% to 36% (on an AC basis), with a sample median of 24%. -Levelized cost of energy (LCOE) of new 2023 projects increased slightly to $\$46$/MWh prior to the application of tax credits but continued to fall to $\$31$/MWh when accounting for federal incentives. PPA prices have largely followed the decline in solar’s LCOE over time, but newly signed longer-term PPA prices have increased since 2021, to an average of $\$35$/MWh (levelized, in 2023 dollars). -Solar’s average energy and capacity value (i.e., ability to offset costs of other power generation sources) across the U.S. was $\$45$/MWh in 2023. Solar’s average market value was lowest in CAISO ($\$27$/MWh), the market with the greatest solar generation share, and highest in ERCOT ($\$67$/MWh). -Newer solar projects had greater market value in 2023 than their generation costs, yielding $\$1.1$ billion in benefits. Projects built in 2022 delivered on average $\$15$/MWh more market value than their costs in 2023. -Solar’s combined value from wholesale electricity markets, public health and climate damage reduction were greater than generation costs and incentives, yielding $\$13.7$ billion in net benefits in 2023. We estimate U.S. health benefits of $\$24$/MWh and reduced global climate damages of $\$101$/MWh. -Adding battery storage is one way to increase the value of solar. Deployment of 52 new PV+battery hybrid plants set a record with 5.3 GW installed in 2023. Our public data file tracks metadata and PPA prices from more than 100 PV+battery hybrid projects that are already online or that have secured offtake arrangements. -Looking ahead, a massive pipeline of at least 1,085 GW of solar capacity dominates the nation’s interconnection queues at the end of 2023. Nearly 571 GW, or 53%, of that total was paired with a battery – in CAISO it was a staggering 98%. Historically only 10% of the requested solar capacity is built. -For more information, and to explore related interactive data visualizations, go to utilityscalesolar.lbl.gov.

14 SOLAR ENERGY↗
DOE OSTI2022

Use of Systems Engineering in Repurposing Coal-Fired Power Plants with Malta Pumped Thermal Energy Storage System

he electric sector across North America is facing a transition. Both economics and policy decisions have pointed towards a broad retirement of fossil assets across markets. Owners are facing the problem of how to evolve the base of the electric sector from fossil asset to greener alternative. Coal-fired power plants built the modern electricity grid. Their rotating machinery are the beating heart of the grid, providing essential resiliency and reliability services. Power plant retirements are disruptive to plant workforces and cause outsized impacts on surrounding communities. The transition from thermal power plants that use rotating machinery to generate electricity (e.g., coal- and gas-fired plants) to variable, inverter-based generation (e.g., solar and wind) is affecting the reliability of the electric grid. Grid operators and national regulators have issued warnings about known and anticipated risk. In 2021, Malta Inc. was awarded a Department of Energy (DOE) grant to study how to integrate a Malta 100MW Pumped Heat Energy Storage (PHES) system with a retiring coal-fired power plant to meet emissions requirements, retain plant workforces, preserve communities, and maintain grid reliability. This presentation provides a summary of this study, focusing on how systems engineering approach was used to arrive at a proposed design concept that met multiple objectives and requirements. There will be three main parts for this presentation. The first part of the presentation will focus on how different systems engineering was applied for this work. In particular, the following areas: stakeholder engagement, site selection process, developing requirements and use cases for the integrated system, defining the system and its boundary, coming up with different system architecture/option, performing a techno-economic analysis to compare the different options and down selection of the preferred option, will be discusses. For these areas, discussion on the decisions on how much breadth and depth to go into each area will be provided. These discussions provide good insights into how to apply systems engineering. The second part of the presentation will provide a deeper dive into the two recommended integration options that repurpose coal-fired power plants with Malta PHES system. The comparison of the two options and general guidance of how to choose an option will be provided. This is particularly useful for utilities who are facing coal-plant retirements. The two options will be compared based on its performance (such as power output, efficiency), complexity, and cost. The social impact on local communities of the two options will also be discussed. The final part of the presentation will discuss the impact that this work has had, including Malta Inc. being invited to the White House to discuss progress and outcomes of this work with the Interagency Working Group on Coal and Power Plant Communities and Economic Revitalization. In summary, this presentation aims to provide a showcase of how sy

25 ENERGY STORAGE↗
NASA NTRS2024

Advances in Thermoplastic Composites Over Three Decades – A Literature Review

Recently, there has been a renewed interest in thermoplastic composites driven mainly by advances in automation which can lead to significant cost reductions by increasing manufacturing rates while simultaneously reducing the part count and energy consumption relative to the manufacturing of thermoset composites. At the same time, new material systems have been developed and the thermoplastic composites prepreg material quality has improved over time. Additionally, thermoplastic composites have nearly infinite room-temperature shelf life and production scraps can be reused and retired parts can be recycled, providing opportunities for more sustainable operations and downstream markets. These factors have contributed to a strong interest in advancing thermoplastic composites for aerospace, automotive, and other industrial applications. The objective of the present study is to assess the state of the art regarding the maturity and performance of thermoplastic composite materials and to document the advances made in manufacturing and assembly of thermoplastic composite structures. Therefore, more than 200 NASA reports, conference proceedings and journal papers spanning three and a half decades (1986-2022) were reviewed and the findings summarized. The current study, however, is limited in scope with a focus on the application of thermoplastic composites to aircraft structures. Further, the study does not provide a comprehensive assessment of the available literature but rather offers an overview of past and present research being conducted in the field of thermoplastic composites. The information provided may be used to identify gaps and help guide future research and development. In this report, the opportunities offered by the use of thermoplastic composites in general and challenges encountered in particular are presented first. Second, an overview of thermoplastic materials is presented, manufacturing methods are discussed, and new methods for fastener-less assembly such as welding are introduced. Third, tests that have been performed on different levels of the building block, ranging from coupon to structural level, are presented. In particular, fracture toughness results for different thermoplastic composite materials are used to demonstrate their performance compared to state-of-the-art thermoset composites. Fourth, several examples of analyses are discussed including process modelling and progressive damage analysis (PDA). An extensive list of references and appendices with tables support the narrative. Lastly, a brief summary with outlook and recommendations for future research is provided.

composites↗
DOE OSTI2021

Storage Futures Study - Distributed Solar and Storage Outlook: Methodology and Scenarios

This presentation discusses the fourth report in NREL’s Storage Futures Study (SFS) publications. The SFS is a multiyear research project that explores the role and impact of energy storage in the evolution and operation of the U.S. power sector. The SFS is designed to examine the potential impact of energy storage technology advancement on the deployment of utility-scale storage and the adoption of distributed storage, and the implications for future power system infrastructure investment and operations. This report describes the expanded capabilities of the Distributed Generation Market Demand (dGen) model to analyze the economics of distributed (behind-the-meter) PV paired with battery storage systems and presents projections of adoption for the contiguous United States out to 2050 under a range of scenarios. These scenarios use technology cost and performance assumptions consistent with the National Renewable Energy Laboratory’s 2020 Standard Scenarios paired with updated battery cost projections and existing policies. Additional scenarios evaluate sensitivities to the value of backup power and DER compensation mechanisms, collectively characterizing the future potential for behind-the-meter storage and identifying key drivers of adoption. Adoption projections of DER and battery storage at high spatial and temporal resolution, as presented in this report, can enable informed planning of technical infrastructure that can help planners capture the benefits and mitigate challenges to support the ongoing trend toward distributed electricity generation.

backup power↗
DOE OSTI2025

Artificial Intelligence and Machine Learning Applications in Modern Power Systems

Machine learning (ML) and artificial intelligence (AI) algorithms offer valuable tools for the analysis and interpretation of large datasets. These tools have the capability to uncover insights that may not be readily apparent within these datasets. In recent years, the integration of ML and AI has become increasingly prevalent in various applications within the power system domain. One of the earliest instances of machine learning in power systems can be traced back to demand forecasting, where artificial neural networks were employed for short-term load forecasting. In contemporary power systems, an abundance of high-resolution geospatial and temporal data is generated at various time intervals, ranging from sub-seconds (Phasor Measurement Units or PMUs) to seconds (Supervisory Control and Data Acquisition or SCADA), minutes (Process Information or PI), and extending to days, months, and years. These datasets contain valuable information concerning system reliability and performance. This information holds the potential to offer critical insights into system operations, as well as solutions for predicting and mitigating contingencies to prevent cascading outages. Despite the immense power of machine learning tools, system operators, planners, and utilities often exhibit hesitancy in fully embracing AI-enabled system operations and planning. This cautious approach persists, even as numerous diverse applications of machine learning continue to emerge in the realm of power systems. In this chapter, our focus will delve deep into ML and AI applications tailored for power systems. These applications aim to furnish system operators with enhanced situational awareness and augment their decision-making capabilities, especially during challenging operating conditions. Specific areas of interest encompass root cause analyses of electricity market datasets and the strategic selection of representative samples from vast power system databases for training ML/AI models. Finally, the chapter will conclude with a short discussion on the future of ML/AI in power systems and possible directions that the industry is moving towards.

power system applications, machine learning (ML), ↗
DOE OSTI2020

Foundations of an Electric Mobility Strategy for the City of Mexicali

The Foundations of an Electric Mobility Strategy for the city of Mexicali aligns with numerous energy, environmental, and transport plans and will help Mexicali meet multiple related goals. Mexicali’s energy mix, with 28% renewables, already enables plugin electric vehicles (PEVs) to reduce the mass of greenhouse gases (GHGs) per km driven 2/3 below that of their conventional counterparts. This GHG benefit will increase should Mexicali take steps to further increase their share of renewables in their electricity supply. Beyond increasing renewables, Mexicali could possibly deploy PEVs so that electric load is added in the right location (depending on further analysis of substations and feeders) and at the right time (between 21:00 and 11:00) in order to minimize grid upgrade costs. There are a handful of charge timing control mechanisms –at various stages of development– that Mexicali could implement. Transport electrification can facilitate mass transit by powering buses, trains, and small vehicles that get people from their homes or work to the transit stations and vice versa. Mexicali could utilize fleets as early PEV adopters in order to gain acceptance and add electric vehicle supply equipment (EVSE). Recommended prioritization of different types of fleets are suggested in this report: transit buses, school buses, airport ground support equipment (GSE), refuse trucks, taxis, shuttle buses, campus vehicles, delivery trucks, utility trucks, and finally semitrailers. There are a handful of policy options that Mexicali could use to incentivize fleets to purchase PEVs, including mandates, economic incentives, energy performance contracts, waivers to access restrictions, electricity discounts, and EVSE requirements in building codes. Mexicali’s taxi fleet was an early adopter of PEVs and had experienced some challenges—mostly related to the insufficient range of the taxis due to hot weather. In this report, we strategize ways to extend the range of the current electric taxis, including ways to make charging more convenient to the drivers, and more suggestions for appropriate vehicles to purchase in the future. This report also includes the groundwork of geotracking Mexicali’s taxi fleet so that more detailed recommendations can be made in the future. Once fleets have increased PEV acceptance and EVSE installations, the market will be ready to expand to private vehicle owners. In order to do this, more EVSE needs to be installed in the right locations. This mobility strategy lays out general local areas where EVSE could be well utilized, based on traffic patterns, land use, and demographic data. Mexicali could approach businesses within these areas that would likely make suitable hosts, based on how well they can profit from the additional business that EVSE would bring. Mexicali could then adopt a series of purchase incentives (including sales tax waivers or access to high-occupancy vehicles [HOV] lanes) that would encourage private vehicle owners to purchase PEVs. Purchase incentives run the risk of creating equity issues, which can be countered by promoting electrification in mass transit, creating more HOV lanes that have PEV exemptions, and installing EVSEs in underserved communities. Private PEV ownership will require a set of experts that Mexicali can help train, including PEV repair technicians, EVSE installation electricians, and first responders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Scout Benchmark Scenarios for U.S. Building Energy and CO2 Emissions to 2050

Overview and Intended Use Cases: These scenarios establish a range of futures for U.S. buildings sector energy use and CO2 emissions to 2050 using Scout (scout.energy.gov), a reproducible and granular model of U.S. building energy use, emissions, and consumer costs developed by the U.S. national labs for the U.S. Department of Energy's Building Technologies Office (BTO). Scout benchmark scenario data are suitable for the following example use cases: setting high-level policy goals for the U.S. buildings sector to 2050 (e.g., X% building CO2 emissions reductions vs. 2005 levels by 2030, Y% reductions vs. 2005 levels by 2050); exploring the effects of key dynamics driving U.S. buildings sector energy and CO2 emissions to 2050 that could be affected by policy levers (e.g., raising minimum technology performance levels; accelerating electrification and/or retrofit rates; introducing breakthrough technologies to the market); determining priority segments (regions, building types, and end use/technology types) and sequencing of U.S. buildings sector energy and CO2 emissions reductions to 2050 under a given set of assumptions; and/or identifying the energy and emissions impacts or cost effectiveness of specific technologies or operational approaches of interest—in isolation or after considering competition with other measures in a scenario portfolio. Scenario Summary: A total of 8 scenarios explore the effects of changes across both the demand- and supply-side of building energy use on annual U.S. building energy use and CO2 emissions from 2022–2050. Scenarios are organized into three groups representing low, moderate, and best-case potentials for building decarbonization, respectively.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Modeling nuclear energy’s future role in decarbonized energy systems

Increased attention has been focused on the potential role of nuclear energy in future electricity markets and energy systems as stakeholders target rapid and deep decarbonization and reductions in fossil fuel use. This paper examines models of electric sector planning and broader energy systems optimization to understand the prospective roles of nuclear energy and other technologies. In this perspective, we survey modeling challenges in this environment, illustrate opportunities to propagate best practices, and highlight insights from the deep decarbonization literature on the range of visions for nuclear energy's role. Nuclear energy deployment is highest with combinations of stringent emissions policies, nuclear cost reductions, and constraints on the deployment of other technologies, which underscores model dimensions related to these areas. New modeling capabilities are needed to adequately address emerging issues, including representing characteristics and applications of nuclear energy in systems models, and to ensure the relevance of models for policy and planning as deeper decarbonization is explored.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

PHEV Distribution Grid Integration and Smart Systems Testing: Cooperative Research and Development Final Report

To continue NREL's mission, which includes preparing technologies and markets with "speed and scale," NREL researchers will collaborate with Toyota on plug-in electric vehicle technology. Toyota will provide a collection of plug-in hybrid electric vehicles ("PHEVs" [and ultimately including PEVs], collectively, the "Vehicles") to conduct infrastructure interaction testing at NREL facilities. NREL will use available resources in the Vehicle Testing and Integration Facility (VTIF), its staff parking garage with numerous commercial Electric Vehicle Supply Equipment ("EVSEs"), and its Energy Systems Integration Facility (ESIF) to safely execute research experiments that highlight potential distribution system power quality challenges related to plug-in electric vehicles. The expected outcome of this project is a better understanding of the correlation of individual vehicle power quality attributes to a system of vehicles on a distribution network. The data collected and the simulations conducted will be used to guide future experiments and project development that aid in the deployment of plug-in electric vehicles ("PEV").

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Knowledge Spillovers and Cost Reductions in Solar Soft Costs

Despite the commonly acknowledged importance of knowledge spillovers in reducing solar soft costs, we are only beginning to answer a fundamental question: who learns what (knowledge acquisition), from whom (knowledge production), and how (spillover mechanisms)? Until recently, this important topic has been largely unexplored in the case of solar soft costs. Thus, this project set out to identify how knowledge spillovers affect soft costs in the U.S. photovoltaic (PV) installation industry, specifically how important spillovers are, what types of knowledge are most likely to spillover, and how networks of actors affect spillovers. Our findings offer insights for designing solutions that address problems associated with knowledge spillovers and that leverage spillovers to reduce solar soft costs. Recognizing the ambiguity in the definition of soft costs, i.e., “non-hardware costs,” and variability in soft cost categories, we developed the Solar Soft Cost Ontology (SSCO) to systematically identify key concepts related to soft costs, network actors, learning processes, and the relationships between them. This ontology served as a foundational organizational structure for the methodology of the remaining tasks: case studies, surveys, pricing analysis, patent analysis, network analysis, and project integration across tasks. While there is substantial learning among installers that is reducing the soft costs for PV installations, most of that learning is retained by firms rather than spread across the industry. The positive relationship between experience accumulation and cost reductions is typically explained as learning by doing (LBD), but we find that LBD effects are mediated by other learning mechanisms, including learning by searching and learning by interacting. Knowledge spillovers have significant potential to reduce solar PV soft costs, but successful knowledge spillover pathways are complex and non-trivial. There are a wide variety of ways to construct an installation business, thus categories of firms that can effectively cross-learn directly are small and what knowledge is relevant to whom is challenging and costly for firms to assess. This fragmentation limits the critical mass needed for spillover related soft cost reductions. Knowledge does not flow directly between installers. Indirect knowledge transfer pathways are critical: distributors, software providers, collaboratives, and hiring. Furthermore, diverse, more integrated knowledge networks tend to promote successful learning by organizations and across the system as a whole. Accordingly, we find the need to supporting the whole ecosystem using an integrated policy and programmatic approach to support installers, distributors, complementary sector, and facilitators. Overall, a deliberate policy-mix design is needed to reduce the solar PV deployment barrier in terms of installation cost reductions, because deployment policies could potentially interact with policies that facilitate network-building and technological innovation. A combination of deployment policies, innovation-support policies, and network-facilitating policies could potentially lead to a more desired market outcome through achieving higher joint learning rates from firms’ cumulative experiences developed in a more integrated production and deployment ecosystem.

14 SOLAR ENERGY↗
NASA NTRS2013

Kinect Engineering with Learning (KEWL)

According to a Nielsen survey at the time of this reporting, 41% of all households have a game console. This is one market in which NASA has been absent from education and outreach efforts. Kinect Engineering with Learning (KEWL) is made to enter into that market and bring NASA education and outreach to a very familiar venue. KEWL creates an education and outreach experience that is more participatory, both in a school and museum environment. KEWL is a set of applications that runs on an Xbox 360 using the Kinect controller used for education and outreach. These applications currently include: Train R2, a visual simulation of Robonaut 2 that allows students to control a virtual R2 in a game environment; Drive R2, an interface using the Xbox 360 and Kinect controller that allows students to control the real R2 using the methods they learned playing Train R2; ISS experience, a visual tour of the interior of the International Space Station where students use their body to fly through the virtual ISS; Gravity Ball, a simulation of throwing balls in the gravity of different planets; Solar Array repair, a simulation of the simplified STS-121 solar array repair mission; and PlaySpace, a Mars/Moon application that allows students to experience different aspects of Mars/Moon. Users can "fly through" the ISS using their body, allowing an experience similar to what an astronaut would have on orbit. In PlaySpace, users can fly over the surface of Mars and view surface data obtained by Mars rovers. Users of Train R2 and Drive R2 can experience what it is like to control a robot over a distance with a time delay, simulating the time delay that would occur between ground control and an on-orbit robot. The initial ISS experiences were built using parts of code from the NASA Enigma software. The models used in these experiences were also from the Integrated Graphics Operations and Analysis Lab model database. The PlaySpace experience incorporates surface data obtained from NASA rovers and satellites and was built by NASA JPL.

Goza, Sharon↗
NASA NTRSDate not supplied

Passenger Aggregation Network with Very Efficient Listing (PANVEL) Ridesharing Model for Urban Air Mobility

This paper introduces a ridesharing model useful for examining the role of ridesharing in advancing Urban Air Mobility (UAM) operations. Although the success of UAM will likely require a host of new technologies in aircraft design, airspace management, autonomy, and more, operational innovations like ridesharing may also be key, especially to lower operating costs and attract a broader market. The ridesharing algorithm introduced, termed the Passenger Aggregation Network with Very Efficient Listing (PANVEL) model, estimates trip numbers and passenger occupancy aboard particular aircraft within a UAM network in a metropolitan area. This algorithm is applied within a transportation computational framework to determine the impact of ridesharing on mode choice, passenger travel patterns, and transportation costs. The algorithm aggregates passengers traveling between identical origin-destination pairs, factoring in individual-specific metrics, such as value of time and alternative mode options, to generate high load factors on UAM aircraft. The computational framework simulates passenger mode-choice selections using an effective-cost approach to determine the number of ridesharing UAM-preferred trips, and results with ridesharing are representative of a rough upper bound on UAM ridership potential for a given metro area. A case study in the Cleveland metro area is presented to demonstrate the algorithm and assess ridesharing potential.

advanced air mobility↗
NASA NTRSDate not supplied

Passenger Aggregation Network with Very Efficient Listing (PANVEL) Ridesharing Model for Urban Air Mobility

This presentation introduces a ridesharing model useful for examining the role of ridesharing in advancing Urban Air Mobility (UAM) operations. Although the success of UAM will likely require a host of new technologies in aircraft design, airspace management, autonomy, and more, operational innovations like ridesharing may also be key, especially to lower operating costs and attract a broader market. The ridesharing algorithm introduced, termed the Passenger Aggregation Network with Very Efficient Listing (PANVEL) model, estimates trip numbers and passenger occupancy aboard particular aircraft within a UAM network in a metropolitan area. This algorithm is applied within a transportation computational framework to determine the impact of ridesharing on mode choice, passenger travel patterns, and transportation costs. The algorithm aggregates passengers traveling between identical origin-destination pairs, factoring in individual-specific metrics, such as value of time and alternative mode options, to generate high load factors on UAM aircraft. The computational framework simulates passenger mode-choice selections using an effective-cost approach to determine the number of ridesharing UAM-preferred trips, and results with ridesharing are representative of a rough upper bound on UAM ridership potential for a given metro area. A case study in the Cleveland metro area is presented to demonstrate the algorithm and assess ridesharing potential.

advanced air mobility↗
DOE OSTI2025

Commercial building HVAC demand flexibility with model predictive control: Field demonstration and literature insights

Model Predictive Control (MPC) for building Heating Ventilation and Air Conditioning (HVAC) systems is beginning to gain traction in the market, with a few controls companies incorporating it into their product offerings. However, it remains difficult to assess whether the energy cost savings are enough to justify the cost of MPC implementation for a particular building, given the limited number of reported demonstrations. For small commercial and residential buildings with relatively uniform systems, standardized approaches can help lower implementation costs. In contrast, for large buildings or district systems, the potential magnitude of cost savings could justify more customized solutions. Estimating the cost-effectiveness of MPC becomes more challenging for medium and large commercial buildings, where a one-size-fits-all solution may not be suitable, and the potential energy cost savings may be insufficient to justify a customized solution. To make MPC technology more appealing, incorporating additional value streams beyond energy efficiency alone can significantly increase its attractiveness. One such revenue stream is demand flexibility, in response to dynamic electricity prices, where MPC can leverage the thermal mass of the building to shift the load and support the grid. Building on an extensive literature review of MPC field studies focused on cost savings and demand flexibility, this paper presents the results of implementing MPC control in a large office building HVAC system in Berkeley, CA. Four different dynamic electricity price profiles were integrated into the MPC objective function to shift building demand while maintaining comfort, and field testing was performed with each price profile across four seasons. The results show potential for 40–65 % demand decrease percentage and up to 61 % annual cost savings compared to the existing rule-based control strategy, under the tested dynamic price scenarios. This paper also presents a sensitivity analysis on the cost savings with respect to the price profile variability, discusses the implementation effort for the price-responsive MPC, and compares the cost savings found in this study to those found in literature on the basis of dynamic price variability, or so-called Electricity Price Relative Standard Deviation.

Zanetti, Ettore↗
NASA NTRS2009

Declining Global Per Capita Agricultural Production and Warming Oceans Threaten Food Security

Despite accelerating globalization, most people still eat food that was grown locally. Developing countries with weak purchasing power tend to import as little food as possible from global markets, suffering consumption deficits during times of high prices or production declines. Local agricultural production, therefore, is critical to both food security and economic development among the rural poor. The level of local agricultural production, in turn, will be controlled by the amount and quality of arable land, the amount and quality of agricultural inputs (fertilizer, seeds, pesticides, etc.), as well as farm-related technology, practices, and policies. In this paper we discuss several emerging threats to global and regional food security, including declining yield gains that are failing to keep up with population increases, and warming in the tropical Indian Ocean and its impact on rainfall. If yields continue to grow more slowly than per capita harvested area, parts of Africa, Asia, and Central and Southern America will experience substantial declines in per capita cereal production. Global per capita cereal production will potentially decline by 14 percent between 2008 and 2030. Climate change is likely to further affect food production, particularly in regions that have very low yields due to lack of technology. Drought, caused by anthropogenic warming in the Indian and Pacific Oceans, may also reduce 21 st century food availability by disrupting Indian Ocean moisture transports and tilting the 21 st century climate toward a more El Nino-like state. The impacts of these circulation changes over Asia remain uncertain. For Africa, however, Indian Ocean warming appears to have already reduced main growing season rainfall along the eastern edge of tropical Africa, from southern Somalia to northern parts of the Republic of South Africa. Through a combination of quantitative modeling of food balances and an examination of climate change, we present an analysis of emerging threats to global food security.

Funk, Chris C.↗
NASA NTRS2012

FERMI/GLAST Integrated Trending and Plotting System Release 5.0

An Integrated Trending and Plotting System (ITPS) is a trending, analysis, and plotting system used by space missions to determine performance and status of spacecraft and its instruments. ITPS supports several NASA mission operational control centers providing engineers, ground controllers, and scientists with access to the entire spacecraft telemetry data archive for the life of the mission, and includes a secure Web component for remote access. FERMI/GLAST ITPS Release 5.0 features include the option to display dates (yyyy/ddd) instead of orbit numbers along orbital Long-Term Trend (LTT) plot axis, the ability to save statistics from daily production plots as image files, and removal of redundant edit/create Input Definition File (IDF) screens. Other features are a fix to address invalid packet lengths, a change in naming convention of image files in order to use in script, the ability to save all ITPS plot images (from Windows or the Web) as GIF or PNG format, the ability to specify ymin and ymax on plots where previously only the desired range could be specified, Web interface capability to plot IDFs that contain out-oforder page and plot numbers, and a fix to change all default file names to show yyyydddhhmmss time stamps instead of hhmmssdddyyyy. A Web interface capability sorts files based on modification date (with newest one at top), and the statistics block can be displayed via a Web interface. Via the Web, users can graphically view the volume of telemetry data from each day contained in the ITPS archive in the Web digest. The ITPS could be also used in nonspace fields that need to plot data or trend data, including financial and banking systems, aviation and transportation systems, healthcare and educational systems, sales and marketing, and housing and construction.

Ritter, Sheila↗
DOE OSTI2020

Integrated Mid-Continent Stacked Carbon Storage Hub Project Phase II (Final Summary Report)

The Phase II Integrated Midcontinent Stacked Carbon Storage Hub (IMSCS-HUB) is part of the Carbon Storage Assurance Facility Enterprise (CarbonSAFE) established by the United States Department of Energy (DOE) National Energy Technology Laboratory (NETL). CarbonSAFE is phased to support the development of commercial-scale (50 million metric tonnes [Mt] over a 30-year period) carbon capture, utilization, and storage (CCUS) in the United States. The IMSCS-HUB study area comprises carbon dioxide (CO 2 ) sources in Iowa, Kansas, and Nebraska (the source corridor), and CO 2 sinks in Kansas and Nebraska (the storage corridor), representing the first large-scale project for the Midcontinent region. The stacked storage corridor is characterized by alternating sequences of deep saline formations, oil-bearing reservoirs, shale, and evaporite units that are conducive to vertically stacked CO 2 injection for geologic storage and enhanced oil recovery (EOR). Three sites within the IMSCS-HUB stacked storage corridor were evaluated in Phase II for commercial CCUS feasibility: one in southwest-central Nebraska, Sleepy Hollow Field (SHF), a second in southwestern Nebraska near Madrid (Madrid), and a third in southwestern Kansas, the Patterson Site (composed of the Patterson, Heinitz, Hartland, and Oslo fields). In Phase II, the team assessed the feasibility of storage complexes at the potential storage sites in Nebraska and Kansas to support a commercial-scale storage hub that integrates proven CO 2 capture technology and transport from nearby ethanol sources. Building on lessons learned from the DOE-NETL Regional Carbon Sequestration Partnerships (RCSPs), the Project Team has identified a clear strategy to meet DOE’s 2025 objective of commercial carbon capture and storage (CCS) implementation by developing a CO 2 market and infrastructure that relies on multiple ethanol-based CO 2 sources in the short term and the incorporation of multiple coal-fired power plant CO 2 sources when commercial capture is economically viable. The team also leveraged the updated 45Q tax credit to develop capture and transport infrastructure. Commercial-scale CCUS is feasible at two candidate storage sites studied, the Madrid, Nebraska Site and the Patterson Site in Kearny County, Kansas. The Sleepy Hollow Field in Nebraska was found to be an attractive candidate for stacked storage with CO 2 -EOR (Battelle 2020e). Outreach efforts facilitated engagement from industry, government, and research sectors (Battelle and GPI, 2020) and an outreach plan for future phases of the project was developed to address issues that are of concern in the IMSCS-HUB project area (Battelle, 2020f). All components of a CCUS project were determined to be feasible in the IMSCS-HUB region and Risk Mitigation Plan was developed and includes strategies to mitigate risks associated with each project component (Battelle, 2020j). A roadmap was developed to obtain the required UIC permits for an integrated CCUS project (Battelle, 2020k). The regional storage resource characterization demonstrated significant opportunity for commercial-scale projects in the IMSCS-HUB storage corridor with 577.4 Mt of stacked CO 2 storage capacity and the potential to produce 181.9 MMbbls of oil via EOR across 17 individual storage areas (Battelle and ARI, 2020). The pipeline assessment study found viable pipeline routes that connected 45Q-eligible ethanol plants, coal fired power plants, and other sources in the IMSCS-HUB corridor. The comprehensive results of subsurface characterization, modeling efforts, outreach assessment, and regulatory analysis from were integrated to develop a Detailed Commercial Development Plan for the IMSCS-HUB (Battelle, 2020n). Commercialization efforts will involve obtaining Class VI UIC permits, establishing and finalizing the pipeline route, and evaluating capture projects at participating CO 2 sources. Phases I and II of the IMSCS-HUB CarbonSAFE provide a strong foundation for safely, efficiently, and cost-effectively characterizing and permitting commercial-scale project sites in the region. The plan for implementation of commercial-scale CCUS projects in the IMSCS-HUB is aligned with the objectives of CarbonSAFE Phase III: Site Characterization and CO 2 Capture Assessment.

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