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DOE OSTI2014

AVTA Federal Fleet PEV Readiness Data Logging and Characterization Study for Department of Veterans Affairs – VA Manhattan Campus

This report focuses on the Department of Veterans Affairs, VA Manhattan Campus (VA- Manhattan) fleet to identify the daily operational characteristics of select vehicles and report findings on vehicle and mission characterizations to support successful introduction of plug-in electric vehicles (PEVs) into the agency’s fleet. Individual observations of these selected vehicles provide the basis for recommendations related to electric vehicle adoption and whether a battery electric vehicle or plug-in hybrid electric vehicle (collectively called PEVs) can fulfill the mission requirements.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2015

Fossil fleet transition with fuel changes and large scale variable renewable integration

Variability in demand as seen by grid-connected dispatchable generators can increase due to factors such as greater production from variable generation assets (for example, wind and solar), increased reliance on demand response or customer-driven automation, and aggregation of loads. This variability results a need for these generators to operate in a range of different modes, collectively referred to as “flexible operations.” This study is designed to inform power companies, researchers, and policymakers of the scope and trends in increasing levels of flexible operations as well as reliability challenges and impacts for dispatchable assets. Background Because there is rarely a direct monetization of the value of operational flexibility, the decision to provide such flexibility is typically dependent on unit- and region-specific decisions made by asset owners. It is very likely that much greater and more widespread flexible operations capabilities will be needed due to increased variability in demand seen by grid-connected generators, uncertainty regarding investment in new units to provide adequate operational flexibility, and the retirement of older, uncontrolled sub-critical pulverized coal units. Objective To enhance understanding of the technical challenges and operational impacts associated with dispatchable assets needed to increase operational flexibility and support variable demand. Approach The study approach consists of three elements: a literature review of relevant prior studies, analysis of detailed scenarios for evolution of the future fleet over the next 35 years, and engineering assessment of the degree and scope of technical challenges associated with transformation to the future fleet. The study approach integrated two key elements rarely brought together in a single analysis—1) long-term capacity planning, which enables modeling of unit retirements and new asset investments, and 2) unit commitment analysis, which permits examination of hourly unit dispatch while considering operational limitations relevant to flexible operations capabilities.

James, Revis↗

DOE OSTI2016

Impact of Market Behavior, Fleet Composition, and Ancillary Services on Revenue Sufficiency

Revenue insufficiency, or the missing money problem, occurs when the revenues that generators earn from the market are not sufficient to cover both fixed and variable costs to remain in the market and/or justify investments in new capacity, which may be needed for reliability. The near-zero marginal cost of variable renewable generators further exacerbates these revenue challenges. Estimating the extent of the missing money problem in current electricity markets is an important, nontrivial task that requires representing both how the power system operates and how market participants behave. This paper explores the missing money problem using a production cost model that represented a simplified version of the Electric Reliability Council of Texas (ERCOT) energy-only market for the years 2012-2014. We evaluate how various market structures -- including market behavior, ancillary services, and changing fleet compositions -- affect net revenues in this ERCOT-like system. In most production cost modeling exercises, resources are assumed to offer their marginal capabilities at marginal costs. Although this assumption is reasonable for feasibility studies and long-term planning, it does not adequately consider the market behaviors that impact revenue sufficiency. In this work, we simulate a limited set of market participant strategic bidding behaviors by means of different sets of markups; these markups are applied to the true production costs of all gas generators, which are the most prominent generators in ERCOT. Results show that markups can help generators increase their net revenues overall, although net revenues may increase or decrease depending on the technology and the year under study. Results also confirm that conventional, variable-cost-based production cost simulations do not capture prices accurately, and this particular feature calls for proxies for strategic behaviors (e.g., markups) and more accurate representations of how electricity markets work. The analysis also shows that generators face revenue sufficiency challenges in this ERCOT-like energy-only market model; net revenues provided by the market in all base markup cases and sensitivity scenarios (except when a large fraction of the existing coal fleet is retired) are not sufficient to justify investments in new capacity for thermal and nuclear power units. Overall, the work described in this paper points to the need for improved behavioral models of electricity markets to more accurately study current and potential market design issues that could arise in systems with high penetrations of renewable generation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

What Fleets Need to Know About Alternative Fuel Vehicle Conversions, Retrofits, and Repowers

Many fleet managers have opted to incorporate alternative fuels and advanced vehicles into their lineup. Original equipment manufacturers (OEMs) offer a variety of choices, and there are additional options offered by aftermarket companies. There are also a myriad of ways that existing vehicles can be modified to utilize alternative fuels and other advanced technologies. Vehicle conversions and retrofit packages, along with engine repower options, can offer an ideal way to lower vehicle operating costs. This can result in long term return on investment, in addition to helping fleet managers achieve emissions and environmental goals. This report summarizes the various factors to consider when pursuing a conversion, retrofit, or repower option.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2018

Implementation of a Grid Connected Battery-Inverter Fleet Model

Batteries are designed to store electrical energy. The increasing variation in time value of energy has driven the use of batteries as controllable distributed energy resources (DER). This is enabled though low-cost power electronic inverters that are able to precisely control charge and discharge. This paper describes the software implementation of an open-source battery inverter fleet models in python. The Sandia BatterylnverterFleet class model can be used by scientists, researchers, and engineers to perform simulations of one or more fleets of similar battery-inverter systems connected to the grid. The program tracks the state- of-charge of the simulated batteries and ensures that they stay within their limits while responding to separately generated service requests to charge or discharge. This can be used to analyze control and coordination, placement and sizing, and many other problems associated with the integration of batteries on the power grid. The development of these models along with their python implementation was funded by the Grid Modernization Laboratory Consortium (GMLC) project 1.4.2. Definitions, Standards and Test Procedures for Grid Services from Devices.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

PV Fleet Performance Data Initiative (March 2020 Methodology Report)

Data for thousands of systems by multiple sources were transmitted to NREL for evaluation. Initial automated data quality assurance (QA) checks identified hundreds of systems (QA Tier 1) with high-quality meteorological and AC production data and hundreds of QA Tier 2 systems with adequate data quality. A standard RdTools analysis was conducted for these systems, evaluating performance loss on an annualized basis. To date with the systems evaluated so far, we find a median performance loss rate (aka Rd or degradation rates) for the entire fleet of -0.72%/year based on individual inverter data, which is in line with historical degradation rates previously published for modules and systems (-0.5% to -0.9% / yr, Jordan et al. 2016). A fleet-scale distribution based on revenue-grade meter data rather than inverter AC (alternating current) data yields a slightly different result. We are working to understand the difference between this result and the inverter-based result of -0.72%/year.

14 SOLAR ENERGY↗

DOE OSTI2023

Assessment of Cloud-Based Applications Enabling a Scalable Risk-Informed Predictive Maintenance Strategy Across the Nuclear Fleet

The current light water reactor fleet uses time-based or failure-based maintenance strategies to achieve high-capacity factors. But to make nuclear more competitive in the energy market, these reactors could utilize emerging technologies in terms of artificial intelligence (AI) and cloud computing to enable a cost-effective, predictive maintenance strategy. This report examines the feasibility of cloud computing for the nuclear industry’s needs in terms of the cloud’s computing capabilities, feasibility, and regulatory concerns. The technical viability of cloud computing was analyzed using one year worth of data from a boiling water reactor’s safety relief valve. Models were hosted on a local desktop, Idaho National Laboratory’s high-performance computer, and Microsoft Azure. Data was loaded, processed, and two types of models were trained in an A/B fashion. Based on the speed at which these actions were completed, it was used to determined that cloud computing has adequate computing resources. Additionally, the computing power can scale with the demanded load. To enable cloud computing in the existing fleet, additional sensors, networks, and other requirements must be implemented to ensure a smooth transition from current maintenance strategies. However, there is a benefit as the plant no longer needs manage their own servers, software, cybersecurity, and IT support staff. Many of these features can be offloaded on to the cloud provider. A comprehensive analysis was completed that showed the current annual cost of operating is more expensive than using cloud computing resources. Lastly, the regulatory framework does not explicitly address AI or autonomous control. Currently, the NRC and other regulatory bodies are evaluating providing guidance to address gaps rather than new regulations to address the use of AI and ML. But since many of the AI applications are focused on non-safety related applications, such as balance-of-plant components, they will likely have little or no regulatory restrictions or necessary approvals. Demonstrating how AI can improve maintenance and operation of these non-safety related systems seems like the likely path forward for implementing AI and cloud computing resources inside nuclear power plants (NPPs).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

Energy-Transit Nexus Tools for Bus Fleet Electrification (NEXTBUS)

NEXTBUS is an open-source software project that integrates NLR's bus energy modeling and simulation tools with multi-objective optimization for fleet operations. NLR is collaborating with a transit technology startup, ReVolt, to commercialize these capabilities by deploying NEXTBUS in ReVolt's software platform. The goal is to manage the added complexities of running a heterogeneous fleet, encompassing battery electric and diesel buses, across a large, multi-depot transit network.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2026

Fleet-Level Fuel Impact of Hybrid-Electric Aircraft in United States

Here, this paper examines the impact of two potential solutions for increasing fuel efficiency and reducing emissions in commercial aviation: hybrid-electric propulsion and the use of drop-in synthetic aviation fuels (SAFs). The authors modeled three representative aircraft employed in the U.S. domestic market: a 70-seat regional turboprop, a 100-seat airliner, and a 180-seat airliner. These aircraft were retrofitted with hybrid-electric propulsion systems that integrate batteries and electric motors to provide additional torque to the propeller or fan. The authors explored various technological scenarios involving different battery specific energies, electric motor specific powers, and other relevant parameters. Flight performance models were used to analyze the range–payload capabilities of these new hybrid-electric aircraft and to compare them with their conventional counterparts. Subsequently, the authors virtually deployed the hybrid-electric aircraft on 2019 U.S. domestic commercial flights to assess the types and lengths of flights that could be serviced by this new fleet. We then compared the resulting fuel consumption, energy use, and emissions with those of a conventional fleet using a combination of jet fuel and SAF.

SAF↗

DOE OSTI2023

Predictive Analytics for Hydropower Fleet Intelligence

A primary challenge in hydropower industry is the ability to maintain cost-competitiveness, reliability, and security of hydropower assets through evolving power system contexts and aging of the fleet. Maintaining cost-effective and reliable operations under these conditions is expected to require new modernization and maintenance paradigms for changing contexts. Changes in existing practices for O&M will require an understanding of the current state and health of hydropower assets, and the impact of changing paradigms on asset health and reliability. The Hydropower Fleet Intelligence project is developing and evaluating standardized methodologies and analysis tools for data-driven asset reliability and management technologies for hydropower, leading to eventual predictive maintenance planning, repair/replacement decision making, and asset-reliability and cost-optimized operations. A key question is the feasibility of using existing data sets at hydropower facilities to perform assessments of asset reliability. This document uses data from hydropower facilities to assess the potential for using available analytics methods for asset reliability estimates. In addition to reliability assessments, the feasibility of using existing analytics techniques for several other potential applications is discussed. Finally, a case study that a data-driven model is trained to learn nominal operations via vibration data from an asset of a certain plant, and then utilized to identify anomalies on a similar asset from a different plant, highlighting the generic use of proposed Prognostics and Health Management (PHM) approaches.

Yucesan, Yigit↗

DOE OSTI2025

Fleet-Level Energy and Emissions Analysis of the US Off-Road Sector with VISION: Off-Road

In the United States (US), the off-road sector (i.e., agriculture, construction, etc.) contributes to approximately 10% of the country’s transportation greenhouse gas (GHG) emissions, similar to the aviation sector. The off-road sector is extremely diverse; as the EPA MOVES model classifies it into 11 sub-sectors, which include 85 different types of equipment. These equipment types have horsepower ranging from 1 to greater than 3000 and have very different utilization, which makes decarbonization a complex endeavor. To address this, Argonne’s on-road vehicle fleet model, VISION, has been expanded to the off-road sector. The GHG emission factors for several energy carriers (biofuels, electricity, and hydrogen) have been incorporated from Argonne’s GREET model for a sector-wide well-to-wheel (WTW) GHG emissions analysis of the present and future fleet. Several technology adoption and energy decarbonization scenarios were modeled to better understand the appropriate actions required to drive towards net-zero emissions of the off-road sector. Results show that WTW decarbonization up to 67% can be achieved from 2023 to 2050 in a business-as-usual scenario. But with aggressive sales increases of electric and hydrogen powertrains, WTW decarbonization up to 77% can be achieved, which can further increase to 85% if electricity production is aggressively decarbonized by 2035.

lifecycle↗

NASA NTRS1987

NASA space transportation plans and roles of a mixed fleet

An account is given of the results of a September, 1987 NASA 'mixed fleet' launching resources/scheduling study that predicated capability projections on a fleet of available ELVs. The launch capability projections extended as far as 1995, and in their later phases encompassed the resumption of Space Shuttle operations and the availability of Orbital Maneuvering Vehicle, which could accomplish such things as the reboosting of the Hubble Space Telescope in 1991, and even the Shuttle-Derived Vehicle, of which two distinct concepts are presently being considered; both would heavily rely on Space Shuttle hardware, but would be unmanned.

Branscome, Darrell R.↗

NASA NTRS1990

Launch site integration for mixed fleet operations

Launch site impacts and integration planning issues are presented to support launch operations for a mixed vehicle fleet (manned and cargo). Proposed ground systems and launch site configurations are described. Prelaunch processing scenarios and schedules are developed for candidate launch vehicles. Earth-to-orbit (ETO) vehicle architectures are presented to meet future launch requirements, including the Space Exploration Initiative (SEI). Flight vehicle design recommendations to enhance launch processing are discussed. The significance of operational designs for future launch vehicles is shown to be a critical factor in planning for mixed fleet launch site operations.

Scott, L. P.↗

NASA NTRS1991

Options in the global change fleet architecture provided by the presence of an EOS-A and -B

The baseline architecture of the Global Change Technology Initiative (GCTI) fleet was established by selecting and designing spacecraft and instruments to meet the science requirements developed under the task 1 effort. While attempting to meet the temporal sampling portion of the science requirements, no consideration was given to the presence of the proposed Earth Observing System (EOS) Spacecraft that would be making many of the same measurements with many of the same instruments. After establishing the GCTI baseline independent of the EOS Spacecraft; however, it is now prudent to examine the impact of the presence of the EOS Spacecraft on the GCTI fleet. A small scope, GCTI study supplement was accomplished to assess the impact. The content and results of the supplementary study are presented.

Hypes, Warren D.↗

NASA NTRS1991

Lessons from cross-fleet/cross-airline observations - Evaluating the impact of CRM/LOFT training

A review is presented of the crew resource management/line oriented flight training (CRM/LOFT) program to help determine the level of standardization across fleets and airlines in the critical area of evaluating crew behavior and performance. One of the goals of the project is to verify that check airmen and LOFT instructors within organizations are evaluating CRM issues consistently and that differences observed between fleets are not a function of idiosyncracies on the part of observers. Attention is given to the research tools for crew evaluation.

Butler, Roy E.↗

NASA NTRS1989

Optimal selection of space transportation fleet to meet multi-mission space program needs

A space program that spans several decades will be comprised of a collection of missions such as low earth orbital space station, a polar platform, geosynchronous space station, lunar base, Mars astronaut mission, and Mars base. The optimal selection of a fleet of several recoverable and expendable launch vehicles, upper stages, and interplanetary spacecraft necessary to logistically establish and support these space missions can be examined by means of a linear integer programming optimization model. Such a selection must be made because the economies of scale which comes from producing large quantities of a few standard vehicle types, rather than many, will be needed to provide learning curve effects to reduce the overall cost of space transportation if these future missions are to be affordable. Optimization model inputs come from data and from vehicle designs. Each launch vehicle currently in existence has a launch history, giving rise to statistical estimates of launch reliability. For future, not-yet-developed launch vehicles, theoretical reliabilities corresponding to the maturity of the launch vehicles' technology and the degree of design redundancy must be estimated. Also, each such launch vehicle has a certain historical or estimated development cost, tooling cost, and a variable cost. The cost of a launch used in this paper includes the variable cost plus an amortized portion of the fixed and development costs. The integer linear programming model will have several constraint equations based on assumptions of mission mass requirements, volume requirements, and number of astronauts needed. The model will minimize launch vehicle logistic support cost and will select the most desirable launch vehicle fleet.

Morgenthaler, George W.↗

NASA NTRS2002

Mission Engineering of a Rapid Cycle Spacecraft Logistics Fleet

The requirement for logistics re-supply of the International Space Station has provided a unique opportunity for engineering the implementation of NASA's first dedicated pressurized logistics carrier fleet. The NASA fleet is comprised of three Multi-Purpose Logistics Modules (MPLM) provided to NASA by the Italian Space Agency in return for operations time aboard the International Space Station. Marshall Space Flight Center was responsible for oversight of the hardware development from preliminary design through acceptance of the third flight unit, and currently manages the flight hardware sustaining engineering and mission engineering activities. The actual MPLM Mission began prior to NASA acceptance of the first flight unit in 1999 and will continue until the de-commission of the International Space Station that is planned for 20xx. Mission engineering of the MPLM program requires a broad focus on three distinct yet inter-related operations processes: pre-flight, flight operations, and post-flight turn-around. Within each primary area exist several complex subsets of distinct and inter-related activities. Pre-flight processing includes the evaluation of carrier hardware readiness for space flight. This includes integration of payload into the carrier, integration of the carrier into the launch vehicle, and integration of the carrier onto the orbital platform. Flight operations include the actual carrier operations during flight and any required real-time ground support. Post-flight processing includes de-integration of the carrier hardware from the launch vehicle, de-integration of the payload, and preparation for returning the carrier to pre-flight staging. Typical space operations are engineered around the requirements and objectives of a dedicated mission on a dedicated operational platform (i.e. Launch or Orbiting Vehicle). The MPLM, however, has expanded this envelope by requiring operations with both vehicles during flight as well as pre-launch and post-landing operations. These unique requirements combined with a success-oriented schedule of four flights within a ten-month period have provided numerous opportunities for understanding and improving operations processes. Furthermore, it has increased the knowledge base of future Payload Carrier and Launch Vehicle hardware and requirement developments. Discussion of the process flows and target areas for process improvement are provided in the subject paper. Special emphasis is also placed on supplying guidelines for hardware development. The combination of process knowledge and hardware development knowledge will provide a comprehensive overview for future vehicle developments as related to integration and transportation of payloads.

Holladay, Jon↗

NASA NTRS2012

Aircraft Anomaly Detection Using Performance Models Trained on Fleet Data

This paper describes an application of data mining technology called Distributed Fleet Monitoring (DFM) to Flight Operational Quality Assurance (FOQA) data collected from a fleet of commercial aircraft. DFM transforms the data into aircraft performance models, flight-to-flight trends, and individual flight anomalies by fitting a multi-level regression model to the data. The model represents aircraft flight performance and takes into account fixed effects: flight-to-flight and vehicle-to-vehicle variability. The regression parameters include aerodynamic coefficients and other aircraft performance parameters that are usually identified by aircraft manufacturers in flight tests. Using DFM, the multi-terabyte FOQA data set with half-million flights was processed in a few hours. The anomalies found include wrong values of competed variables, (e.g., aircraft weight), sensor failures and baises, failures, biases, and trends in flight actuators. These anomalies were missed by the existing airline monitoring of FOQA data exceedances.

Gorinevsky, Dimitry↗