SEARCH · Engineering Papers

Results for “customize”

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

SourceResearch connectionFrom yearThrough year

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

At least 901 records · Page 50

All sources NASA NTRS DOE OSTI

NASA NTRS2024

Decision Space Modeling: Trade Space Ontology

As the National Aeronautics and Space Administration (NASA) works to develop a crewed Moon to Mars Architecture, it is dealing with a large decision space consisting of the overlay of human exploration architectures for both the Moon and for Mars. Efforts are underway to enable reasoning, analysis, and deliberation on this decision space. A critical first step is to develop a model of the decision space, which will then allow for various methods and techniques to be applied in support of the larger architecture decision-making process. The Trade Space Ontology consists of a set of terminologies and relations (an ontology) and a MagicDraw resource that enables documentation of decisions and alternatives. It also provides a means by which decisions and alternatives can be traced to other Systems Engineering artifacts. For documenting alternatives, the Trade Space Ontology adapts the Morphological Matrix methodology to The Systems Modeling Language (SysML) through a profile; custom diagrams are also implemented to simplify the profile's use. With the profile and custom diagrams, system architects can specify options for architecture attributes, as well as compatibility between them, in a compact visual format. While the approach shares similarities to a trade tree, the emphasis at this stage is less on enumerating specific combinations of options and instead on specifying the options and their compatibility. Enumeration of alternatives is performed by an external analysis that operates on an output file from a model constructed using the Trade Space Ontology. For decisions, the Trade Space Ontology provides a way to model generic precedence relationships as well as documenting inputs and outputs. These may include what alternatives, criteria, and rationale are understood to be relevant for each decision. Importantly, the decision-making side of the Trade Space Ontology is defined at a more general level, such that it can be adapted to the specific terms in use by projects and programs at NASA. However, this adaptability also means that less capability is provided ``out-of-the-box'' from installation. Currently the resource includes plugin functionality to enumerate paths through generic precedence relationships between decisions and to export these paths to a spreadsheet. Custom dependency stereotypes are included in the profile to indicate the cross-cutting relationships between the trade space and the architecture decisions, providing a means to map which parts of the trade space enumerate alternatives for a decision, and to identify how the output of a decision may modify the trade space through pruning or down-selection. While the motivating use case for this resource is in human exploration architectures, the broad applicability of the Morphological Matrix methodology indicates that the Trade Space Ontology should also be useful for other activities and tasks at the agency.

Trade Tree↗

NASA NTRSDate not supplied

LS-DYNA User-Defined Internal Ballistic Modeling

One of the challenges in modeling deflagration of solid propellants with LS-DYNA is its limited capability, which is mostly applicable to airbag systems that use gaseous nitrogen generated by burning sodium azide. To overcome this limitation and enable the modeling of custom propellant grains with specific geometries, perforations, surface inhibitors, impetus, burn rates, and co-volumes, a user-defined burn model must be defined. In this study, a custom internal ballistic analysis code is integrated into LS-DYNA to simulate kinematic systems driven by pyro-mechanical devices such as pyro pushers, cutters, thrusters, separations bolts, ejection seat catapults, etc. Step-by-step guidance is provided on implementing a user-defined loading subroutine and the requirements for compiling a custom LS-DYNA executable along with a simple pyro thruster example.

pyrotechnics↗

DOE OSTI2017

Identifying Potential Markets for Behind-the-Meter Battery Energy Storage: A Survey of U.S. Demand Charges

This paper presents the first publicly available comprehensive survey of the magnitude of demand charges for commercial customers across the United States -- a key predictor of the financial performance of behind-the-meter battery storage systems. Notably, the analysis estimates that there are nearly 5 million commercial customers in the United States who can subscribe to retail electricity tariffs that have demand charges in excess of $15 per kilowatt (kW), over a quarter of the 18 million commercial customers in total in the United States. While the economic viability of installing battery energy storage must be determined on a case-by-case basis, high demand charges are often cited as a critical factor in battery project economics. Increasing use of demand charges in utility tariffs and anticipated future declines in storage costs will only serve to unlock additional markets and strengthen existing ones.

14 SOLAR ENERGY↗

DOE OSTI2017

Optimal Sizing of Energy Storage for Community Microgrids Considering Building Thermal Dynamics

This paper proposes an optimization model for the optimal sizing of energy storage in community microgrids considering the building thermal dynamics and customer comfort preference. The proposed model minimizes the annualized cost of the community microgrid, including energy storage investment, purchased energy cost, demand charge, energy storage degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation. The decision variables are the power and energy capacity of invested energy storage. In particular, we assume the heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently by the microgrid central controller while maintaining the indoor temperature in the comfort range set by customers. For this purpose, the detailed thermal dynamic characteristics of buildings have been integrated into the optimization model. Numerical simulation shows significant cost reduction by the proposed model. The impacts of various costs on the optimal solution are investigated by sensitivity analysis.

Liu, Guodong↗

DOE OSTI2017

The Geography of Green Power

Green power refers to the voluntary purchase of renewable electricity by retail electricity customers. Green power is unlike compliance-based renewable energy procurement imposed by law or regulation. In 2016, over six million customers procured about 95 million megawatt-hours (MWh) of green power in the United States, which represents about 28% of all U.S. renewable energy sales, excluding large hydropower. In this fact sheet, we use available data to illustrate the geography of green power demand (in terms of number of customers) and supply (in terms of MWh of generation) by state.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2017

Stochastic Dual Algorithm for Voltage Regulation in Distribution Networks with Discrete Loads: Preprint

This paper considers distribution networks with distributed energy resources and discrete-rate loads, and designs an incentive-based algorithm that allows the network operator and the customers to pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. Four major challenges include: (1) the non-convexity from discrete decision variables, (2) the non-convexity due to a Stackelberg game structure, (3) unavailable private information from customers, and (4) different update frequency from two types of devices. In this paper, we first make convex relaxation for discrete variables, then reformulate the non-convex structure into a convex optimization problem together with pricing/reward signal design, and propose a distributed stochastic dual algorithm for solving the reformulated problem while restoring feasible power rates for discrete devices. By doing so, we are able to statistically achieve the solution of the reformulated problem without exposure of any private information from customers. Stability of the proposed schemes is analytically established and numerically corroborated.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

Semiconductor Reliability Testing Data Management

iT2 Technologies is a startup developing analytical software and creating automated workflow environment in the area of big data in IC reliability. The main beneficiaries of the iT2 software will be the semiconductor companies as they will see significant savings in terms of time and cost. They will be able to efficiently perform the analysis of large amount of reliability data. A better standard of reliability and quality will also lead to the improvement in public safety in consumer, automotive, medical, and military applications. Smarter and thorough testing will reduce the risk of faulty hardware getting into the hands of the end users. The software is being developed and designed within the United States and will help keep the prominence of US in the cutting edge of high tech space. iT2 is establishing strong relations with its potential customers thanks to its key players being involved in this industry for the past several years and, thus, having a deep understanding of the market. The target clients will be all major semiconductor suppliers such as Intel, Qualcomm, Texas Instruments, OnSemi, and Broadcom and their customers including Apple, Cisco, IBM, HP, and Dell. The iT2 software will be used in a business-to-business environment for sharing engineering data and communicating results between these two classes of customers - some of which are participating in the beta testing of the iT2 software.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2018

Solar Buyer's Markets: Unlocking Lower Photovoltaic and Battery Prices on Online Quote Platforms

Previous NREL research shows that solar photovoltaic (PV) customers tend to obtain lower installation quote prices on online quote platforms. In new research reported in Solar Buyer's Markets: Unlocking Lower Photovoltaic and Battery Prices on Online Quote Platforms, we corroborate those results using data from the Pick My Solar quote platform. Furthermore, for the first time, we evaluate quote prices for batteries on online quote platforms. Given that few customers currently use quote platforms, we discuss various pathways to increase use of online quote platforms, including developing strategic partnerships, building customer trust, increasing market transparency, and providing quality guarantees.

14 SOLAR ENERGY↗

DOE OSTI2018

The Geography of Green Power (2017 Data)

Green power refers to the voluntary purchase of renewable electricity by retail electricity customers, as opposed to renewable energy procurement to comply with mandates imposed by law or regulation. In 2017, over five million customers procured about 113 million megawatt-hours (MWh) of green power in the United States, which represents about 27% of all U.S. renewable energy sales, excluding large hydropower. In this fact sheet, we use available data to illustrate the geography of green power demand (in terms of number of customers) and supply (in terms of MWh of generation) by state.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2018

Managing Through Continuous Improvement: If it doesn’t challenge you, it won’t change you

The past 24 months has been one of non-stop continuous improvement – every month, every week, every day, and every hour. It has been filled with continuously re-examining and challenging business systems, work processes, and legacy culture. The journey was difficult, but well worth it. It began by examining the existing conditions in each organization and building the case for change. When we stepped back and looked at our processes, systems, tools, and performance objectively, we realized we were struggling with frequent organizational, resource, and schedule conflicts, work processes that were not well-defined or expert based, project delays were common, management methods were predominantly reactive, advanced planning was limited to the near-term, no integration in scheduling across organizations, limited to no performance metrics to measure and manage performance, and internal and external customers did not feel like we were meeting their quality and performance expectations. It was a wake-up call. Change began at the top with a change leadership with where a new vision, expectations, and commitment were established. Leaving no stone left unturned, every aspect of the business was challenged which opened up communication and exposed the gaps. This was done in a ‘safe’ environment allowing for honest and solution-oriented discussion and action. The leadership team committed to managing through continuous improvement. The organizational structure was realigned to better align scope, responsibilities, execution, and customer focus. Visibility and transparency became the norm as higher levels of leadership and supporting organizations were invited to be part of regular strategy meetings and partnership discussion, effectively opening up the dialogue. This required a tremendous amount of trust and faith in a short period of time. Health assessments were conducted on each organization with specific lines of inquiry. These self-assessments helped to identify better define the scope of the organization and where targeted improvements were needed. Frequent organizational reviews were implemented to answer three fundamental questions: 1) What is your organization paid to do (scope)?, 2) How does your organization, or you, demonstrate that you are doing the job effectively?, and 3) What are you doing to improve your performance? To answer the first question, leaders defined the scope of the organization. Leaders were required to provide a path forward, with specific actions, where performance was not at expected levels internally at first and then from the stakeholders. Where business processes were not clearly understood, process maps were developed to provide this clarity for both those performing the work and those utilizing the process – the customers. To help answer the second question, numerous automated or semi-automated real-time, dynamic performance metrics were developed and implement to help leaders gain the visibility and demonstrate performance in six areas of operational excellence: safety, security, quality, effectiveness, productivity, and sustainability. Analysis of the performance provided windows of transparency and trends of work performance, work delays, cycle times, utilization, and much more that revealed many areas of improvement that were either not visible or desired to be visible. At the same time, they provided real-time progress which generated initial performance improvements by just beginning to measure. To address the third question, where systems did not support effectiveness of an existing or new process, then systems and tools were developed and implemented to drive the right behaviors and reinforce the processes. Tools and metrics were one of the major catalysts for culture shift and change. Risk assessments were leveraged into continuous improvement strategies, plans, and schedules. Targeted initiatives were identified and performed. Change and improvement was not, and is not, without significant and common challenges including limited/fixed budgets, resource availability, data access, natural resistance to change, and numerous other reasons or excuses – we called them ‘off-ramps’ and began to close them one-by-one. The results and outputs were significant and impactful in each organization and across the business with increased productivity, efficiency, visibility, accountability, management, and performance. Stakeholder satisfaction also increased. Cost and time savings allowed to more continuous improvement efforts to be performed. The effort clearly provided clear and measurable return on investment and value. Efforts that once seemed impossible, not feasible, or not achievable were performed. Decades-long issues were solved. ‘Impossible things are simply those which so far have never been done’ said Elbert Hubbard. So what will the next year be for you and your organization? Are you satisfied with the ‘same ‘ol, same ‘ol?’ Will you fall into the complacency trap and believe that change is too difficult, too expensive, and not necessary (or any number of possible excuses) or will you make this year your year or continuous improvement (and every year thereafter…)? Remember – what you do today can improve all your tomorrows’ (Ralph Marston).

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2018

A Demonstration of Blockchain-Based Energy Transactions between Laboratory Test Homes

Current electricity payment mechanisms and accessible value streams are inhibiting innovation in energy markets that stand to enhance grid security and resilience and enable increased integration of distributed energy resources (DER). In the era of near-instantaneous settlement times brought about by blockchain technology, the unidirectional (customer --> utility) monthly settlement of the incumbent infrastructure appears arcane. The lack of an effective market interface for DER results in fewer value streams for customers, underutilized assets for utilities, and reduced opportunities for vendors/manufacturers. A secure, real-time energy market enabled by blockchain technology presents a transformative opportunity to unlock innovations in DER and integrated controls. Blockchain technology provides a compelling pathway to energy market evolution, however there are several challenges to be addressed, including: simultaneous exchange of currency and energy commodities, ensuring customer privacy, incorporating transmission/distribution losses in energy trading contracts. To address the first of these - commodity tracking - we have established peer-to-peer energy transactions between two test homes at the National Renewable Energy Laboratory. Our research architecture demonstrates integration with high-fidelity metering for commodity tracking, and integration with NREL's foresee(TM) controls platform which orchestrates building loads and DER to execute the energy contract. The digital currency Dash, which supports enhanced privacy features and instant transactions, is employed for transaction settlement. BlockCypher's blockchain-agnostic web services are used to provide future flexibility in integrating various payment and contract options. In this paper we describe the technology, the research methodology employed, and present results on transaction execution speed and compliance with energy trading contracts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Enterprise: a reduced-scale, flexible fuel, single-cylinder crosshead marine diesel research engine

A custom-built 1/10 scale, flexible-fuel, single-cylinder crosshead marine diesel research engine, dubbed the Enterprise, was designed and built as a platform for conducting marine lubricant research. The engine design was focused on maintaining lubricant boundary conditions similar those of full-scale engines. The Enterprise has a rated speed of 625 rpm to match the linear mean piston speed of full-scale marine engines with the reduced stroke and is capable of 18 bar brake mean effective pressure (BMEP). A high-swirl, uniflow-scavenged, two-stroke combustion system was designed to operate on either distillate diesel or heavy fuel oil (HFO). A hydraulic electronic unit injector (HEUI) fuel injection system with two injectors having customized three-hole nozzles provides fueling and is driven by the MAHLE Flexible ECU (MFE). Intake air boost is provided using a variable speed industrial air compressor along with closed-loop electronically controlled pressure regulation. Exhaust backpressure is also controlled electronically using an electro-pneumatic butterfly valve. A customized, miniaturized Hans Jensen Lubetronic cylinder lubrication system, which is capable of delivering 0.88 mg of cylinder oil per lubricator per injection to the ring pack at up to the maximum engine overspeed rating of 656 rpm, was commissioned for the Enterprise. Four independently temperature-controlled cooling zones are used to provide control of the liner temperature profile. The four coolant zones as well as the system oil and cylinder oil supplies are all controlled within 1°C for consistent thermal boundary conditions. The engine is instrumented with an in-cylinder pressure transducer as well as an inline torque transducer and numerous process temperature and pressure measurements to allow for detailed thermodynamic efficiency analysis, and experimental facilities allow for precise measurement of liner wear and characterization of deposits on the piston and rings. A radio telemetry system from IR Telemetrics is used to measure piston crown temperatures during engine operation. Engine design considerations and experimental facilities are described in detail, along with the results of a study investigating the impact of both system oil and cylinder oil viscosity on friction and efficiency. A test matrix was designed to compare base stock chemistries and viscosities for both system and cylinder oils. Experiments were completed using a fuel economy test protocol that was defined, consisting of repeating six speed/load operating conditions. An automated dynamometer control system was implemented to ensure repeatability of the test procedure. Preliminary testing indicated that the coolant, oil, and exhaust temperatures reach a steady state within 5 minutes of changing operating conditions. The system oil viscosity was found to have a significant impact on friction, with a reduction in viscosity from SAE 30 to SAE 20 resulting in over 6% reduction in friction mean effective pressure (FMEP) and over a 2% reduction in brake-specific fuel consumption (BSFC). Chemistry effects were also evident in the system and cylinder oils. Repeatability comparisons between the individual repetitions of each operating condition were used to ensure that results are statistically valid. For the initial cylinder oil viscosity experiments, observed changes were within the established/normal repeatability; ongoing experiments will determine whether improvements in boundary condition control will enable cylinder friction changes of this magnitude to be measured on this engine platform.

Kaul, Brian↗

DOE OSTI2020

Cooperative Load Scheduling for Multiple Aggregators Using Hierarchical ADMM

Demand response (DR) serves an important role in improving the efficiency and stability of power systems. In recent years, with advances in communication and smart device technologies, many aggregators have emerged to facilitate end customer participation in DR programs. These aggregators, equipped with customized optimal control algorithms, are capable of providing various grid services. Among them is load scheduling during DR events, namely following a load signal provided by the utility company while minimizing overall customer discomfort. However, as the number of aggregators keeps increasing, it becomes challenging for utility companies to conduct load scheduling for multiple aggregators and generate reference signals for each of them. This paper proposes an optimization framework using hierarchical alternating direction method of multipliers (H-ADMM) to optimally generate load following signals for multiple aggregators. Under this framework, utility and multiple aggregators work in a cooperative manner, aiming at minimizing an overall system cost from different levels of the power system hierarchy, while protecting user privacy. A case study has been conducted in a system with multiple aggregators, based on control of HVAC loads. Experimental results validate the effectiveness of the proposed algorithm.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Cooperative Load Scheduling for Multiple Aggregators Using Hierarchical ADMM: Preprint

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Smart-DS: Synthetic Models for Advanced, Realistic Testing: Distribution Systems and Scenarios

The explosion of new ideas for distributed energy resources and advanced distribution grid algorithms faces a critical challenge: how can one effectively develop and evaluate these breakthrough technologies without an adequate set of power systems network, load, and resource data to test against? Today's open test systems, particularly for distribution systems, are tiny and incomplete; and though with enough effort, obtaining utility data under NDA can overcome scale challenges, the results can't be openly shared, preventing fair comparison. The Smart-DS project-led by NREL in partnership with MIT, Universidad Pontificia Comillas, CYME, and EDD-is working to overcome this gap by generating multiple large-scale, open, synthetic, distribution systems that are realistic but not real. These datasets go beyond a single medium voltage feeder (~1000 customers) to cover entire metropolitan areas and their surrounds with up to hundreds of feeders and millions of customers, complete with low voltage customer connections and high voltage sub-transmission. This scale allows adequate testing and analysis of not just local controls and advanced DERs, but also multiple substation interactions, optimized switching, full-scale distribution-OPF, and more. To accompany these datasets, the project is also building a rich set of scenario generation tools that can be used for distribution and transmission systems alike. This includes automated, spatially aware access to world-class, high-resolution solar, wind, and weather data: forward looking generation mixes: and highly configurable DER, load, climate, outage, control-scheme, and other scenarios. We will also highlight DiTTo, an exciting open-source, multi-way distribution dataset transformation tool for many-to-many format translation with scenario, merge/split, and many other manipulation capabilities.

DERs↗

DOE OSTI2020

Who Controls Energy in the Smart Home? A Multidisciplinary Taxonomy

Advances in technology have begun to open new opportunities for behavior-based and technical approaches to managing residential energy use and meet sustainability-related objectives. Visions of the future predict homes with smart technologies delivering enhanced comfort and cost savings to residents; utility-partners who can remotely optimize energy resources to meet grid needs; and occupants who play more active roles in the energy system supported by advanced information communication technologies. Each of these scenarios implies augmented control over home energy use, yet uncertainties remain regarding which ones will deliver the greatest grid benefits and services to customers in a given situation. These scenarios also raise broader questions regarding customer agency and the relationship between customers and third parties moving forward. While both the provision of information to spur behavior change and automated technologies theoretically enhance control over energy use in the built environment, these strategies are not often studied from an integrated perspective. Seeking to address this gap and develop a deeper understanding of the evolving paradigm of control over home energy use, this paper presents a taxonomy to evaluate perspectives from public policy (ex. demand-side management), technological innovation (automated controls), and user-agency (ex. the role of behavior change) on approaches to managing home energy use. We draw on theoretical and empirical evidence from across disciplines to detail the dimensions and implications of deploying programs that incorporate various levels of control and anticipate such a taxonomy will help holistically map out and evaluate tradeoffs between different approaches to demand-side management moving forward.

McIlvennie, Claire↗

DOE OSTI2021

On the Use of Smart Meter Data to Estimate the Voltage Magnitude on the Primary Side of Distribution Service Transformers: Preprint

This paper develops a novel method to estimate the voltage magnitude on the primary side of distribution service transformers. The proposed method relies exclusively on smart meters, and therefore it is fully data-driven. This is an important feature because electric utilities have detailed models of only the primary network--that is, the network between the distribution substation and the primary side of service transformers that are installed closer to end-customer sites. The network that connects the secondary side of service transformers to end-customer sites, referred to as the secondary network, is simply represented by a lumped load. For each secondary network, the proposed method uses data acquired from only 2 smart meters: the closest and the farthest--in the sense of electrical distance--from the service transformer. As a reference to this feature, the proposed method is named SM2Vp. To our knowledge, this is the first time a method is shown to provide actionable information for real-time operation and control of power distribution grids using only two smart meters per secondary network. This is important because utilities have experienced barriers in managing and using large data sets for real-time operation and control. SM2Vp is primarily intended to provide pseudo-measurements for distribution system state estimation, but it can also be used directly for voltage control schemes. The performance of SM2Vp is demonstrated by numerical simulations carried out on three secondary network synthetic models and by using field data provided by a utility partner serving customers in southwestern California. A maximum relative error of approximately 3.9% or less is observed for the primary voltage magnitude estimates in all numerical experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Smart Semi-Supervised Accumulation of Large Repositories for Industrial Control Systems Device Information

Industrial Control Systems device manufacturers frequently add new features to improve their product performance. Oftentimes, these changes are mainly vendor-driven initiatives, and customers may not be aware of the full impact of these new capabilities on their cybersecurity posture. In the energy sector, this can lead to considerable dissonance between vendor-provided cybersecurity claims and a customer’s responsibility for Operation Technology cybersecurity compliance. Thus, the resulting dynamic verification burden is shifted towards the customer and may pose a significant cybersecurity risk to the energy sector landscape. We found that there is very limited research into cybersecurity auditing for Operational Technology. However, a solution is needed for vetting the vendor-supplied feature claims and their adherence to cybersecurity requirements and standards. We are presently engaged in an effort to develop such a system. This paper demonstrates one vital aspect of this effort in proposing an end-to-end framework to accumulate a large repository of ICS device information for this vetting system, curate the dataset, and conduct extensive processing. This framework is designed to use web scraping, data analytics and Natural Language Processing (NLP) techniques to identify vendor websites, automate the collection of website-accessible documents and automatically derive metadata from them for identification of product documents relevant to the repository. We have found that this automated approach to vendor identification, document extraction into a product repository, and NLP pre-processing is unique and has not been previously presented in the literature. The preliminary work shows that this is feasible and can produce reliable results with minimum supervision. Future work will be built upon this foundation in order to achieve semi-supervised vetting of device technical information – a vital capability for ensuring that vendor-claimed device cybersecurity capabilities match industry requirements.

Ameri, Kimia↗