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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.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Connected Loads – Grid Connected Appliances: Deployment IoT Solution for Fault Detection and Diagnostics

As one of the most energy-intensive end-uses in the commercial buildings sector, supermarkets consume around 50 kWh/ft 2 ( or 537.6 kWh/m 2 ) of electricity annually, or more than 2 million kWh of electricity per year for a typical store. The biggest consumer of energy in a supermarket is its refrigeration system, which accounts for 40–60% of its total electricity usage and is equivalent to about 2–3% of the total energy consumed by commercial buildings in United States, or around 0.5 quadrillion Btu (or 0.53 quadrillion KJ). Also, the supermarket refrigeration system is one of the biggest consumers of refrigerants. Current supermarket refrigeration systems rely on high global warming potential hydrofluorocarbon refrigerants. Reducing refrigerant usage or using environment friendly alternatives can result in significant climate benefits. Transcritical CO2 refrigeration systems have attracted more attention in recent years because of their zero-carbon emission advantages compared with traditional refrigerants. These systems are widely used in commercial buildings such as supermarkets. The refrigeration system can also be adapted to handle flexible building loads and be integrated into grid response transactive control to balance the supply and demand of the electric grid. Even minor improvements in the efficiency and operational reliability of supermarket refrigeration systems can create significant value in terms of saving energy, improving food quality, protecting the environment, reducing carbon footprint, and enhancing electric grid resilience. For decarbonization, the new administration has set a target to reduce greenhouse gas emissions by 50– 52% by 2030 and targeting a carbon-neutral economy by 2050. For electrification, the goal is to achieve 100% clean electricity by 2035. Such decarbonization and electrification in the building sector require that energy consumption in buildings be reduced significantly. Therefore, the building sector must continuously adopt new technologies to achieve its energy and carbon emission goals. One of the most fundamental technologies is the Internet of Things (IoT). IoT has proven to be an effective solution for the building domain, including building information/energy modeling, smart buildings, etc. Although much progress has been made in the development of IoT-based building energy systems, there is still a lack of reliable, scalable, and affordable IoT-based automated fault and degradation diagnostics (AFDDs) solutions. Such solutions would enable deployment of advanced algorithms into real systems to archive the projected energy benefits. This study reviews existing IoT solutions developed for building energy– related application and developed a simple but effective AFDD IoT deployment solution, including developing a suitable IoT architecture and conducting easy and scalable deployment by leveraging a common cloud-based IoT service.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Framework for Large-scale Implementation of Wholesale-Retail Transactive Control Mechanism

Transactive energy is a control technique that uses market mechanisms to achieve desired control objectives. Several simulation studies and field demonstrations were carried out in recent years, but all focused on small scale systems and purpose-built simplified models which are not always capable of pointing out all the advantages and shortcomings of transac- tive energy methods. This work describes a co-simulation framework built on a hierarchical control architecture that allows for conducting studies of the impacts of a very large-scale deployment of transactive energy. The hierarchical transactive control architecture adopted in this work helps with alleviating computation and communication burden to facilitate a more effective large scale real-time market operation among device level resources and the system level operators. The co-simulation framework is evaluated an integrated power sys- tem model of unprecedented scale composed of the Western Electricity Coordination Council (WECC) transmission system with tens of thousands of distribution systems deployed with flexible device-level distributed energy resources (DERs) using off-the-shelf simulators.

Transactive energy, market-based controls, DER int↗
DOE OSTI2022

Capacity Markets for Transactive Energy Systems

Capacity markets provide important incentives for resource adequacy in electricity markets and may become more important for providing sufficient revenue and generation capacity with changes to energy market prices driven by increasing levels of zero marginal cost resources. However, current capacity market designs also have important shortfalls that may limit the benefits they can provide to the future grid. Current capacity markets are primarily designed for participation from conventional thermal generators, but markets are evolving with increasing levels of variable renewable energy resources. However, further reforms may be necessary to enable more participation from DERs and demand-side resources. To understand the benefits and shortfalls of current capacity market design, we review the historical reasons electricity markets have needed capacity markets or capacity payments for resource adequacy, and how current capacity market designs may create challenges for incorporating increasing levels of DERs and demand-side resources. We then consider how transactive systems, which allow the coordination of bids and offers for DERs and demand-side resources through a market interaction approach, administered by a Distribution System Operator (DSO), can address traditional resource adequacy problems due to inelastic consumer demand. We also consider the need for a DSO-level capacity market in helping to meet resource adequacy, reliability, and other electricity market objectives. We find that because the missing money in electricity markets is largely driven by incentives to meet resource adequacy goals, and the bulk grid would always supply power to the DSO, that resource adequacy is unlikely to be a determining factor in the need for a DSO-level capacity market. Many current reliability problems could also be addressed by the incorporation of more flexible demand enabled with transactive energy systems. However, other DSO objectives, including resilience, reactive power, voltage control, environmental policies, and energy equity could lead to specific challenges that could be aided by a DSO-level capacity market. We consider the possibility of a DSO-level capacity market in addressing these challenges as well as its potential role in coordinating with the Independent System Operator (ISO) who operates the wholesale market. We conclude with suggestions for future research, including the need to develop analytical models of DSO-level capacity market designs to address these potential objectives and examine their implications for DSOs and consumers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Coordinated Market Design for Peer-to-Peer Energy Trade and Ancillary Services in Distribution Grids

A novel peer-to-peer (P2P) market design is proposed in this work for the distribution grid level. Envisioning that the grid constraints violations are the major challenge for P2P energy sharing, we propose they are handled through the ancillary service (AS) market. By calculating the decomposable distribution locational marginal prices (DLMPs), the essential price signals of procuring AS can be recovered to determine the grid usage prices (GUPs) to each P2P transaction. Hence, the GUPs, due to their decomposable properties, act as incentive signals for the P2P market to support the grid operation in terms of loss reduction, voltage support and congestion management. The proposed market design comprises: i) an interactive market design of P2P trade & AS and, ii) a fully decentralized peer-centric market clearing model for P2P energy trade. The duality analysis provides the composition of market equilibrium prices of P2P trading and their interpretations. The case studies demonstrate the effectiveness of the proposed P2P trade to support grid operational objectives.

Zhang, Kai↗
DOE OSTI2022

Avista CEF2 Shared Energy Economy: Modeling and Simulation

This research project supported Avista’s Shared Energy Economy (SEE) Project in Spokane’s University District (UDistrict), as funded by the WA Department of Commerce Clean Energy Fund (CEF) Phase 2. The SEE project comprises a microgrid with two campus buildings, two solar photovoltaic generators, and two batteries. The microgrid can operate grid-connected or off-grid. This research project included modeling the buildings and other microgrid components, simulating a transactive energy system, and supporting Avista’s testing of different use cases for the WA Department of Commerce. The main research finding is that buildings can be modeled successfully in a data-driven approach.

14 SOLAR ENERGY↗
DOE OSTI2023

Blockchain Empowered Provenance Framework for Sensor Identity Management and Data Flow Security in Fossil-based Power Plants

The overall goals of this project are divided into 3 important phases. First, a peer-to-peer SCADA network is to be established where identity profile of sensors from fossil-power plants will be stored in an immutable manner in order to verify data flow integrity in real time. Second, it is aimed to develop a Blockchain-based provenance platform to audit equipment operations along with data and process integrity violations. In this phase, various operational rules will be incorporated in the ledger on behalf of the operating sensor so its abnormal use can be easily detected. In addition, it is aimed to achieve provenance when the rate of transactions is exceedingly high, thus enabling to design a scalable provenance scheme that can work in real time when number of data collecting points or sensor units increase in fossil-based power plants. Finally, a working testbed will be developed to integrate the Blockchain platform with sensor-based fossil power plant comprising of Remote Terminal Units (RTU) and SCADA devices. Using multiple Raspberry-PIs mimicking the role of RTUs that are interfaced with multiple sensors devices will be deployed to serve as a critical component of fossil power plant and the performance metrics such as throughput, latency, bootstrapping time, etc., will be evaluated on the testbed.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS2005

Modeling Leadership Styles in Human-Robot Team Dynamics

The recent proliferation of robotic systems in our society has placed questions regarding interaction between humans and intelligent machines at the forefront of robotics research. In response, our research attempts to understand the context in which particular types of interaction optimize efficiency in tasks undertaken by human-robot teams. It is our conjecture that applying previous research results regarding leadership paradigms in human organizations will lead us to a greater understanding of the human-robot interaction space. In doing so, we adapt four leadership styles prevalent in human organizations to human-robot teams. By noting which leadership style is more appropriately suited to what situation, as given by previous research, a mapping is created between the adapted leadership styles and human-robot interaction scenarios-a mapping which will presumably maximize efficiency in task completion for a human-robot team. In this research we test this mapping with two adapted leadership styles: directive and transactional. For testing, we have taken a virtual 3D interface and integrated it with a genetic algorithm for use in &le-operation of a physical robot. By developing team efficiency metrics, we can determine whether this mapping indeed prescribes interaction styles that will maximize efficiency in the teleoperation of a robot.

Cruz, Gerardo E.↗
DOE OSTI2020

Safe and Private Forward-trading Platform for Transactive Microgrids

Power grids are evolving at an unprecedented pace due to the rapid growth of distributed energy resources (DER) in communities. These resources are very different from traditional power sources, as they are located closer to loads and thus can significantly reduce transmission losses and carbon emissions. However, their intermittent and variable nature often results in spikes in the overall demand on distribution system operators (DSO). To manage these challenges, there has been a surge of interest in building decentralized control schemes, where a pool of DERs combined with energy storage devices can exchange energy locally to smooth fluctuations in net demand. Building a decentralized market for transactive microgrids is challenging, because even though a decentralized system provides resilience, it also must satisfy requirements such as privacy, efficiency, safety, and security, which are often in conflict with each other. As such, existing implementations of decentralized markets often focus on resilience and safety but compromise on privacy. In this article, we describe our platform, called TRANSAX, which enables participants to trade in an energy futures market, which improves efficiency by finding feasible matches for energy trades, enabling DSOs to plan their energy needs better. TRANSAX provides privacy to participants by anonymizing their trading activity using a distributed mixing service, while also enforcing constraints that limit trading activity based on safety requirements, such as keeping planned energy flow below line capacity. We show that TRANSAX can satisfy the seemingly conflicting requirements of efficiency, safety, and privacy. We also provide an analysis of how much trading efficiency is lost. Trading efficiency is improved through the problem formulation, which accounts for temporal flexibility, and system efficiency is improved using a hybrid-solver architecture. Lastly, we describe a testbed to run experiments and demonstrate its performance using simulation results.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2010

The Kepler DB, a Database Management System for Arrays, Sparse Arrays and Binary Data

The Kepler Science Operations Center stores pixel values on approximately six million pixels collected every 30-minutes, as well as data products that are generated as a result of running the Kepler science processing pipeline. The Kepler Database (Kepler DB) management system was created to act as the repository of this information. After one year of ight usage, Kepler DB is managing 3 TiB of data and is expected to grow to over 10 TiB over the course of the mission. Kepler DB is a non-relational, transactional database where data are represented as one dimensional arrays, sparse arrays or binary large objects. We will discuss Kepler DB's APIs, implementation, usage and deployment at the Kepler Science Operations Center.

McCauliff, Sean↗
NASA NTRS1992

Reuse: A knowledge-based approach

This paper describes our research in automating the reuse process through the use of application domain models. Application domain models are explicit formal representations of the application knowledge necessary to understand, specify, and generate application programs. Furthermore, they provide a unified repository for the operational structure, rules, policies, and constraints of a specific application area. In our approach, domain models are expressed in terms of a transaction-based meta-modeling language. This paper has described in detail the creation and maintenance of hierarchical structures. These structures are created through a process that includes reverse engineering of data models with supplementary enhancement from application experts. Source code is also reverse engineered but is not a major source of domain model instantiation at this time. In the second phase of the software synthesis process, program specifications are interactively synthesized from an instantiated domain model. These specifications are currently integrated into a manual programming process but will eventually be used to derive executable code with mechanically assisted transformations. This research is performed within the context of programming-in-the-large types of systems. Although our goals are ambitious, we are implementing the synthesis system in an incremental manner through which we can realize tangible results. The client/server architecture is capable of supporting 16 simultaneous X/Motif users and tens of thousands of attributes and classes. Domain models have been partially synthesized from five different application areas. As additional domain models are synthesized and additional knowledge is gathered, we will inevitably add to and modify our representation. However, our current experience indicates that it will scale and expand to meet our modeling needs.

Iscoe, Neil↗
NASA NTRS2010

Polyphony: A Workflow Orchestration Framework for Cloud Computing

Cloud Computing has delivered unprecedented compute capacity to NASA missions at affordable rates. Missions like the Mars Exploration Rovers (MER) and Mars Science Lab (MSL) are enjoying the elasticity that enables them to leverage hundreds, if not thousands, or machines for short durations without making any hardware procurements. In this paper, we describe Polyphony, a resilient, scalable, and modular framework that efficiently leverages a large set of computing resources to perform parallel computations. Polyphony can employ resources on the cloud, excess capacity on local machines, as well as spare resources on the supercomputing center, and it enables these resources to work in concert to accomplish a common goal. Polyphony is resilient to node failures, even if they occur in the middle of a transaction. We will conclude with an evaluation of a production-ready application built on top of Polyphony to perform image-processing operations of images from around the solar system, including Mars, Saturn, and Titan.

Space Exploration,↗
DOE OSTI2019

GridWise Transactive Energy Framework (V.1.1)

Over the past two decades, the use of demand response and other flexible distributed resources for electricity market efficiency and grid reliability has grown dramatically. Federal and state policy objectives point to an important role for customers’ loads, generation, and storage in the management of an increasingly unpredictable power system. As we consider the need to substantially scale the use of flexible distributed energy resources, growing attention has been devoted to the need to address not only the economics of the electricity grid, but also the control system implications, to address grid reliability. This has led to a focus on an area of activity called “Transactive Energy.” Transactive energy (TE) refers to the use of a combination of economic and control techniques to improve grid reliability and efficiency. These techniques may also be used to optimize operations within a customer’s facility. The U.S. Department of Energy has supported the GridWise ® Architecture Council (“the Council”) in developing a conceptual framework for developing architectures and designing solutions related to TE. The goal of this effort is to encourage and facilitate collaboration among the many stakeholders involved in the transformation of the power system and thereby advance the practical implementation of TE.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Optimal Transactive Energy Trading of Electric Vehicle Charging Stations With On-Site PV Generation in Constrained Power Distribution Networks

This paper presents a two-level transactive energy market framework, that enables energy trading among electric vehicle charging stations (EVCSs). At the lower level, the discharging capability of EVs and on-site PV generation are leveraged by individual EVCS for participating in the transactive trading with their peers. Once the lower-level trading is completed, EVCSs trade energy at the upper level through the power grid network managed by the distribution system operator (DSO). The upper-level market is cleared while satisfying the power distribution network constraints. A cooperative game-based model is proposed to model the energy trading among EVCSs. To this end, the asymmetric Nash bargaining method is applied to allocate the grand coalition's payoff to each EVCS at the upper-level market, while a weighted proportional allocation method is used to allocate individual EVCS's payoff to its respective EVs at the lower-level market. In this work, the upper-level market formulation is further decomposed into two subproblems representing an energy scheduling and trading subproblem which maximizes EVCS payoffs, and a bargaining subproblem which allocates EVCS payoffs. The effectiveness of the proposed framework for incentivizing transactive trades among EVs and EVCSs is validated in case studies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1989

Linking consistency with object/thread semantics - An approach to robust computation

This paper presents an object/thread based paradigm that links data consistency with object/thread semantics. The paradigm can be used to achieve a wide range of consistency semantics from strict atomic transactions to standard process semantics. The paradigm supports three types of data consistency. Object programmers indicate the type of consistency desired on a per-operation basis and the system performs automatic concurrency control and recovery management to ensure that those consistency requirements are met. This allows programmers to customize consistency and recovery on a per-application basis without having to supply complicated, custom recovery management schemes. The paradigm allows robust and nonrobust computation to operate concurrently on the same data in a well defined manner. The operating system needs to support only one vehicle of computation - the thread.

Chen, Raymond C.↗
DOE OSTI2024

Power System Waveform Datasets for Machine Learning

The desire for increased visibility across the electricity grid will necessarily increase the deployment of sensing and measurement devices and associated data management needs to unprecedented levels. For the existing sensing and measurement infrastructure, there remains a great amount of “value” yet to be extracted through advanced data management and analytics. Availability of more data will not, by itself, lead to changes in grid visibility, security, and resiliency. To create the predictive and prescriptive environment required to enable new markets and transactions for customer revenue and a reliable grid, the data must be collected, organized, evaluated, and analyzed using sophisticated algorithms to provide actionable information allowing operators and customers to reliably manage an increasingly complex grid. Progress in artificial intelligence (AI) has been largely driven by large, publicly available datasets that can be used to train AI algorithms such as MNIST, a database of handwritten images of digits, and ImageNet, an image database of everyday objects. These types of publicly available databases of real-world training datasets have been largely credited for advancement of image processing, computer vision, and deep learning algorithms that these use cases deploy. However, in the power systems industry to date, there are few databases with proper event labeling, and data access to a publicly available collection of power system event waveforms that will allow users to interact with grid signature data. Publicly available datasets of power system event waveforms, such as the DOE/EPRI dataset, often lack critical metadata or contain limited examples of each event type, and data formats vary widely across these datasets.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Instruction Roofline: An insightful visual performance model for GPUs

The Roofline performance model provides an intuitive approach to identify performance bottlenecks and guide performance optimization. However, the classic FLOP-centric approach is inappropriate for the emerging applications that perform more integer operations than floating point operations. In this article, we reintroduce our Instruction Roofline Model on NVIDIA GPUs and expand our evaluation of it. The Instruction Roofline incorporates instructions and memory transactions across all memory hierarchies together, and provides more performance insights than the FLOP-oriented Roofline Model, that is, instruction throughput, stride memory access patterns, bank conflicts, and thread predication. We use our Instruction Roofline methodology to analyze eight proxy applications: HPGMG from AMReX, Matrix Transpose benchmarks, ADEPT from MetaHipMer's sequence alignment phase, EXTENSION from MetaHipMer's local assembly phase, CUSP, cuSPARSE, cudaTensorCoreGemm, and cuBLAS. We demonstrate the ability of our methodology to understand various aspects of performance and performance bottlenecks on NVIDIA GPUs and motivate code optimizations.

Ding, N↗
DOE OSTI2021

Co-simulation of transactive energy markets: A framework for market testing and evaluation

The proliferation of distributed energy resources (DER)—and the ability to intelligently control these assets—is re-defining the electrical distribution system. As the number of controllable devices rapidly expands, grid operators must determine how to incorporate these assets while delivering reliable, equitable, and affordable electricity. One possible approach is to establish distribution-level electricity markets and allow devices/aggregations of devices to participate in price establishment. While this approach purports some of the same benefits as the highly successful wholesale electricity markets (i.e., open competition, efficient price discovery, reduced communication overhead), this needs to be researched and quantified via an analysis platform that models distribution-level markets at the appropriate fidelity. Specifically, the simultaneous evaluation of market performance, DER performance, DER bidding approaches, and distribution feeder power quality requires modeling that spans multiple technical areas. Co-simulation has emerged as a powerful tool in addressing this type of problem, where outputs depend on a range of underlying areas of expertise and associated models. In this paper we describe a solution, as implemented in the HELICS co-simulation platform, where we include (1) high fidelity house models, (2) intelligent bidding agents, (3) a modular market integration/design, and (4) a distribution feeder model. We then present a case study where we test two different market designs: (1) a pseudo-wholesale double-blind auction, and (2) an asynchronous matching market. In this work, the markets are run under two DER penetration levels and economic results are compared to full retail net energy metering and avoided cost net metering scenarios that bookend current approaches to remuneration of DER participation. We show the potential for transactive markets to provide increased value for most customers relative to net metering (and all customers relative to avoided cost scenarios) while decreasing costs for the utility.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Distributed Ledger Technology Preliminary Performance Assessment for Applications in Utilities Operational Technology

This paper provides descriptions of the key components of different distributed ledger technology platforms. Distributed ledger technology (DLT) allows for distribution of databases among different organizations and devices. The platforms use cryptographically linked “blocks” to store and verify transactional information between these organizations. DLT increases data security, data integrity, trust among its participants. Different organizations are looking to deploy this distributed and decentralized approach to avoid the single-point-of-failure vulnerabilities associated with centralized data repositories. In this study we examine twelve different DLT platforms. There is agreement within the community that of all the platforms considered here, Hyperledger and Ethereum are the most mature when it comes to privacy and permissions. These DLT platforms are being used for applications such as transactive energy, health care, and the food and goods supply chain. However, further development is required to realize the full promise of DLT. Our assessment includes a general description of each DLT and its key characteristics. Such characteristics include consensus protocol and cryptography used, public vs. private, and permissioned or permissionless. The selection and implementation of a DLT architecture depends heavily on the use case and performance requirements. During this research we found key parameters to measure performance and existing tools for assessment. Four different parameters were identified 1) consensus, 2) throughput, 3) latency, and 4) scalability. The architectures of Hyperledger Caliper and Blockbench are described as different performance assessment frameworks. From this preliminary study it is evident that there are dissimilarities on the performance assessments methods developers and users are characterizing DLT architectures. The purpose of this paper is to identify key parameters to test performance, tools that are being used and provide information on results from previous studies.

97 MATHEMATICS AND COMPUTING↗