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At least 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Lessons in Commercial PACE Leadership: The Path from Legislation to Launch

Property Assessed Clean Energy (PACE) financing enables building owners to finance energy efficiency, renewable energy, and, in some states, non-energy building improvements through a voluntary special assessment on their properties. For commercial buildings, there are many benefits to using Commercial PACE (C-PACE) financing. Still, using C-PACE financing is a multi-step process and involves diverse stakeholders (see Figure ES-1 for a simplified overview), and the process may vary depending on the state and policy context. The primary audience for this report, Lessons in Commercial PACE Leadership, is state and local decision makers that seek an informed, objective perspective of what it takes to launch a C-PACE program. The report is specifically for those states with enabling legislation and program sponsors (i.e., state or local governments) that are looking to launch or join a C-PACE program. The report is a starting point for understanding what approaches have worked to establish successful C-PACE programs. It examines the experience of programs across the country and provides insights for making the process smoother, and hopefully less cost and time-intensive, for new state and local governments sponsoring C-PACE programs. The report also provides a roadmap to key decision points on the path to setting up a program — the different paths taken and program models employed by those who have blazed the trail. The report is organized into three sections describing the decision points involved, options and considerations, and experience from the field.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Informing forest carbon inventories under the Paris Agreement using ground-based forest monitoring data

Human interactions with forests have shaped Earth's climate for millennia and will continue to do so as we target net-zero emission goals. Accurately characterizing these climate impacts requires making reliable forest carbon data available for forest monitoring and planning. Here, we develop a semi-automated process for submitting forest carbon measurements from the largest relevant scientific database to the International Panel on Climate Change's Emission Factor Database, which currently has sparse forest carbon data. Building this bridge from scientific research to international policy is an important step towards managing forests in a net-zero motivated future. Humans have been influencing Earth's climate via transformative impacts on forests for millennia, and forests are now recognized as critical to climate change mitigation under the Paris Agreement. The efficacy of climate change mitigation planning and reporting depends on quality data on forest carbon (C) stocks and changes. The Emission Factor Database (EFDB) of the International Panel on Climate Change (IPCC) is intended to be a definitive source for such data, but needs comprehensive and well-documented data to be so. To facilitate submission of forest C estimates from scientific studies to EFDB, we develop and document a process for semi-automated data submission from the Global Forest C database (ForC v4.0), which is the largest compilation of ground-based forest C estimates. We then assess the data currently available through ForC and provide recommendations for improving forest data collection, analysis, and reporting. As of September 2024, ForC contained ~19,286 records potentially relevant to EFDB, 1068 of which had been submitted and posted to EFDB. These represented 19% of the total EFDB records for forest land. Records were unevenly distributed across variables and geographic regions. ForC records (37%) reviewed could not be submitted because the original publication lacked required information. In the future, ground-based forest C estimates should target gaps in the record, and studies should ensure that they report all information necessary for inclusion in EFDB. Given that climate change is rapidly impacting the world's forests, timely reporting of recent estimates will be critical to accurate forest C inventories.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Documenting Climate Models and Their Simulations

The results of climate models are of increasing and widespread importance. No longer is climate model output of sole interest to climate scientists and researchers in the climate change impacts and adaptation fields. Now nonspecialists such as government officials, policy makers, and the general public all have an increasing need to access climate model output and understand its implications. For this host of users, accurate and complete metadata (i.e., information about how and why the data were produced) is required to document the climate modeling results. We describe a pilot community initiative to collect and make available documentation of climate models and their simulations. In an initial application, a metadata repository is being established to provide information of this kind for a major internationally coordinated modeling activity known as CMIP5 (Coupled Model Intercomparison Project, Phase 5). We expected that for a wide range of stakeholders, this and similar community-managed metadata repositories will spur development of analysis tools that facilitate discovery and exploitation of Earth system simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Optimization of the Observing Cadence for the Rubin Observatory Legacy Survey of Space and Time: A Pioneering Process of Community-focused Experimental Design

Vera C. Rubin Observatory is a ground-based astronomical facility under construction, a joint project of the National Science Foundation and the U.S. Department of Energy, designed to conduct a multipurpose 10 yr optical survey of the Southern Hemisphere sky: the Legacy Survey of Space and Time. Significant flexibility in survey strategy remains within the constraints imposed by the core science goals of probing dark energy and dark matter, cataloging the solar system, exploring the transient optical sky, and mapping the Milky Way. The survey’s massive data throughput will be transformational for many other astrophysics domains and Rubin’s data access policy sets the stage for a huge community of potential users. To ensure that the survey science potential is maximized while serving as broad a community as possible, Rubin Observatory has involved the scientific community at large in the process of setting and refining the details of the observing strategy. The motivation, history, and decision-making process of this strategy optimization are detailed in this paper, giving context to the science-driven proposals and recommendations for the survey strategy included in this Focus Issue.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2018

A Persistent Simulation Environment for Autonomous Systems

The age of Autonomous Unmanned Aircraft Systems (AUAS) is creating new challenges for the accreditation and certification requiring new standards, policies and procedures that sanction whether a UAS is safe to fly. Establishing a basis for certification of autonomous systems via research into trust and trustworthiness is the focus of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR), a new NASA Convergent Aeronautics Solution (CAS) project. Simulation Environments to test and evaluate AUAS decision making may be a low-cost solution to help certify that various AUAS systems are trustworthy enough to be allowed to fly in current general and commercial aviation airspace. NASA is working to build a peer-to-peer persistent simulation (P3 Sim) environment. The P3 Sim will be a Massively Multiplayer Online (MMO) environment were AUAS avatars can interact with a complex dynamic environment and each other. The focus of the effort is to provide AUAS researchers a low-cost intuitive testing environment that will aid training for and assessment of decisions made by autonomous systems such as AUAS. This presentation focuses on the design approach and challenges faced in development of the P3 Sim Environment is support of investigating trustworthiness of autonomous systems.

Kelley, Benjamin N.↗
DOE OSTI2017

Improving social impact assessment of protected areas: A review of the literature and directions for future research

Protected areas are the most widely applied policy tool for biodiversity conservation. However, effective management of protected areas is often obstructed by conflicts mainly associated with the social impacts imposed on local communities and other users by their establishment. Despite the importance of these social impacts they remain significantly under-researched. There is now an increasing need to incorporate social impacts in decision making processes by providing accurate estimations and develop ways to forecast their change in the future. Considering the increase of studies identifying this need, the present paper aims to indicate three main directions that will assist in designing effective tools for measuring and most importantly understanding social impacts: a) perceptions on social impacts of individuals who are directly affected by protected areas need to be incorporated in management evaluation techniques in a meaningful and accurate way and be combined with objective measurements of impact; b) understanding the factors determining the actual and perceived levels of social impacts is a key step for the design of effective management frameworks of protected areas and c) social impacts should not be seen as static concepts but should be seen as a dynamic and long-term factor which needs to be incorporated in decision-making processes.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Climate impacts on hydropower in Colombia: A multi-model assessment of power sector adaptation pathways

There is uncertainty as to how climate change will affect hydropower generation in different regions of the world. In drying regions, impaired hydropower production could result in significant changes to the power sector implying new plants to be installed to make up for lost hydropower generation. In this article we apply two partial equilibrium models (TIAM-ECN and GCAM) and two general equilibrium models (Phoenix and MEG4C) to identify possible pathways of power sector adaptation for Colombia under climate change scenarios that reflect altered water inflow to hydropower reservoirs. Each model is run for two emissions policy scenarios and for a dry and moderate climate projection. Planned hydropower expansion for Colombia is insufficient to meet increased power demands as the country's economy grows; the contribution of hydropower to Colombia's power supply drops from ~65% currently to 30 - 50 % by 2050 depending on energy model and scenario. Climate change reduces this by a further 5 - 10 % under the dry climate projection. Climate-driven losses in hydropower will be compensated by an expansion of alternative technologies, which vary significantly across models. When climate policy is implemented, three distinct pathways emerge: expanding the electricity production from solar and wind energy (TIAM-ECN); reducing overall power demand hence exploiting savings and efficiencies (Phoenix and MEG4C); and expanding the use of fossil resources—primarily natural gas— complemented with carbon dioxide capture and storage (GCAM).

Arango, Santiago↗
DOE OSTI2023

The Health and Climate Benefits of Economic Dispatch in China’s Power System

China’s power system is highly regulated and uses an “equal-share” dispatch approach. However, market mechanisms are being introduced to reduce generation costs and improve system reliability. Here, we quantify the climate and human health impacts brought about by this transition, modeling China’s power system operations under economic dispatch. We find that significant reductions in mortality related to air pollution (11%) and CO 2 emissions (3%) from the power sector can be attained by economic dispatch, relative to the equal-share approach, through more efficient coal-powered generation. Additional health and climate benefits can be achieved by incorporating emission externalities in electricity generation costs. However, the benefits of the transition to economic dispatch will be unevenly distributed across China and may lead to increased health damage in some regions. Our results show the potential of dispatch decision-making in electricity generation to mitigate the negative impacts of power plant emissions with existing facilities in China.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

An Analysis of the Costs, Benefits, and Implications of Different Approaches to Capturing the Value of Renewable Energy Tax Incentives

This report compares the relative costs, benefits, and implications of capturing the value of renewable energy tax benefits in these three different ways – applying them against outside income, carrying them forward in time until they can be fully absorbed internally, or monetizing them through third-party tax equity investors – to see which method is most competitive under various scenarios. It finds that under current law and late-2013 market conditions, monetization makes sense for all but the most tax-efficient project sponsors. In other words, for most project sponsors, bringing in third-party tax equity currently provides net benefits to a project.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Hamiltonian switching control of noisy bipartite qubit systems

Abstract We develop a Hamiltonian switching ansatz for bipartite control that is inspired by the quantum approximate optimization algorithm, to mitigate environmental noise on qubits. We demonstrate the control for a central spin coupled to bath spins via isotropic Heisenberg interactions, and then make physical applications to the protection of quantum gates performed on superconducting transmon qubits coupling to environmental two-level-systems (TLSs) through dipole-dipole interactions, as well as on such qubits coupled to both TLSs and a Lindblad bath. The control field is classical and acts only on the system qubits. We use reinforcement learning with policy gradient to optimize the Hamiltonian switching control protocols, using a fidelity objective for specific target quantum gates. We use this approach to demonstrate effective suppression of both coherent and dissipative noise, with numerical studies achieving target gate implementations with fidelities over 0.9999 (four nines) in the majority of our test cases and showing improvement beyond this to values of 0.999 999 999 (nine nines) upon a subsequent optimization by GRadient Ascent Pulse Engineering (GRAPE). We analyze how the control depth, total evolution time, number of environmental TLS, and choice of optimization method affect the fidelity achieved by the optimal protocols and reveal some critical behaviors of bipartite control of quantum gates.

Physics↗
DOE OSTI2022

PowerNet: Multi-agent Deep Reinforcement Learning for Scalable Powergrid Control

This paper develops an efficient multi-agent deep reinforcement learning algorithm for cooperative controls in powergrids. Specifically, we consider the decentralized inverter-based secondary voltage control problem in distributed generators (DGs), which is first formulated as a cooperative multi-agent reinforcement learning (MARL) problem. We then propose a novel on-policy MARL algorithm, PowerNet, in which each agent (DG) learns a control policy based on (sub-)global reward but local states and encoded communication messages from its neighbors. Motivated by the fact that a local control from one agent has limited impact on agents distant from it, we exploit a novel spatial discount factor to reduce the effect from remote agents, to expedite the training process and improve scalability. Furthermore, a differentiable, learning-based communication protocol is employed to foster the collaborations among neighboring agents. In addition, to mitigate the effects of system uncertainty and random noise introduced during on-policy learning, we utilize an action smoothing factor to stabilize the policy execution. To facilitate training and evaluation, we develop PGSim, an efficient, high-fidelity powergrid simulation platform. Here, experimental results in two microgrid setups show that the developed PowerNet outperforms the conventional model-based control method, as well as several state-of-the-art MARL algorithms. The decentralized learning scheme and high sample efficiency also make it viable to large-scale power grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

GridOPTICS Software System

GridOPTICS Software System (GOSS) is a middleware that facilitates creation of new, modular and flexible operational and planning platforms that can meet the challenges of the next generation power grid. GOSS enables Department of Energy, power system utilities, and vendors to build better tools faster. GOSS makes it possible to integrate Future Power Grid Initiative software products/prototypes into existing power grid software systems, including the PNNL PowerNet and EIOC environments. GOSS is designed to allow power grid applications developed for different underlying software platforms installed in different utilities to communicate with ease. This can be done in compliance with existing security and data sharing policies between the utilities. GOSS not only supports one-to-one data transfer between applications, but also publisher/subscriber scheme. To support interoperability requirements of future EMS, GOSS is designed for CIM compliance. In addition to this, it supports authentication and authorization capabilities to protect the system from cyber threats. In summary, the contributions of the GOSS middleware are as follows: A platform to support future EMS development. A middleware that promotes interoperability between power grid applications. A distributed architecture that separates data sources from power grid applications. Support for data exchange with either one-to-one or publisher/subscriber interfaces. An authentication and authorization scheme for limiting the access to data between utilities.

Akyol, BoraA↗
DOE OSTI2019

The Need for Nuclear Deterrent Fundamentals Training

NNSA policy requires that personnel working in the Nuclear Security Enterprise (NSE) receive comprehensive training to be fully capable before they begin their work and that personnel receive ongoing training to maintain their capability and competence. However, the loss of experienced NSE staff through retirements and the influx of personnel who are inexperienced and untrained in nuclear weapons technology make these training requirements difficult to achieve. This paper presents an approach for developing and delivering a nuclear deterrent (ND) fundamentals curriculum to respond to these challenges. The training approach leverages existing material already used by Sandia National Laboratories in the ND training arena and proposes to deliver the material in an e-learning format as much as possible. The approach also seeks to maximize the amount of material to be delivered in an unclassified setting.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS1997

Out-of-Core Streamline Visualization on Large Unstructured Meshes

It's advantageous for computational scientists to have the capability to perform interactive visualization on their desktop workstations. For data on large unstructured meshes, this capability is not generally available. In particular, particle tracing on unstructured grids can result in a high percentage of non-contiguous memory accesses and therefore may perform very poorly with virtual memory paging schemes. The alternative of visualizing a lower resolution of the data degrades the original high-resolution calculations. This paper presents an out-of-core approach for interactive streamline construction on large unstructured tetrahedral meshes containing millions of elements. The out-of-core algorithm uses an octree to partition and restructure the raw data into subsets stored into disk files for fast data retrieval. A memory management policy tailored to the streamline calculations is used such that during the streamline construction only a very small amount of data are brought into the main memory on demand. By carefully scheduling computation and data fetching, the overhead of reading data from the disk is significantly reduced and good memory performance results. This out-of-core algorithm makes possible interactive streamline visualization of large unstructured-grid data sets on a single mid-range workstation with relatively low main-memory capacity: 5-20 megabytes. Our test results also show that this approach is much more efficient than relying on virtual memory and operating system's paging algorithms.

Ueng, Shyh-Kuang↗
NASA NTRS2020

Advanced Air Mobility (AAM) Vertiport Automation Trade Study

The NASA Advanced Air Mobility (AAM) Vertiport Automation Trade Study seeks to understand the barriers to scaling AAM takeoff and landing facilities, described in this study as vertiplaces. This trade study provides an overview of AAM, vertiplaces, and insight into the gaps in capability, regulatory certainty, and knowledge needed to sufficiently manage the volume of expected traffic anticipated for vertiplaces. The study also outlines potential mitigations to those gaps based on research conducted by the project team and interviews with 23 individuals in government and industry. In this report, the elements that make up a vertiport are discussed. The study then defines a vertiplace and introduces a concept for vertiplace categorization based on capability. Capability gaps and mitigations to increasing scale and automation of vertiplaces are then discussed based around four cross-cutting themes the research of our project team found in the interviews and research: Technology, Physical Infrastructure, Policy, and Community Acceptance. The study then concludes by discussing topics requiring further research that were identified by interviewees.

Vertiport↗
DOE OSTI2014

GridOPTICS Software System

GridOPTICS Software System (GOSS) is a middleware that facilitates creation of new, modular and flexible operational and planning platforms that can meet the challenges of the next generation power grid. GOSS enables Department of Energy, power system utilities, and vendors to build better tools faster. GOSS makes it possible to integrate Future Power Grid Initiative software products/prototypes into existing power grid software systems, including the PNNL PowerNet and EIOC environments. GOSS is designed to allow power grid applications developed for different underlying software platforms installed in different utilities to communicate with ease. This can be done in compliance with existing security and data sharing policies between the utilities. GOSS not only supports one-to-one data transfer between applications, but also publisher/subscriber scheme. To support interoperability requirements of future EMS, GOSS is designed for CIM compliance. In addition to this, it supports authentication and authorization capabilities to protect the system from cyber threats. In summary, the contributions of the GOSS middleware are as follows: A platform to support future EMS development. A middleware that promotes interoperability between power grid applications. A distributed architecture that separates data sources from power grid applications. Support for data exchange with either one-to-one or publisher/subscriber interfaces. An authentication and authorization scheme for limiting the access to data between utilities.

Akyol, Bora A↗
DOE OSTI2023

Embodied Carbon Resource Navigator

The Embodied Carbon Resource Navigator is a guide to help architects, engineers, designers, contractors, and those who want to reduce their embodied carbon impact make more informed design decisions for buildings. The guide is a compilation of embodied carbon resources, organized by experience level to direct the user to the necessary resources.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗