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Wind Technology Modeling Within the System Advisor Model (SAM) (Poster)

This poster provides detail for implementation and the underlying methodology for modeling wind power generation performance in the National Renewable Energy Laboratory's (NREL's) System Advisor Model (SAM). SAM's wind power model allows users to assess projects involving one or more large or small wind turbines with any of the detailed options for residential, commercial, or utility financing. The model requires information about the wind resource, wind turbine specifications, wind farm layout (if applicable), and costs, and provides analysis to compare the absolute or relative impact of these inputs. SAM is a system performance and economic model designed to facilitate analysis and decision-making for project developers, financers, policymakers, and energy researchers. The user pairs a generation technology with a financing option (residential, commercial, or utility) to calculate the cost of energy over the multi-year project period. Specifically, SAM calculates the value of projects which buy and sell power at retail rates for residential and commercial systems, and also for larger-scale projects which operate through a power purchase agreement (PPA) with a utility. The financial model captures complex financing and rate structures, taxes, and incentives.

17 WIND ENERGY↗

Smart Grid Solutions That Pay You [Slides]

Describes technologies for mature demand-side asset market. Bi-directional DR; less intrusive to customers; challenges: regulatory, ISO and utility focus, engagement of loads, and effective pilots.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA's Space Launch System Mission Capabilities for Exploration

Designed to enable human space exploration missions, including eventual landings on Mars, NASA's Space Launch System (SLS) represents a unique launch capability with a wide range of utilization opportunities, from delivering habitation systems into the lunar vicinity to high-energy transits through the outer solar system. Developed with the goals of safety, affordability and sustainability in mind, SLS is a foundational capability for NASA's future plans for exploration, along with the Orion crew vehicle and upgraded ground systems at the agency's Kennedy Space Center. Substantial progress has been made toward the first launch of the initial configuration of SLS, which will be able to deliver more than 70 metric tons of payload into low Earth orbit (LEO), greater mass-to-orbit capability than any contemporary launch vehicle. The vehicle will then be evolved into more powerful configurations, culminating with the capability to deliver more than 130 metric tons to LEO, greater even than the Saturn V rocket that enabled human landings on the moon. SLS will also be able to carry larger payload fairings than any contemporary launch vehicle, and will offer opportunities for co-manifested and secondary payloads. Because of its substantial mass-lift capability, SLS will also offer unrivaled departure energy, enabling mission profiles currently not possible. Early collaboration with science teams planning future decadal-class missions have contributed to a greater understanding of the vehicle's potential range of utilization. This presentation will discuss the potential opportunities this vehicle poses for the planetary sciences community, relating the vehicle's evolution to practical implications for mission capture. As this paper will explain, SLS will be a global launch infrastructure asset, employing sustainable solutions and technological innovations to deliver capabilities for space exploration to power human and robotic systems beyond our Moon and in to deep space.

Creech, Stephen D.↗

NASA'S Space Launch System Mission Capabilities for Exploration

Designed to enable human space exploration missions, including eventual landings on Mars, NASA’s Space Launch System (SLS) represents a unique launch capability with a wide range of utilization opportunities, from delivering habitation systems into the lunar vicinity to high-energy transits through the outer solar system. Developed with the goals of safety, affordability and sustainability in mind, SLS is a foundational capability for NASA’s future plans for exploration, along with the Orion crew vehicle and upgraded ground systems at the agency’s Kennedy Space Center. Substantial progress has been made toward the first launch of the initial configuration of SLS, which will be able to deliver more than 70 metric tons of payload into low Earth orbit (LEO), greater mass-to-orbit capability than any contemporary launch vehicle. The vehicle will then be evolved into more powerful configurations, culminating with the capability to deliver more than 130 metric tons to LEO, greater even than the Saturn V rocket that enabled human landings on the moon. SLS will also be able to carry larger payload fairings than any contemporary launch vehicle, and will offer opportunities for co-manifested and secondary payloads. Because of its substantial mass-lift capability, SLS will also offer unrivaled departure energy, enabling mission profiles currently not possible. Early collaboration with science teams planning future decadal-class missions have contributed to a greater understanding of the vehicle’s potential range of utilization. This presentation will discuss the potential opportunities this vehicle poses for the planetary sciences community, relating the vehicle’s evolution to practical implications for mission capture. As this paper will explain, SLS will be a global launch infrastructure asset, employing sustainable solutions and technological innovations to deliver capabilities for space exploration to power human and robotic systems beyond our Moon and in to deep space.

Creech, Stephen D.↗

Adapting Grid Criticality for Data Centers

This presentation explores the evolving definition of “critical load” in the electric grid, emphasizing the growing importance of digital infrastructure—particularly data centers—in grid resilience, restoration, and modernization. As utilities increasingly rely on AI-driven analytics and software-defined control systems, data centers have shifted from passive electricity consumers to essential computational hubs that enable National Critical Functions (NCFs) and support real-time grid operations. The deck examines the scale and impact of digital loads, the need for grid modernization to manage rapid load growth, and the diverse computing paradigms required for AI deployment. It introduces a tiered taxonomy for classifying critical loads, highlights operational dependencies between the grid and digital infrastructure, and discusses policy implications for integrating data centers into emergency planning and restoration protocols. Through case studies and practical frameworks, the presentation provides actionable insights for utilities, regulators, and planners navigating the digital transformation of the power sector.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

Precursor SSF utilization: The MODE experiments

The MIT Space Engineering Research Center is the principal investigator for a series of experiments which utilize the Shuttle Middeck as an engineering dynamics laboratory. The first, which flew on STS-48 in Sep. 1991, was the Middeck O-gravity Dynamics Experiment (MODE). This experiment focused on the dynamics of a scaled deployable truss, similar to that of SSF, and contained liquids in tanks. MODE will be reflown in the fall of 1993. In mid-1994, the Middeck Active Control Experiment (MACE) will examine the issues associated with predicting and verifying the closed loop behavior of a controlled structure in zero gravity. The paper will present experiment background, planning, operational experience, results, and lessons learned from these experiments which are pertinent to SSF utilization.

Crawley, Edward F.↗

Automated Glovebox Work-cell Design - 18370

Los Alamos National Laboratory (LANL) is the primary plutonium science and manufacturing facility in the United States supporting multiple national security programs. It is responsible for completing a high variety of small-batch manufacturing tasks requiring the handling and precision machining of Special Nuclear Materials (SNM). Given the myriad of tasks that must be completed in a limited workspace, LANL intends to utilize flexible, multi-use robotic work-cells capable of completing a variety of mission critical tasks in a single glovebox with no re-tooling needed between batch jobs. This approach would allow LANL more flexibility in its production schedule and to meet its future production and research objectives. In this paper, we present a system that integrates multiple sensors and other manufacturing peripherals into existing glovebox infrastructure. Currently, a technician can place an object in the work area where vision sensors and supervisory software identify the object and its pose and automatically determine which manufacturing task to complete. Pose uncertainty is addressed in real-time by the task planner, eliminating the need for fixtures. Grasps are validated using pressure sensors, payload sensors, and grasp quality metrics to ensure that objects are not dropped or damaged during manipulation. The robot, sensors, and peripherals are controlled using open-source software built utilizing ROS (Robot Operating System), which minimizes redevelopment and allows for re-use and extensibility. Established capabilities support vision, collision-free path planning, and more, minimizing development time. For this effort, particular attention was given to the integration of general peripheral devices (drill, chuck, etc.), which is critical to efficiently utilizing ROS in manufacturing environments. This integration is achieved with an in-development framework that allows for quick integration of peripherals, including I/O devices and motors. Contact tasks utilize the Generalized Contact Control Framework (GCCF) previously developed at UT Austin. GCCF allows application developers to easily define multiple contact control tasks for a single robot. This paper summarizes the key software components necessary to develop the multi-use work-cell including existing ROS components. UT-developed software for grasp validation, peripheral integration, and contact control is presented in more depth. Finally the glovebox system is demonstrated completing a set of tasks with no fixturing necessary. Primary tasks include surface preparation/ablation, drilling, press-fitting, and sorting, as well as supporting material transfer and inspection tasks. The glovebox work-cell reduces cost, operator dose, ergonomic issues, and time loss due to material transfer between gloveboxes that only support one task. If multiple glovebox work-cells are in use, they have the potential to eliminate bottlenecks and scale production capabilities beyond current limits. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Advances on CHP District Energy and Microgrids Deployment: Simplified Tool for Rapidly Deploying Feasibility Analytics for the Non-Technical User (Final Technical Report)

Community energy systems have proven to have the potential to improve cost efficiency, resilience, and decarbonize. However, investing in community energy systems such as community microgrids or district energy systems is a complex decision due to the high initial investment and the uncertainties associated with the long development time and lifecycle of the project. Tools that make feasibility assessments accessible to non-technical users like investors, policymakers, and other stakeholders will result in more feasibility analyses completed, more candidate projects identified, and more community energy systems deployed. The pilot tool developed under this award is named Energy Fellow. Energy Fellow allows technical and non-technical users to complete feasibility analyses for district energy systems and community microgrids. This is the first software tool of its kind designed for non-technical users and available at no cost. Its scope was adjusted to a 25x25-mile region within the Houston area in Texas to make its development compatible with the funding available. However, the findings and models developed make this pilot tool easily scalable to the US. The lessons learned during the design, implementation, and testing stages have helped find trade-off solutions to software and hardware challenges related to implementing 3D models in online tools. Green software strategies has been successfully applied to the design and operations of the tool, and the team has researched the aspects of the (non-technical) user experience that will make commercial developments of this tool even more impactful.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Resource Requirements Planning for Hospitals Treating Serious Infectious Disease Cases

This report presents a mathematical model of the way in which a hospital uses a variety of resources, utilities and consumables to provide care to a set of in-patients, and how that hospital might adapt to provide treatment to a few patients with a serious infectious disease, like the Ebola virus. The intended purpose of the model is to support requirements planning studies, so that hospitals may be better prepared for situations that are likely to strain their available resources. The current model is a prototype designed to present the basic structural elements of a requirements planning analysis. Some simple illustrati ve experiments establish the mo del's general capabilities. With additional inve stment in model enhancement a nd calibration, this prototype could be developed into a useful planning tool for ho spital administrators and health care policy makers.

59 BASIC BIOLOGICAL SCIENCES↗

Operational Benefits of Meeting California's Energy Storage Targets

In October 2013, the California Public Utilities Commission (CPUC) finalized procurement targets and other requirements to its jurisdictional utilities for a minimum of 1,325 MW of 'viable and cost-effective' energy storage systems by 2020. The goal of this study is to explore several aspects of grid operations in California and the Western Interconnection resulting from meeting the CPUC storage targets. We perform this analysis using a set of databases and grid simulation tools developed and implemented by the CPUC, the California Independent System Operator (CAISO), and the California Energy Commission (CEC) for the CPUC's Long-term Procurement Plan (LTPP). The 2014 version of this database contains information about generators, storage, transmission, and electrical demand, for California in the year 2024 for both 33% and 40% renewable energy portfolios. We examine the value of various services provided by energy storage in these scenarios. Sensitivities were performed relating to the services energy storage can provide, the capacity and duration of storage devices, export limitations, and negative price floor variations. Results show that a storage portfolio, as outlined by the CPUC, can reduce curtailment and system-wide production costs for 33% and 40% renewable scenarios. A storage device that can participate in energy and ancillary service markets provides the grid with the greatest benefit; the mandated storage requirement of 1,325 MW was estimated to reduce the total cost of production by about 78 million per year in the 33% scenario and 144 million per year in the 40% scenario. Much of this value is derived from the avoided start and stop costs of thermal generators and provision of ancillary services. A device on the 2024 California grid and participating in only ancillary service markets can provide the system with over 90% of the value as the energy and ancillary service device. The analysis points to the challenge of new storage providing regulation reserve, as the added storage could provide about 75% of the regulation up requirement for all of California, which would likely greatly reduce regulation prices and potential revenue. The addition of storage in California decreases renewable curtailment, particularly in the 40% RPS case. Following previous analysis, storage has a mixed impact on emissions, generally reducing emissions, but also creating additional incentives for increased emissions from out-of-state coal generations. Overall, storage shows significant system cost savings, but analysis also points to additional challenges associated with full valuation of energy storage, including capturing the operational benefits calculated here, but also recovering additional benefits associated avoided generation, transmission, and distribution capacity, and avoided losses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

National Grid Deep Energy Retrofit Pilot

Through discussion of five case studies (test homes), this project evaluates strategies to elevate the performance of existing homes to a level commensurate with best-in-class implementation of high-performance new construction homes. The test homes featured in this research activity participated in Deep Energy Retrofit (DER) Pilot Program sponsored by the electric and gas utility National Grid in Massachusetts and Rhode Island. Building enclosure retrofit strategies are evaluated for impact on durability and indoor air quality in addition to energy performance.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Artificial Intelligence and Machine Learning Applications in Modern Power Systems

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

power system applications, machine learning (ML), ↗

Capacity Expansion Planning for LA Basin: the Role of Energy Storage

The paper evaluates the deployment of energy storage to support equitable energy outcomes and the clean energy transition in the Los Angeles Basin (LAB). The deployment of energy storage is considered in a 10 zone capacity expansion planning model from 2022-2045. The model is based on the California Public Utility Commission’s 7 zone RESOLVE model but has been modified to give greater spatial granularity in the LAB area by addig 3 new zones representing the Eastern Los Angeles, Western Los Angeles and the El Nido subzones. Three different scenarios are studied in this work; a base case with no natural gas retirements in the LAB, and two cases exploring extreme natural gas retirements, where the 8GW of natural gas belonging to the LAB are retired by 2045. Study results indicate that storage can play a significant role in helping the LAB meeting its energy requirements. However, when considering extreme retirement scenarios, either new generation (such as solar) or capacity (such as new import capacity via transmission lines) will likely be needed to serve projected system loads.

Maloney, Patrick R.↗

Final scientific report for DOE award title: Improving the Representation of Ice Sedimentation Rates in Global Climate Models

It is well known that cirrus clouds play a major role in regulating the earth’s climate, but the details of how this works are just beginning to be understood. This project targeted the main property of cirrus clouds that influence climate processes; the ice fall speed. That is, this project improves the representation of the mass-weighted ice particle fall velocity, V m , in climate models, used to predict future climate on global and regional scales. Prior to 2007, the dominant sizes of ice particles in cirrus clouds were poorly understood, making it virtually impossible to predict how cirrus clouds interact with sunlight and thermal radiation. Due to several studies investigating the performance of optical probes used to measure the ice particle size distribution (PSD), as well as the remote sensing results from our last ARM project, it is now well established that the anomalously high concentrations of small ice crystals often reported prior to 2007 were measurement artifacts. Advances in the design and data processing of optical probes have greatly reduced these ice artifacts that resulted from the shattering of ice particles on the probe tips and/or inlet tube, and PSD measurements from one of these improved probes (the 2-dimensional Stereo or 2D-S probe) are utilized in this project to parameterize V m for climate models. Our original plan in the proposal was to parameterize the ice PSD (in terms of temperature and ice water content) and ice particle mass and projected area (in terms of mass- and area-dimensional power laws or m-D/A-D expressions) since these are the microphysical properties that determine V m , and then proceed to calculate V m from these parameterized properties. But the 2D-S probe directly measures ice particle projected area and indirectly estimates ice particle mass for each size bin. It soon became apparent that the original plan would introduce more uncertainty in the V m calculations than simply using the 2D-S measurements to directly calculate V m . By calculating V m directly from the measured PSD, ice particle projected area and estimated mass, more accurate estimates of V m are obtained. These V m values were then parameterized for climate models by relating them to (1) sampling temperature and ice water content (IWC) and (2) the effective diameter (D e ) of the ice PSD. Parameterization (1) is appropriate for climate models having single-moment microphysical schemes whereas (2) is appropriate for double-moment microphysical schemes and yields more accurate V m estimates. These parameterizations were developed for tropical cirrus clouds, Arctic cirrus, mid-latitude synoptic cirrus and mid-latitude anvil cirrus clouds based on field campaigns in these regions. An important but unexpected result of this research was the discovery of microphysical evidence indicating the mechanisms by which ice crystals are produced in cirrus clouds. This evidence, derived from PSD measurements, indicates that homogeneous freezing ice nucleation dominates in mid-latitude synoptic cirrus clouds, whereas heterogeneous ice nucleation processes dominate in mid-latitude anvil cirrus. Based on these findings, D e was parameterized in terms of temperature (T) for conditions dominated by (1) homo- and (2) heterogeneous ice nucleation. From this, an experiment was designed for global climate models (GCMs). The net radiative forcing from cirrus clouds may be affected by the means ice is produced (homo- or heterogeneously), and this net forcing contributes to climate sensitivity (i.e. the change in mean global surface temperature resulting from a doubling of CO 2 ). The objective of this GCM experiment was to determine how a change in ice nucleation mode affects the predicted global radiation balance. In the first simulation (Run 1), the D e -T relationship for homogeneous nucleation is used at all latitudes, while in the second simulation (Run 2), the D e -T relationship for heterogeneous nucleation is used at all latitudes. For both runs, V m is calculated from D e . Two GCMs were used; the Community Atmosphere Model version 5 (CAM5) and a European GCM known as ECHAM5 (thanks to our European colleagues who collaborated with us). Similar results were obtained from both GCMs in the Northern Hemisphere mid-latitudes, with a net cooling of ~ 1.0 W m -2 due to heterogeneous nucleation, relative to Run 1. The mean global net cooling was 2.4 W m -2 for the ECHAM5 GCM while CAM5 produced a mean global net cooling of about 0.8 W m -2 . This dependence of the radiation balance on nucleation mode is substantial when one considers the direct radiative forcing from a CO 2 doubling is 4 W m -2 . The differences between GCMs in mean global net cooling estimates may demonstrate a need for improving the representation of cirrus clouds in GCMs, including the coupling between microphysical and radiative properties. Unfortunately, after completing this GCM experiment, we learned from the company that provided the 2D-S microphysical data that the data was corrupted due to a computer program coding problem. Therefore the microphysical data had to be reprocessed and reanalyzed, and the GCM experiments were redone under our current ASR project but using an improved experimental design.

54 ENVIRONMENTAL SCIENCES↗

Vulnerability Assessments and Resilience Planning at Federal Facilities. Preliminary Synthesis of Project

U.S. government agencies are now directed to assess the vulnerability of their operations and facilities to climate change and to develop adaptation plans to increase their resilience. Specific guidance on methods is still evolving based on the many different available frameworks. Agencies have been experimenting with these frameworks and approaches. This technical paper synthesizes lessons and insights from a series of research case studies conducted by the investigators at facilities of the U.S. Department of Energy and the Department of Defense. The purpose of the paper is to solicit comments and feedback from interested program managers and analysts before final conclusions are published. The paper describes the characteristics of a systematic process for prioritizing needs for adaptation planning at individual facilities and examines requirements and methods needed. It then suggests a framework of steps for vulnerability assessments at Federal facilities and elaborates on three sets of methods required for assessments, regardless of the detailed framework used. In a concluding section, the paper suggests a roadmap to further develop methods to support agencies in preparing for climate change. The case studies point to several preliminary conclusions; (1) Vulnerability assessments are needed to translate potential changes in climate exposure to estimates of impacts and evaluation of their significance for operations and mission attainment, in other words into information that is related to and useful in ongoing planning, management, and decision-making processes; (2) To increase the relevance and utility of vulnerability assessments to site personnel, the assessment process needs to emphasize the characteristics of the site infrastructure, not just climate change; (3) A multi-tiered framework that includes screening, vulnerability assessments at the most vulnerable installations, and adaptation design will efficiently target high-risk sites and infrastructure; (4) Vulnerability assessments can be connected to efforts to improve facility resilience to motivate participation; and (5) Efficient, scalable methods for vulnerability assessment can be developed, but additional case studies and evaluation are required.

54 ENVIRONMENTAL SCIENCES↗

5th Annual Earth System Grid Federation Face-to-Face Conference report, Monterey, California, December 7-11, 2015

The purpose of the Fifth Annual Earth System Grid Federation (ESGF) Face-to-Face (F2F) Conference was to present the most recent information on the state of ESGF’s software stack and to identify and address the data needs and gaps for the climate and weather communities that ESGF supports. This was the first meeting at which members of the international community, under international ESGF Executive Committee leadership, came together to host the conference. The organizers believed that the ESGF F2F Conference was an ideal gateway for agencies and science project leads to express their current and future data infrastructure needs to tool developers. The organizers also envisioned that attendees would brainstorm and share enhancement plans for data distribution, analysis, visualization, hardware and international network infrastructure, standards, and utilization of assorted community resources.

54 ENVIRONMENTAL SCIENCES↗

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