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At least 253 records · Page 14

SEED Platform for Building Performance Standards Implementation Guide (Mandarin Translation)

This guide provides an overview of the Standard Energy Efficiency Data (SEED) Platform. The SEED Platform developed by the U.S. Department of Energy (DOE) to provide a low-cost, user-friendly tool for jurisdictions to launch and manage energy benchmarking and Building Performance Standard (BPS) programs. It has been translated into Spanish. This is the Mandarin translation of NREL/FS-5500-90691.

benchmarking↗

BETO 2021 Peer Review - Algal Biofuels Techno-Economic Analysis 1.3.5.200

The objective of NREL's Algal Biofuel Techno-Economic Analysis (TEA) project is to provide process modeling and analysis to support Algae Program activities, utilizing TEA models to relate key process parameters with overall economics for cultivation, processing, and conversion of algal biomass to fuels and coproducts. By quantifying economic implications of key process metrics, TEA models highlight the technical requirements to achieve future program cost goals as well as enabling a means to track progress towards these goals. This project provides high impact and relevance though generation of critical cost data tied to funded research, with our analyses subsequently exercised by BETO to guide program plans, FOA priorities, and other directives. This includes costs for both algal biomass production and downstream conversion, most notably to support BETO's fuel cost targets below $2.5/GGE by 2030. To mitigate a key risk/challenge in constraining our work to academic analyses rooted only in future projections, our work also seeks to provide near-term value to today's algae industry through frequent industry engagement, while maintaining close ties with other BETO collaborators. This project has made numerous accomplishments since the 2019 peer review, including a continued focus on opportunities for value-added products, with related analyses for new pathway opportunities to achieve BETO cost goals and notable State-of-Technology (SOT) improvements over prior cost benchmarks.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Boosting Energy Efficiency and Economic Development through Chambers of Commerce (Final Technical Report)

The U.S. Department of Energy’s (DOE) Building Technology Office (BTO), in its mission to improve energy efficiency in commercial and residential buildings, recognized the unique challenges posed by small- and medium-sized commercial buildings. This project targeted these buildings by using a business-to-business model originally pioneered in Cleveland, Ohio, by the Greater Cleveland Partnership’s Council of Smaller Enterprises (COSE). Rather than attempting to take programs and materials designed for large commercial buildings and simply disseminate them to owners of small- and medium-sized buildings, COSE targeted the tenants and owners of these buildings directly through existing business partnership channels and built additional business partnerships with banks willing to finance cost-effective retrofits, and leveraging utility efficiency programs that enabled them to provide free audits via an established network of auditors. By delivering a customized message to their members and leveraging their connections in the local business community, Chambers of Commerce and other business-oriented organizations use their existing relationship and trust to deliver clear and concise messages about the opportunities, impacts, and value of energy efficiency investments.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Transitioning the California Energy Commission Eligible Equipment List to a National Platform

The Energy Commission called on the National Renewable Energy Laboratory's (NREL)'s Solar Technical Assistance Team to explore various pathways for supporting continued evolution of the list. NREL staff utilized the Database of State Incentives for Renewables and Efficiency (DSIRE), California Solar Initiative (CSI) data, and information from in-depth interviews to better understand the impact of a lack of an updated list and suggest potential solutions. A total of 18 people from state energy offices, rebate program administrators, utilities, national testing laboratories, private companies, nonprofit organizations, and the federal government were interviewed between July and September 2013. CSI data were analyzed to illustrate the monetary benefits of the algorithm behind calculating performance of PV modules included on the list. The primary objectives of this study are to: 1) Determine the impact of not maintaining the list, and 2) Explore alternatives to the State of California's maintenance of the list.

14 SOLAR ENERGY↗

Integrating Mindfulness with Human Performance in High Complexity Environments - 19498

This paper includes a survey of both scientific and technical literature studies of mindfulness interventions in a variety of industries and populations and proposes potential applications in complex nuclear waste operations. Mindfulness training techniques have been utilized in various forms for decades in high consequence work in both public and private enterprise. The traditional safety nomenclature has simply used different words to describe many of the same concepts that mindfulness practice addresses. Historically, human performance improvement (HPI) has focused on task, mission and error-likely conditions. These safety programs recognize that human behavior is the source of most errors and focus on identification of specific error precursors (mind not on task, incorrect mental picture, etc.). Workers in nuclear and related industries have been trained to recognize these error precursors but have received little training on what to do about them. The techniques of mindfulness align well with HPI programs currently utilized in commercial and government nuclear operations. Indeed, Chapter 5 of the Department of Energy Human Performance Improvement Handbook (DOE-HDBK-1028-2009) includes a discussion of mindfulness with respect to human performance. Mindfulness training supplements current performance improvement efforts by giving workers the tools to not just recognize error-likely conditions within themselves, but also gives them methods to mitigate them. The mindfulness practices presented here focus on self-awareness rather than task-awareness. Workers can apply these techniques in all aspects of their lives which in turn addresses many of the distractions previously identified as error precursors (stress at home or at work, physical discomforts, mind not on task, etc.). The application of mindfulness techniques through integration with established Integrated Safety Management Systems (ISMS) has the potential to improve the safe performance of nuclear waste operations and increase the breadth of organizational safety culture. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Multiparametric Programming in Process Systems Engineering: Recent Developments and Path Forward

The inevitable presence of uncertain parameters in critical applications of process optimization can lead to undesirable or infeasible solutions. For this reason, optimization under parametric uncertainty was, and continues to be a core area of research within Process Systems Engineering. Multiparametric programming is a strategy that offers a holistic perspective for the solution of this class of mathematical programming problems. Specifically, multiparametric programming theory enables the derivation of the optimal solution as a function of the uncertain parameters, explicitly revealing the impact of uncertainty in optimal decision-making. By taking advantage of such a relationship, new breakthroughs in the solution of challenging formulations with uncertainty have been created. Apart from that, researchers have utilized multiparametric programming techniques to solve deterministic classes of problems, by treating specific elements of the optimization program as uncertain parameters. In the past years, there has been a significant number of publications in the literature involving multiparametric programming. The present review article covers recent theoretical, algorithmic, and application developments in multiparametric programming. Additionally, several areas for potential contributions in this field are discussed, highlighting the benefits of multiparametric programming in future research efforts.

Pappas, Iosif↗

Energy Efficiency Financing for Low- and Moderate-Income Households: Current State of the Market, Issues, and Opportunities

Ensuring that low- and moderate-income (LMI) households have access to energy efficiency is equitable, provides energy savings as a resource to meet energy needs, and can support multiple policy goals, such as affordable energy, job creation, and improved public health. Although the need is great, many LMI households may not be able to afford efficiency improvements or may be inhibited from adopting efficiency for other reasons. Decision-makers across the country are currently exploring the challenges and potential solutions to ramping up adoption of efficiency in LMI households, including the use of financing. The report’s objective is to offer state and local policymakers, state utility regulators, program administrators, financial institutions, consumer advocates and other LMI stakeholders with an understanding of: -The relationship between LMI communities and financing for energy efficiency, including important considerations for its use such as consumer protections -The larger programmatic context of grant-based assistance and other related resources supporting LMI household energy efficiency -Lessons learned from existing energy efficiency financing programs serving LMI households -Financing products used by these programs and their relative advantages and disadvantages in addressing barriers to financing or to energy efficiency uptake for LMI households

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Final Report for US DOE Grant DE-FG02-99ER54527

The failure of the NSTX-U coil in 2016 resulted in a redirection of UCLA’s NSTX-U research program. At that time UCLA had two functioning fluctuation reflectometer systems installed on the tokamak and was in the process of installing the new DBS/CPS system. These projects were placed on hold due to the NSTX-U recovery effort. UCLA in consultation with DOE OFES began a program of utilizing the equipment installed at NSTX-U in order to maximize the science output. In these discussion it was decided to move the V-band 50-75 GHz and the W-band 83-88 GHz multifrequency fluctuation reflectometer systems to the DIII-D tokamak. This would achieve two goals – to continue to provide important scientific input the US fusion research program and to test the new W-band system in a fusion research relevant plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

SHINE and Mini-SHINE Column Designs for Recovery of Mo from 140 g-U/L Uranyl Sulfate

Argonne is assisting SHINE Medical Technologies (SHINE) in their efforts to develop an accelerator-driven process that utilizes a uranyl-sulfate solution for the production of fission Mo-99. In an effort to design a Mo-recovery system for the SHINE project using low-enriched uranium (LEU), we conducted batch, breakthrough, and pulse tests to determine the Mo isotherm, mass-transfer zone (MTZ), and system parameters for a 130 g-U/L uranyl sulfate solution at pH 1 and 80°C, as described previously. The VERSE program was utilized to calculate the MTZ under various loading times and velocities. The results were then used to design Mo separation and recovery columns employing a pure titania sorbent (110-μm particles, S110, and 60 Å pore size). The plant-scale column designs assume Mo will be separated from 271 L of a 141 g-U/L uranyl sulfate solution, pH 1, containing 0.0023 mM Mo. The VERSE-designed recovery systems have been tested and verified in laboratory-scale experiments, and this approach was found to be very successful.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

SAM Plug-in Development (Phase I Final Report)

The DOE Office of Nuclear Energy (NE) has created an extensive set of advanced modeling and simulation tools for nuclear engineering analysis. The advanced capabilities of these newer analysis codes require more in-depth training, skills, and knowledge in order to effectively utilize them for the design, analysis, and licensing of advanced nuclear systems and experiments. A high learning curve for inexperienced users may deter organizations from incorporating these tools into their internal processes. This project involved development of a plug-in to the Symbolic Nuclear Analysis Package (SNAP) for the System Analysis Module (SAM) tool. SAM is an advanced system analysis tool for reactor transient analyses being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. SAM utilizes an object-oriented application framework (MOOSE), and its underlying meshing and finite-element library (libMesh) and linear and non-linear solvers (PETSc), to leverage modern advanced software environments and numerical methods. SNAP provides a highly flexible framework for creating, modifying and documenting input for engineering analysis codes such as SAM as well as extensive functionality for submitting, monitoring, and interacting with the codes through an intuitive graphical user interface (GUI). The common user interface provided by SNAP minimizes the learning curve for engineers starting with a new analysis code and provides an intuitive framework for transitioning between different analysis codes. SNAP provides a powerful but intuitive interface to facilitate access to advanced modeling and simulation tools for inexperienced users. Unlike many “form based” GUI’s, SNAP maps each engineering code’s component input to an internal database which manages all component input parameters along with component interconnections. This level of abstraction permits SNAP to support several advanced capabilities such as renodalization, model validation and consistency checks, embedded documentation, model notebook generation, data ownership and reviewer tracking, and variable assignment for inputs to name a few. SNAP includes a built-in Python interpreter and is interfaced to several commercial and open source packages including CPython, MATLAB/OCTAVE, Microsoft Office, Open Office, and SANDIA’s DAKOTA package which provides Uncertainty Quantification analysis through the SNAP plug-ins. Phase I of this project involved development a fully functional basic SAM plug-in to SNAP. This plug-in provides the ability to import existing models, graphically construct, edit and submit models using SNAP’s extensive functionality.

99 GENERAL AND MISCELLANEOUS↗

Insights from Smart Meters. Ramp-up, dependability, and short-term persistence of savings from Home Energy Reports

Smart meters, smart thermostats, and other new technologies provide previously unavailable high-frequency and location-specific energy usage data. Many utilities are now able to capture real-time, customer specific hourly interval usage data for a large proportion of their residential and small commercial customers. These vast, constantly growing streams of rich data (or, “big data”) have the potential to provide novel insights into key policy questions about how people make energy decisions. The richness and granularity of these data enable many types of creative and cutting-edge analytics. Technically sophisticated and rigorous statistical techniques can be used to pull useful insights out of this high-frequency, human-focused data. In this series, we call this “behavior analytics.” This kind of analytics has the potential to provide tremendous value to a wide range of energy programs. For example, disaggregated and heterogeneous information about actual energy use allows energy efficiency (EE) and/or demand response (DR) program implementers to target specific programs to specific households; enables evaluation, measurement and verification (EM&V) of energy efficiency programs to be performed on a much shorter time horizon than was previously possible; and may provide better insights into the energy and peak hour savings associated with EE and DR programs (e.g., behavior-based (BB) programs). The goal of this series is to enable evidence-based and data-driven decision making by policy makers and industry stakeholders, including program planners, program administrators, utilities, state regulatory agencies, and evaluators. We focus on research findings that are immediately relevant.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Disruption avoidance via island suppression: the crucial roles of DIII-D and foundational research

The FESAC long range plan calls out disruption avoidance and mitigation as key remaining technical gaps. In discussing the roles of DIII-D and NSTX-U, the FESAC long range plan says “Additional research on these facilities, in combination with private and international collaborations, continuing support of existing university tokamak programs, and utilization of US expertise in theory and simulation, is needed to find solutions to remaining technical gaps. These gaps include disruption prediction, avoidance, and mitigation …”. Disruptions pose an existential threat to ITER and to FPPs. For a fusion reactor, unplanned shutdowns caused by disruptions will be a significant barrier to connecting such a reactor to the electric grid, even if disruption mitigation is successful. Disruption studies for ITER in recent years have largely focused on disruption mitigation (e.g., pellet injection), motivated by near-term deadlines for finalizing the design of the mitigation hardware. It is recognized, however, that mitigation alone will not suffice. The 2022 U.S. ITER Research Needs Workshop Report states that ”[d]isruptions are considered the largest threat to the ITER Research Program”, and that “[m]itigation should be a last resort”. As we discuss below, there are unresolved foundational issues that play a critical role in avoidance, and DIII-D is an ideal device for generating the data needed to address these issues.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Stakeholder Transportation Scorecard: Reviewing Nevada's Recommendations for Enhancing the Safety and Security of Nuclear Waste Shipments - 13518

As a primary stakeholder in the Yucca Mountain program, the state of Nevada has spent three decades examining and considering national policy regarding spent nuclear fuel and high-level radioactive waste transportation. During this time, Nevada has identified 10 issues it believes are critical to ensuring the safety and security of any spent nuclear fuel transportation program, and achieving public acceptance. These recommendations are: 1) Ship the oldest fuel first; 2) Ship mostly by rail; 3) Use dual-purpose (transportable storage) casks; 4) Use dedicated trains for rail shipments; 5) Implement a full-scale cask testing program; 6) Utilize a National Environmental Policy Act (NEPA) process for the selection of a new rail spur to the proposed repository site; 7) Implement the Western Interstate Energy Board (WIEB) 'straw man' process for route selection; 8) Implement Section 180C assistance to affected States, Tribes and localities through rulemaking; 9) Adopt safety and security regulatory enhancements proposed states; and 10) Address stakeholder concerns about terrorism and sabotage. This paper describes Nevada's proposals in detail and examines their current status. The paper describes the various forums and methods by which Nevada has presented its arguments and sought to influence national policy. As of 2012, most of Nevada's recommendations have been adopted in one form or another, although not yet implemented. If implemented in a future nuclear waste program, the State of Nevada believes these recommendations would form the basis for a successful national transportation plan for shipments to a geologic repository and/or centralized interim storage facility. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Machine Learning-Based Anomaly Detection for Load Forecasting Under Cyberattacks

Accurate load forecasting can create both economic and reliability benefits for power system operators. However, the cyberattack on load forecasting may mislead operators to make unsuitable operational decisions for the electricity delivery. To effectively and accurately detect these cyberattacks, this paper develops a machine learning-based anomaly detection (MLAD) methodology. First, load forecasts provided by neural networks are used to reconstruct the benchmark and scaling data by using the k-means clustering. Second, the cyberattack template is estimated by the naive Bayes classification based on the cumulative distribution function and statistical features of the scaling data. Finally, the dynamic programming is utilized to calculate both the occurrence and parameter of one cyberattack on load forecasting data. Here, a widely used symbolic aggregation approximation method is compared with the developed MLAD method. Numerical simulations on the publicly load data show that the MLAD method can effectively detect cyberattacks for load forecasting data with relatively high accuracy. Also, the robustness of MLAD is verified by thousands of attack scenarios based on Monte Carlo simulation.

97 MATHEMATICS AND COMPUTING↗

Existing Whole-House Case Study: Evaluation of Missed Energy Saving Opportunity Based on Illinois Home Performance Program Field Data: Homeowner Selected Upgrades vs. Cost-Optimized Solutions, Chicago, Illinois

Expanding on previous research by PARR, this study compares measure packages installed during 800 Illinois Home Performance with ENERGY STAR® (IHP) residential retrofits to those recommended as cost-optimal by Building Energy Optimization (BEopt) modeling software. In previous research, cost-optimal measure packages were identified for 15 Chicagoland single family housing archetypes, called housing groups. In the present study, 800 IHP homes are first matched to one of these 15 housing groups, and then the average measures being installed in each housing group are modeled using BEopt to estimate energy savings. For most housing groups, the differences between recommended and installed measure packages is substantial. By comparing actual IHP retrofit measures to BEopt-recommended cost-optimal measures, missed savings opportunities are identified in some housing groups; also, valuable information is obtained regarding housing groups where IHP achieves greater savings than BEopt-modeled, cost-optimal recommendations.

Air Sealing↗

Pre-Commercial Scale-Up of a Gas-Fired Absorption Heat Pump

The project sought to advance the maturity of SMTI’s 80 kBTU/hr residential space and water heating GAHP from the engineering prototype stage (TRL-7) to pre-production readiness by addressing manufacturing, balance of system design and installation, cost, reliability, and field application questions. As part of this project, the project team has: (1) Matured the design package for a commercially ready product (2) Demonstrated compliance with relevant ANSI standards (3) Completed manufacturing and assembly process specifications (4) Completed total production cost estimates and capital equipment requirements (5) Initiated component and system level reliability assessments (6) Completed a small field demonstration including measured performance, installation requirements and expected costs, and customer/key stakeholder feedback. (7) Completed a Techno-economic analysis for representative applications and climate zones, including justification for utility incentive programs. (8) Completed a market intelligence report. Scope of Work: A multi-faceted project was completed that included: (a) design for manufacturing tasks for both the sealed system and balance of system, (b) development and trial of key manufacturing processes and techniques, (c) evaluation of component and system level reliability, (d) exploration of make/buy decisions including impact on cost and required capital. Additionally, (e) installation and monitoring of a small number of field test units was completed to demonstrate energy savings and collect customer/installer feedback, and (f) a focused market research task was completed to explore potential barriers and improve market introduction plans. These tasks addressed many of the remaining technical risks regarding long-term reliability, verification of manufacturing cost estimates and identification of cost concerns, identify installation and balance of system design criteria necessary to achieve energy savings and installed cost goals, and identify market barriers and strategies prior to product market introduction.

03 NATURAL GAS↗

Evaluation of Missed Energy Saving Opportunity Based on Illinois Home Performance Program Field Data: Homeowner Selected Upgrades Versus Cost-Optimized Solutions

Expanding on previous research by PARR, this study compares measure packages installed during 800 Illinois Home Performance with ENERGY STAR® (IHP) residential retrofits to those recommended as cost-optimal by Building Energy Optimization (BEopt) modeling software. In previous research, cost-optimal measure packages were identified for 15 Chicagoland single family housing archetypes. In the present study, 800 IHP homes are first matched to one of these 15 housing groups, and then the average measures being installed in each housing group are modeled using BEopt to estimate energy savings. For most housing groups, the differences between recommended and installed measure packages is substantial. By comparing actual IHP retrofit measures to BEopt-recommended cost-optimal measures, missed savings opportunities are identified in some housing groups; also, valuable information is obtained regarding housing groups where IHP achieves greater savings than BEopt-modeled, cost-optimal recommendations. Additionally, a measure-level sensitivity analysis conducted for one housing group reveals which measures may be contributing the most to gas and electric savings. Overall, the study finds not only that for some housing groups, the average IHP retrofit results in more energy savings than would result from cost-optimal, BEopt recommended measure packages, but also that linking home categorization to standardized retrofit measure packages provides an opportunity to streamline the process for single family home energy retrofits and maximize both energy savings and cost effectiveness.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Evaluation of Missed Energy Saving Opportunity Based on Illinois Home Performance Program Field Data: Homeowner Selected Upgrades vs. Cost-Optimized Solutions; Chicago, Illinois (Fact Sheet)

Expanding on previous research by PARR, this study compares measure packages installed during 800 Illinois Home Performance with ENERGY STAR (IHP) residential retrofits to those recommended as cost-optimal by Building Energy Optimization (BEopt) modeling software. In previous research, cost-optimal measure packages were identified for fifteen Chicagoland single family housing archetypes, called housing groups. In the present study, 800 IHP homes are first matched to one of these fifteen housing groups, and then the average measures being installed in each housing group are modeled using BEopt to estimate energy savings. For most housing groups, the differences between recommended and installed measure packages is substantial. By comparing actual IHP retrofit measures to BEopt-recommended cost-optimal measures, missed savings opportunities are identified in some housing groups; also, valuable information is obtained regarding housing groups where IHP achieves greater savings than BEopt-modeled, cost-optimal recommendations. Additionally, a measure-level sensitivity analysis conducted for one housing group reveals which measures may be contributing the most to gas and electric savings. Overall, the study finds not only that for some housing groups, the average IHP retrofit results in more energy savings than would result from cost-optimal, BEopt-recommended measure packages, but also that linking home categorization to standardized retrofit measure packages provides an opportunity to streamline the process for single family home energy retrofits and maximize both energy savings and cost-effectiveness.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗