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DOE OSTI2022

CLARIFYING THE NEXUS BETWEEN LIFE CYCLE ASSESSMENT AND CIRCULARITY INDICATORS: A SETAC/ACLCA INTEREST GROUP

Purpose Improving the circularity of resources is important to the sustainability of consumer goods. Current research has indicated that circularity practices and circular economy (CE) methods do not always reduce environmental impacts. The aim of this research is to investigate the adoption of the life cycle assessment (LCA) methodology to improve the environmental impacts of circularity practices. Methods As part of the Society for Environmental Toxicology And Chemistry (SETAC) forum, an interest group (IG) on Circularity and LCA was formed in partnership with the American Center for Life Cycle Assessment (ACLCA) to tackle methodological and technical issues related to circularity in LCA. The IG’s research approach is summarized in four key steps: defining goals and objectives, literature review and gap analysis, ideation, and experimentation. The twelve active persons within this IG meet monthly and have been divided into four sub-working groups (sub-WGs) so that complementary tasks can be completed concurrently in an effective manner. Each sub-WG meets monthly and reports back to the main group for collaboration and brainstorming to meet the research objectives. Results and discussion First, the sub-WG #1, focusing on the “pool of circularity and LCA-based indicators”, analyzed the complementarity between two of the most used circularity indicators and LCA. Second, the sub-WG #2, working on the “evaluation of CE loops performance through LCA”, built a mind map of pain points that reflect the challenges that the LCA practitioners face when combining LCA with CE approaches. Third, the sub-WG #3, dealing with the “trade-offs between circularity and sustainability”, highlighted key alignments and/or conflicts between circularity and sustainability performance depending on the scope, product, industry, or system of analysis. Fourth, the sub-WG #4, focusing on “business and industrial cases”, plans to leverage the knowledge base developed within this IG to develop use cases documenting the benefits and challenges associated with CE-related loops modeling in LCA. Conclusions The first findings of this SETAC/ACLCA IG provide a state-of-the-art overview of the synergists of LCA methodology and the CE measurement frameworks reported in the literature. To move forward and capitalize on the first findings, one valuable point will be to discuss and provide concrete solutions to the pain points that emerged when considering circularity in LCA. Eventually, the knowledge base and resources created within this IG ultimately aim to support the proper application of LCA for practitioners in CE contexts, and could provide relevant inputs for the ISO Technical Committee ISO/TC 323 working on the upcoming standard for the measurement of CE performance.

Life cycle assessment, circular economy, circulari↗

DOE OSTI2022

Decarbonization scenarios of the U.S. Electricity system and their costs

Decarbonizing the electricity system to zero-carbon emission is crucial for climate change mitigation. Previous studies have shown that such a transition in the United States (U.S.) may lead to higher system cost compared to a business-as-usual case, but it is not well-known how the cost of electricity generation varies at sub-regional level under the transition, and studies have rarely evaluated the trade-off between the cost and avoided climate damages, as well as the potential roles of negative emission technologies (NETs) in the electricity decarbonization. In this work, we present a regionally resolved national model to quantify the cost of decarbonizing the U.S. electricity system under a set of possible scenarios. The results show that, compared to the reference scenario without a decarbonization policy, reaching zero CO 2 emission by 2050 would incur, depending on the scenarios, 335-494 billion USD additional cost to the U.S. electric power sector during 2020-2050. The regional costs of electricity generation ranges from 2.4 to 4.7 cent/kWh, largely due to the generation profiles and renewable resources availability of those regions. The additional costs can be translated to an average CO 2 abatement cost of 29-59 USD/metric ton CO 2 (with 2%-7% discount rates), which are comparable to the social cost of carbon in the literature at around 4% discount rate. The results also show that the cost of mitigating the last few percent CO 2 emission from the U.S. electricity system may exceed the costs of NETs, indicating an opportunity for NETs to contribute to electricity decarbonization.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Application of Site Controllers for Electrification of Commercial Fleet Vehicles

Electrification of transportation fleets presents a significant challenge for commercial customers. These challenges can be specific to region, weather, operating schedule, charging infrastructure, and other factors. This paper presents the value of integrating a site controller to monitor the health of assets and co-optimize the operation of commercial sites with multiple distributed energy resource technologies and electric vehicle fleets. The tests demonstrate smart-charging and vehicle-to-building uses compared to business-as-usual cases. The secondary objectives of power management for the customer vehicle are optimized by a planning tool (REopt) and integrated using the site controller. Any deviations from the planned dispatch are addressed by the real-time controllers offering tertiary controls, such as energy management, and limiting the reverse power flow (back into the grid). The results indicate that site controllers offer an efficient solution to manage the health of the connected assets and a scalable means to optimize the operations of a commercial customer with electrified transportation fleets.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗

DOE OSTI2022

DSO+T: Valuation Methodology and Economic Metrics (DSO+T Study: Volume 4)

This report summarizes a rigorous valuation analysis methodology used by the Distribution System Operator with Transactive (DSO+T) study to estimate the financial benefits and costs of adopting Transactive Energy coordination of distributed energy resources for key stakeholders (for example distribution system operators and customers). This was achieved by modeling the value exchanges between stakeholders and determining the annualized costs and revenues experienced by stakeholders, enabling the evaluation of overall impact on stakeholder’s annualized cash flow. Extensive work was conducted developing methods to estimate the operating costs of distribution system operators at a level of granularity that would allow the financial impact of implementing a transactive energy approach to be estimated. This work included developing parametric models for labor and software costs, distribution system capital and maintenance costs, growth rates, and factors to determine annualized costs of capital investments. Simulation results were used to calculate wholesale energy costs and revenues from retail sales. Valuation analysis methods were also developed for other stakeholders including customers, the transmission system operator, independent system operator, and generators. The resulting capability allows a complete mapping of the flow of financial value between stakeholders that can be directly integrated with the results of demand flexibility simulations. Example results are provided for a business-as-usual case and compared to a transactive energy case as well as to actual cost data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Oak Ridge National Laboratory Neutron Spin Echo Beamline on NB-2

Neutron Spin Echo (NSE) spectroscopy uniquely measures the Q-dependence of slow relaxation dynamics, and having such a machine at HFIR will advance polarized neutron spectroscopy and promote the study of biophysical and energy materials using neutrons. The 2018 Instrument Advisory Board (IAB) advises Neutron Sciences Directorate, ORNL to upgrade the cold neutron delivery system at HFIR, addressing geometrical challenges in neutron transfer from the bright cold source. This is being optimized now: the entrance to the guide system is moving closer to the source, and more guides are being added. However, there are still significant challenges to making the cold flux at the sample world-class. With the proposed guide system, NB-2 can deliver more than 10 6 polarized neutrons per cm 2 /sec below 8Å, and probably 10Å with further optimization. With no potential for running user experiments with neutrons longer than 15Å, the utility of such a machine for biological studies is limited. However, there is a large demand for this class of spectrometer in materials science, chemical engineering, and nanotechnology. Workshops held over the past decade and the three-source vision have highlighted the community's need for a low-angle, high-energy resolution spectrometer at HFIR. A detailed design study of this spectrometer is needed, focusing on optimizing the neutron delivery system for SANS-type studies. This neutron spectrometer would complement studies already performed on both SNSNSE and BASIS by overlapping and extend the dynamic range accessible, while acknowledging the proposed machine, EXPANSE, at the Second Target Station. Two technologies currently exist for such a spectrometer: traditional DC solenoids like those on BL-15 at SNS and IN15 at the ILL, and RF-flipper-based machines similar to RESEDA at FRMII. Either instrument would satisfy the scientific justification. However, there are strong business and scientific cases to utilize the thermal flux, the resonant expertise developed at ORNL, and the potential to utilize an entangled beam of neutrons to probe quantum matter by adopting the neutron resonant spin-echo configuration.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Can Collaboration Succeed in Siting a Spent Nuclear Fuel Facility in the United States?—A Challenge in Political Sustainability

We examine the U.S. Department of Energy (DOE)’s collaborative process to locate, build, and operate one or more federal consolidated interim storage facilities (FCISFs) for commercial U.S. spent nuclear fuel—instead of continuing to store the material at over 70 nuclear reactor sites. Technocratic siting of nuclear facilities in the U.S., most of which did not involve meaningful public participation, was not successful. We consider increasing pressure to find at least one FCISF site, as well as the critical role of trust in engaging communities and reaching agreement—leading some observers to assert that DOE is in the “trust building business”, not the siting business. We present case studies with the following: (1) illustrating community engagement that led to a more satisfactory outcome than had been anticipated (Fernald); (2) a planned voluntary process that failed to produce an operating CISF (Office of the Nuclear Waste Negotiator); and (3) a site that demonstrates the ongoing need for negotiations to keep a site open and operational (Waste Isolation Pilot Plant). The essay concludes with the observation that a collaboration-based siting effort can succeed in the U.S., but that five main challenges—related to trust and requiring patience—will need to be addressed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Long-run Marginal CO2 Emission Rates Workbooks for 2020 Standard Scenarios Cambium Data

This dataset has been superseded by a new set of workbooks that can be found here: https://data.nlr.gov/submissions/183 These workbooks contain modeled estimates of long-run marginal CO2 emission rates (LRMER) for the contiguous United States. The LRMER is an estimate of the rate of emissions that would be either induced or avoided by a long-term (i.e., more than several years) change in electrical demand. It incorporates both the projected changes to the electric grid, as well as the potential for an incremental change in electrical demand to influence the structural evolution of the grid (i.e., the building and retiring of capital assets, such as generators and transmission lines). It is therefore distinct from the more-commonly-known short-run marginal, which treats grid assets as fixed. In addition to year-over-year data, the Levelized LRMER worksheet within each workbook is set up to produce a levelized long-run marginal emission rate based on user-provided inputs. These levelized LRMER values are intended for analysts to use when estimating the emissions induced (or avoided) by a long-term change in end-use electricity demand. Three future scenarios are provided in separate workbooks: A Mid-case (i.e., business-as-usual), and two scenarios with relatively higher or lower renewable energy costs. For more details on these scenarios, see the Standard Scenarios 2020 Report ( https://www.nlr.gov/docs/fy21osti/77442.pdf ). For more data underlying each scenario, see the Standard Scenarios 2020 project (Cambium data) at https://cambium.nlr.gov/ . This data was produced as part of the Cambium project. For more details about the methodology, see the Cambium Documentation: Version 2020 ( https://www.nlr.gov/docs/fy21osti/78239.pdf ). This data is planned to be updated annually. Information on the latest versions can be found at https://www.nlr.gov/analysis/cambium.html .

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2002

A Response Surface Methodology for Bi-Level Integrated System Synthesis (BLISS)

The report describes a new method for optimization of engineering systems such as aerospace vehicles whose design must harmonize a number of subsystems and various physical phenomena, each represented by a separate computer code, e.g., aerodynamics, structures, propulsion, performance, etc. To represent the system internal couplings, the codes receive output from other codes as part of their inputs. The system analysis and optimization task is decomposed into subtasks that can be executed concurrently, each subtask conducted using local state and design variables and holding constant a set of the system-level design variables. The subtasks results are stored in form of the Response Surfaces (RS) fitted in the space of the system-level variables to be used as the subtask surrogates in a system-level optimization whose purpose is to optimize the system objective(s) and to reconcile the system internal couplings. By virtue of decomposition and execution concurrency, the method enables a broad workfront in organization of an engineering project involving a number of specialty groups that might be geographically dispersed, and it exploits the contemporary computing technology of massively concurrent and distributed processing. The report includes a demonstration test case of supersonic business jet design.

Altus, Troy David↗

DOE OSTI2023

Historical Pattern Analysis of Global Geothermal Power Capacity Development: Preprint

Between 1913 and 1958, Italy was the only country with an operational geothermal power plant until New Zealand installed its first plant in 1958. At present, 24 countries are involved in the geothermal power market, and they have a combined installed capacity of 16,127 GW. This study analyzes the historical patterns of geothermal power capacity in the world and in individual countries to investigate the ideal global geothermal development pattern by examining the annual cumulative capacity (ACC) and the annual capacity addition (ACA) graphs of the historical development of geothermal power capacity in 24 countries. First, the global patterns are analyzed using these graphs in five periods (1945-1957, 1958-1976, 1977-1991, 1992-2002, and 2003-2020) that are marked by a series of characteristics of ACA peaks separated by two major troughs. Then, five characteristic patterns are developed in five periods globally. These patterns correspond to the early-stage linear, the first acceleration, the first steady-state linear, the second acceleration, and the second steady-state linear developments. A positive relationship exists between global patterns and the 5-year shifted oil-price curve: two major factors influenced global development: 1) increasing oil prices and increasing awareness of global climate change, and 2) global development of geothermal power. Last, we investigate these patterns in each country. The top ten countries, which comprise 93.3% of the world's total installed capacity are separated into five groups based on the availability and characteristics of patterns globally developed in five periods. Group-1 (the United States) has an installed capacity of 3,794 MW, Group-2 (Mexico and Philippines) 963-1935 MW, Group-3 (New Zealand, Italy, Iceland, and Japan) 601-1,037 MW, and Group-4 (Indonesia, Kenya, and Turkiye) 944-2,356 MW. The remaining 14 countries (6.7%), which are called Group 5, are still in an immature stage and have installed capacities of 7-262 MW and are not involved in pattern analysis. Overall, geothermal power in the world is in its third stage of development, which had its peak development after 1977. A fourth development peak may be expected to occur after this through business-as-usual cases. The biggest barrier to the development of the global geothermal power market is the risk associated with exploration and drilling. If risk mitigation systems and funds are employed, the growth of geothermal power production projects could accelerate.

GEOTHERMAL ENERGY↗

DOE OSTI2023

Historical Pattern Analysis of Global Geothermal Power Capacity Development

GEOTHERMAL ENERGY↗

NASA NTRS1997

Hierarchical Modeling and Robust Synthesis for the Preliminary Design of Large Scale Complex Systems

Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis; Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration; and Noise modeling techniques for implementing robust preliminary design when approximate models are employed. Hierarchical partitioning and modeling techniques including intermediate responses, linking variables, and compatibility constraints are incorporated within a hierarchical compromise decision support problem formulation for synthesizing subproblem solutions for a partitioned system. Experimentation and approximation techniques are employed for concurrent investigations and modeling of partitioned subproblems. A modified composite experiment is introduced for fitting better predictive models across the ranges of the factors, and an approach for constructing partitioned response surfaces is developed to reduce the computational expense of experimentation for fitting models in a large number of factors. Noise modeling techniques are compared and recommendations are offered for the implementation of robust design when approximate models are sought. These techniques, approaches, and recommendations are incorporated within the method developed for hierarchical robust preliminary design exploration. This method as well as the associated approaches are illustrated through their application to the preliminary design of a commercial turbofan turbine propulsion system. The case study is developed in collaboration with Allison Engine Company, Rolls Royce Aerospace, and is based on the Allison AE3007 existing engine designed for midsize commercial, regional business jets. For this case study, the turbofan system-level problem is partitioned into engine cycle design and configuration design and a compressor modules integrated for more detailed subsystem-level design exploration, improving system evaluation. The fan and low pressure turbine subsystems are also modeled, but in less detail. Given the defined partitioning, these subproblems are investigated independently and concurrently, and response surface models are constructed to approximate the responses of each. These response models are then incorporated within a commercial turbofan hierarchical compromise decision support problem formulation. Five design scenarios are investigated, and robust solutions are identified. The method and solutions identified are verified by comparison with the AE3007 engine. The solutions obtained are similar to the AE3007 cycle and configuration, but are better with respect to many of the requirements.

Koch, Patrick N.↗

DOE OSTI2020

Southpointe Business Park and City of Pittsburgh’s Almono District: Case Studies in Deep Direct Use of Geothermal Energy

Geothermal TRS

TRS↗

DOE OSTI2022

Case studies of robots and automation as health/safety interventions in small manufacturing enterprises

This article reviews the experiences of 63 case studies of small businesses (<250 employees) with manufacturing automation equipment acquired through a health/safety intervention grant program. The review scope included equipment technologies classified as industrial robots (n = 17), computer numerical control (CNC) machining (n = 29), or other programmable automation systems (n = 17). Descriptions of workers' compensation (WC) claim injuries and identified risk factors that motivated the acquisition of the equipment were extracted from grant applications. Other aspects of the employer experiences, including qualitative and quantitative assessment of effects on risk factors for musculoskeletal disorders (MSD), effects on productivity, and employee acceptance of the intervention were summarized from the case study reports. Case studies associated with a combination of large reduction in risk factors, lower cost per affected employee, and reported increases in productivity were CNC stone cutting system, CNC/vertical machining system, automated system for bottling, CNC/routing system for plastics products manufacturing, and a CNC/Cutting system for vinyl/carpet. Six case studies of industrial robots reported quantitative reductions in MSD risk factors in these diverse manufacturing industries: snack foods; photographic film, paper, plate, and chemical; machine shops; leather goods and allied products; plastic products; and iron and steel forging. Furthermore, this review of health/safety intervention case studies indicates that advanced (programmable) manufacturing automation, including industrial robots, reduced workplace musculoskeletal risk factors, and improved process productivity in most cases.

42 ENGINEERING↗

DOE OSTI2025

Day-Ahead Forecasting with Federated LSTM to Plan Energy Sharing in a Community Microgrid

Energy balancing in microgrids is a key enabler of resilience. Community microgrids located close to each other have the added benefit of networking and sharing surplus energy, if available. Such complex decision-making runs on optimization that requires reliable short-term (up to very-short-term) forecasts of energy generation and consumption for scheduling or trading. Each microgrid may also opt to not expose their sensitive data such as consumption patterns of individual businesses or residences. This paper investigates a federated approach to dayahead forecasting that trains naive long short-term memory (LSTM) at each business in a microgrid and aggregates weights at the microgrid controller using proximal regularization. This approach ensures that the controller has access only to energy surplus/deficit and not the actual generation or consumption values, avoiding unwanted exposure of sensitive data. A community microgrid in Adjuntas, Puerto Rico with 3 businesses is selected as a case study with a laboratory-scale computing setup. A central LSTM forecaster, where sensitive data from businesses are aggregated at the controller, is implemented as a baseline for qualifying the results. This work serves as a proof-of-concept for scaling the approach to networked and nested microgrids with more complex control options.

Sundararajan, Aditya [ORNL] (ORCID:000000033577854↗

DOE OSTI2020

Energy Consumption and Cost Reduction of Future Light-Duty Vehicles through Advanced Vehicle Technologies: A Modeling Simulation Study Through 2050

The U.S. Department of Energy’s (DOE’s) Vehicle Technologies Office (VTO) and Hydrogen and Fuel Cell Technologies Office (HFTO) aim to develop sustainable, affordable and efficient technologies for transportation of goods and people. Translating investments in advanced transportation component technologies and powertrains to estimate vehicle-level fuel savings potential is critical for understanding DOE’s impact. In this work, we simulated technologies funded by VTO and HFTO for light duty vehicles. The simulations were performed across: Multiple powertrain configurations (i.e., conventional, power-split, extended-range electric vehicle, battery electric drive, and fuel-cell vehicles), Vehicle classes (i.e., compact car, midsize car, small sport utility vehicle [SUV], midsize SUV, and pickup trucks); and Fuels (i.e., gasoline, diesel, hydrogen, and battery electricity). These various technologies are assessed for six different timeframes: laboratory years 2015, 2020, 2025, 2030, and 2045. A delay of 5 years is assumed between laboratory year and model year (year technology is introduced into production). Finally, uncertainties are included for both technology performance and cost aspects by considering two cases: Low case, aligned with DOE technology manager estimates of expected original equipment manufacturer (OEM) improvements based on regulations, business as usual; and High case, aligned with aggressive technology advancements based on R&D targets developed through support by VTO & HFTO. These scenarios are not intended as predictions of future performances. The energy and cost impact of different technologies were estimated using Autonomie (www.autonomie.net), Argonne vehicle system simulation tool. Autonomie is a state-of-the-art vehicle system simulation tool used to assess the energy consumption, performance and cost of multiple advanced vehicle technologies across classes (from light to heavy duty), powertrains (from conventional to HEVs, FCEVs, PHEVs and BEVs), components and control strategies. Autonomie is packaged with a complete set of vehicle models for a wide range of vehicle classes, powertrain configurations and component technologies, including vehicle level and component level controls. These controls were developed and calibrated using dynamometer test data. Autonomie has been used to support a wide range of studies including analyzing various component technologies, sizing powertrains components for different vehicle requirements, comparing the benefits of powertrain configurations, optimizing both heuristic and route based vehicle energy control and predicting transportation energy use when paired with a traffic modeling tool such as POLARIS. This report documents the assumptions and estimates the vehicle-level energy consumption benefits and associated technology costs for the various types of light duty vehicles. All details of vehicle assumptions and simulation results are available in the spreadsheets accompanying this report.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Low-Cost Preform and Molding Processes

The entry cost for prototyping a composite component for manufacture using automated, high rate processes is prohibitively expensive in many cases, especially for small business, where tooling costs may be several $100k. Discussions with industry also indicate that many small companies, tier 1 and 2 suppliers, have an interest to mold composite parts but do not want to deal with the capital cost, material handling issues, and labor associated with dry fiber preforming operations. While the molders may locate near the end user for logistics reasons, it may be more cost effective for the performer to remain regional and invest in capital equipment to support preform automation, thus keeping costs to a minimum. This project was designed to explore and demonstrate several options to meet these industry needs. Dry fiber preforming approaches were evaluated which allow for low pressure resin infusion, single sided tooling options such a vacuum assisted resin transfer molding (VARTM) or low pressure resin transfer molding (RTM-light). Unlike sheet molding compound, SMC compression molding where typical molding pressures of 1000 psi are required to push material into the desired location; positioning of a dry fiber preform into the desired location on the tool allows for low molding pressures of 10-50 psi. Lower molding pressures allow for use of low cost, additive fabrication of polymeric tooling. Polymeric tooling is suitable for rapid part prototyping and limited production. Dry fiber preforming approaches evaluated included use of commercial chopped strand mat, robotic chopper gun deposition, and continuous fiber preform augmentation using tailored fiber placement (TFP). Use of chopped strand mat does not require a robotic deposition method, however a cutting table is generally required and there is typically 20-30% scrap generation. While various fiber areal weights are available, the preform is not readily optimized for minimal fiber use or weight savings. In contrast, a robotic chopper gun approach allows for localized deposition where fiber is required to meet structural requirements. The robotic method is highly automated and minimizes fiber scrap, however the capital cost of the equipment and engineering labor for programming can result in higher preform cost compared to chopped strand mat in certain cases depending on preform complexity. Dry fiber preforming using the robotic chopper gun method allows for creation of three dimensional forms. This approach may be ideal for molding in-house, or if the preforms stack together densely to allow for efficient shipping. Applications evaluated for this program considered trade-off between fabrication of a fully 3D preform versus production of a flat preform which is designed to readily drape into the final desired shape. Such a preform design greatly simplifies robotic programming and requires no specialized tooling. The flat preforms are easily stacked and shipped to the final molding location. Flat preforms are much easier to augment with TFP continuous fiber to provide local reinforcement. The demonstration and evaluation of these preforming and tooling methods were completed on three component applications. The first application was a battery box cover for an electric vehicle which was highly three dimensional. The second demonstrator article was comprised of complex contours and was used to demonstrate the use of TFP and RTM-light molding process. The third demonstration article was the roof of an operator’s cab for large construction equipment. The roof is relatively flat however it is comprised of complex changes in thickness which clearly demonstrate the advantage of robotic chopper gun approach as compared to using numerous preform layers of chopped strand mat. The cost trades for the various preforming methods are summarized to help guide the reader as to preforming method considerations. Finally, these demonstrations all used glass fiber roving. A fourth, exploratory task was added to evaluate the ability to make preforms using Zoltek’s carbon fiber split tow roving. We were able to adapt the chopper gun to make flat preforms for laminate testing, but further development effort would be required to make suitable preforms.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Advancing Energy Equity Considerations in Distribution Systems Planning

Current distribution system planning (DSP) processes do not explicitly account for energy equity considerations, such as who is most affected by power system burdens, where those burdens are concentrated, and what investments can be made to improve baseline conditions. This paper proposes an iterative framework for advancing energy equity as an objective of the DSP process, showing how measurement strategies, or metrics (informed by conceptual foundations of energy justice), can be applied to benchmark equity performance at various stages. This methodology is applied for equity-aware distributed energy resource (DER) hosting capacity analysis and outage analysis to provide critical insights on infrastructure upgrade decisions compared to a business-as-usual (BAU) case. The analysis is performed on a taxonomy feeder representing the West Coast urban/semi-urban system with augmentation of electric vehicles (EVs) and rooftop solar photovoltaic (PV) generators. The study considers disadvantaged community (DAC) and non-disadvantaged community (NDAC) load regions to enable equity-aware simulations. The results demonstrate how equity-aware planning could reveal the limitations of the traditional DSP process as DAC regions are found to have lower DER hosting capacity and higher outage vulnerability. Overall, this work provides insights on the need to incorporate energy equity as an integral part of the DSP process.

Energy Equity, Distribution System Planning, DER a↗

DOE OSTI2024

PV Generation and Load Forecasting for Adjuntas PR Community Microgrids

Existing frameworks to forecast time-series photovoltaic (PV) output power and consumer load for microgrid operations and controls assume a near-continuous availability of real-time input features from the field assets such as PV inverters, energy meters, and weather station. These incoming data points are used to periodically retrain models and update forecast snapshots over a moving horizon window, be it one hour-ahead, one-day ahead, or one-week ahead. However, such frameworks are not resilient to disruptions in data availability caused by losses in communications between the field sensors and data loggers. Hence, there is a need for programs that assume no availability of real-time microgrid asset data and still make reliable forecasts that can be used for decision-making. Such programs would be apt to function in extreme weather events such as hurricanes and would use lightweight recursive time-series models to independently forecast solar irradiance and ambient temperature, then compute PV power from those forecasts, as well as independently forecast consumer load. The codebase performs forecasting for the scenario of when the microgrid does not have a reliable access to forecasts or real-time observations of solar irradiance (I) and ambient temperature (AT) and load (Load) to be able to adequately forecast, in real-time, the PV power production or a business' load. In this case, using historical values of PV power and load, a univariate forecasting of generation and consumption are respectively made. The use-case in particular has two sub-scenarios: one, a normal 7-day ahead forecast where the unavailability of real-time data is assumed due to infrastructure issues such as loss of communication or sensor maintenance or service downtimes. Whereas a hurricane-caused unavailability of real-time data requires a second model trained specifically on historical hurricane days to be able to capture the extreme day behavior of generation in particular, and load if applicable. A gradient boosted regression tree comprises an ensemble of additive models that map between the input of historical values (be it irradiance, temperature, or load) and their corresponding output forecasts of a given horizon such that the individual learner predictions are summed up over the total number of such learners in the ensemble to produce an aggregate forecast. A weighting mechanism is applied to the training data in each iteration, where actual and forecast values are compared to penalize incorrect forecasts by increasing the weight and reducing it to reward correct forecasts. The code's benefits are that it: (a) accounts for a contingency where communication loss renders newly measured real-time data unavailable for model tuning and snapshot updates; (b) presents blind forecasting that recursively determines the next time-step value in a horizon using the forecast of the same attribute from a prior step; and (c) employs lightweight models that, once trained, can reliably generalize for different horizons, which make them suitable for enhancing the resilience of field microgrids prone to extreme events that encounter disruptions to data availability.

Sundararajan, Aditya [Oak Ridge National Laborator↗