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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2025

Application of Cyber-Informed Engineering for Protecting BESS

This white paper synthesizes an array of crucial grid services provided by BESS technology, assesses its architecture and communications, and presents a case study for analysis against the principles introduced by Cyber-Informed Engineering (CIE). Furthermore, in walking through the analysis, this paper presents a framework to evaluate risks and solutions when considering BESS components. Asset owners and buyers could perform this analysis to assess their BESS product implementations, alternative inverter-based resources (IBR), and energy management systems (EMS). Battery systems fulfill various roles contingent on the unique market demands and the specific challenges presented by regional grid infrastructures. These roles also vary due to the differing utility models for ownership and operation, which are adapted to meet regional and local capabilities and requirements. Concerns have been raised regarding the potential for adversaries to exploit knowledge of battery operational patterns to orchestrate decisive attacks. However, the security of operational data for these systems may not be the primary vulnerability, as much of this information is already well-understood within the community. Applying a modest degree of subject matter expertise can often yield valuable predictions regarding how a battery will respond under certain conditions, such as grid emergencies, high or low-temperature days, Public Safety Power Shutoff (PSPS) events, and outages. The operational characteristics of batteries are well-documented, and their capabilities, including the risks associated with misoperation and the resulting consequences, are published and understood within the industry. CIE practices represent the next step in gaining functional assurance and providing an acceptable level of risk, regardless of whether a battery vendor can support a trusted and validated supply chain. While this issue has exacerbated supply chain challenges, it is not an isolated condition. This foreign supply route is the primary source of BESS for the U.S. market. Significant efforts are underway through the Bipartisan Infrastructure Law (BIL) to change that. Still, strategic short-term operational mitigations are needed to ensure the security of our operational technology (OT) systems, which are enhanced by instilling trust and are separate from vendors implementing CIE principles.

25 ENERGY STORAGE↗
DOE OSTI2020

Update on the United States Advanced Ultra-Supercritical Program with Full Scale Component Fabrication to Develop Utility Scale Power Plants with 760°C Steam Temperature

Following the successful completion of a 15-year effort to develop and test materials that would allow coal-fired power plants to be operated at advanced ultra-supercritical (A-USC) steam conditions, a United States-based consortium is presently engaged in Phase 2 of a project which includes an advanced manufacturing effort to complete US-based supply chain development for full commercial scale (800-850 MWe) A-USC components made of nickel-based alloys, components operating at up to 760°C. The project, funded under U.S. Department of Energy Award No. DE-FE0025064, falls under the US DOE overall goal to Develop cost-effective, reliable technologies to improve the efficiency of new and existing coal-fired power plants. A-USC steam cycles have the potential to improve cycle efficiency, reduce fuel costs, and reduce greenhouse gas emissions. Current development and demonstration efforts are focused on enabling the construction of A-USC plants, operating with steam temperatures as high as 1400°F (760°C) and steam pressures up to 5000 psi (35 MPa), which can potentially increase cycle efficiencies to 47% HHV (higher heating value), or approximately 50% LHV (lower heating value), and reduce CO 2 emissions by roughly 25%, compared to today’s U.S. fleet. A-USC technology provides a lower-cost method to reduce CO 2 emissions, compared to CO 2 capture technologies, while retaining a viable coal option for owners of coal generation assets. Among the specific goals of Phase 2 of the ComTest Project are to: validate that components made from advanced nickel-based alloys can operate and perform under A-USC conditions accelerate the development of a U.S.-based supply chain for the full complement of A-USC components close the remaining gaps and reduce the risks for manufacturing components from advanced materials for commercial demonstration fabricate full-scale versions of selected key components made of nickel-based alloys validate a qualified U.S. supply chain, to provide greater cost certainty for components obtain American Society of Mechanical Engineers (ASME) code approval for new materials, components and processes Additional benefit: Manufacturing technology will be applicable to other advanced fossil energy high temperature cycles, and can support increased flexibility of existing power plants The ComTest project is managed by Energy Industries of Ohio, and technically directed by the Electric Power Research Institute, Inc., with General Electric designing the A-USC components. As stated earlier, the current phase of the effort is primarily funded by the U.S. Department of Energy, through the National Energy Technology Laboratory. This presentation outlines the motivation for the project, explains the project’s structure and schedule, and provides some of the technical details on the design of the ComTest components.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Update on the United States Advanced Ultra-Supercritical Program with Full Scale Component Fabrication to Develop Utility Scale Power Plants with 760°C Steam Temperature

Following the successful completion of a 15-year effort to develop and test materials that would allow coal-fired power plants to be operated at advanced ultra-supercritical (A-USC) steam conditions, a United States-based consortium is presently engaged in Phase 2 of a project which includes an advanced manufacturing effort to complete US-based supply chain development for full commercial scale (800-850 MWe) A-USC components made of nickel-based alloys, components operating at up to 760°C. The project, funded under U.S. Department of Energy Award No. DE-FE0025064, falls under the US DOE overall goal to Develop cost-effective, reliable technologies to improve the efficiency of new and existing coal-fired power plants. A-USC steam cycles have the potential to improve cycle efficiency, reduce fuel costs, and reduce greenhouse gas emissions. Current development and demonstration efforts are focused on enabling the construction of A-USC plants, operating with steam temperatures as high as 1400°F (760°C) and steam pressures up to 5000 psi (35 MPa), which can potentially increase cycle efficiencies to 47% HHV (higher heating value), or approximately 50% LHV (lower heating value), and reduce CO 2 emissions by roughly 25%, compared to today’s U.S. fleet. A-USC technology provides a lower-cost method to reduce CO 2 emissions, compared to CO 2 capture technologies, while retaining a viable coal option for owners of coal generation assets. Among the specific goals of Phase 2 of the ComTest Project are to: validate that components made from advanced nickel-based alloys can operate and perform under A-USC conditions accelerate the development of a U.S.-based supply chain for the full complement of A-USC components close the remaining gaps and reduce the risks for manufacturing components from advanced materials for commercial demonstration fabricate full-scale versions of selected key components made of nickel-based alloys validate a qualified U.S. supply chain, to provide greater cost certainty for components obtain American Society of Mechanical Engineers (ASME) code approval for new materials, components and processes Additional benefit: Manufacturing technology will be applicable to other advanced fossil energy high temperature cycles, and can support increased flexibility of existing power plants The ComTest project is managed by Energy Industries of Ohio, and technically directed by the Electric Power Research Institute, Inc., with General Electric designing the A-USC components. As stated earlier, the current phase of the effort is primarily funded by the U.S. Department of Energy, through the National Energy Technology Laboratory. This presentation outlines the motivation for the project, explains the project’s structure and schedule, and provides some of the technical details on the design of the ComTest components.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

West Valley Demonstration Project Annual Site Environmental Report (CY2019)

The report, prepared for the U.S. Department of Energy West Valley Demonstration Project office (DOE-WVDP), summarizes the environmental protection program at the WVDP for calendar year (CY) 2019. Monitoring and surveillance of the facilities used by the DOE are conducted to verify protection of public health and safety and the environment. The report is a key component of DOE’s effort to keep the public informed of environmental conditions at the WVDP. The quality assurance protocols applied to the environmental monitoring program ensure the validity and accuracy of the monitoring data. In addition to demonstrating compliance with environmental laws, regulations, and directives, evaluation of data collected in 2019 continued to indicate that WVDP activities pose no threat to public health or safety, or to the environment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

U.S. Solar Siting Regulation and Zoning Ordinances (2025)

A machine readable collection of documented solar siting ordinances at the state and local (e.g., county, township) level throughout the United States. The data were compiled using the Infrastructure Continuous Ordinance Mapping for Planning and Siting Systems (INFRA-COMPASS) tool, which leverages Large Language Models (LLMs) to automate the collection of local codes and ordinances applicable to energy infrastructure. URLs for the ordinance source documents are included in the Solar Ordinances spreadsheet. The GeoPackage file included below contains the jurisdiction shapes for each ordinance. Note that the GeoPackage file is formatted for ingestion by NLR's reVX setbacks tool and therefore does not contain any of the state-level regulations. NOTE: This data was collected with the help of generative AI. The Large Language Models used for this effort make mistakes. Always validate the data for critical use cases. This data is an update to a previously developed database of wind ordinances found in OEDI Submission 5734: see the "U.S. Solar Siting Regulation and Zoning Ordinances 2022" link below. INFRA-COMPASS version used for collection: v0.11.3 LLMs used for collection: GPT-4.1, GPT-4.1 mini, GPT-4.1 nano

14 SOLAR ENERGY↗
DOE OSTI2023

Spatiotemporal Super-Resolution with Generative Machine Learning for Creating Renewable Energy Resource Data Under Climate Change Scenarios

As we plan for a future with higher penetrations of renewables and increasing electrification, it becomes more important to understand how the electricity grid will operate under a variety of weather events. We must also consider that the weather our future grid will experience will be different and possibly more extreme than the historical weather that we have extensive data for. We can use data from global climate models (GCMs) to help understand how our climate may change over the next several decades, but there is often a significant gap between the low-resolution GCM data and the high-resolution weather data required to study power systems under specific weather events. Therefore, our objective in this work is to develop tools that can bridge this gap by using low-resolution GCM data to create realistic high-resolution weather datasets that can be used to study renewable energy generation and electricity demand. To accomplish this objective, we have developed a set of generative machine learning models that can rapidly downscale GCM daily average output data at an approximate grid resolution of 100km to hourly data at an approximate 4 km grid resolution. The models can be used to create high resolution data from nearly any GCM included in the Coupled Model Intercomparison Project (CMIP) Phase 5 or 6. Our methods include all datasets regularly used to study the integration of wind and solar power plants as well as changes in electricity demand due to heating and cooling loads. These models and datasets enable power systems modelers to study climate change-influenced weather events and their impact on the grid. We have downscaled and validated wind, solar, temperature, and humidity data with very promising results. The generative machine learning methods are computationally efficient and produce data that has similar statistical characteristics to current state-of-the-art historical datasets. We have trained initial generative models and produced an initial dataset collectively referred to as Sup3rCC: Super-Resolved Renewable Energy Resource Data with Climate Change Impacts. The data covers a (mostly) historical period from 2015-2025 and a future period from 2050-2059. We have also taken hypothetical high-electrification load data and scaled the heating and cooling loads with respect to the 2050-2059 high-resolution Sup3rCC meteorology. The results show how future levels of renewable energy generation and electrified load may be impacted by climate change, setting the stage for capacity expansion models to consider a dynamic climate through model years.

climate change↗
DOE OSTI2021

Keystone Solar Future Project (KSFP)

The Keystone Solar Future Project (KSFP, also referred to as “Keystone Project” in the report) implements a cost-effective, secure, reliable, and safe technology platform that paves the way for future interconnected distributed energy resources (DER), creates a framework that enables high penetration of DER, and transforms the DER interconnection process. The project is important and necessary in a few aspects. First, the industry definition of Distributed Energy Resource Management System (DERMS) is not yet validated against field deployments and mostly implemented in small pilots relying on third party integration. Keystone project implements a direct plug and play communication to inverter based DER systems. Secondly, most interconnection application portal is not yet fully integrated with back-end system, thus lacks the capability to drive a complete and accurate modeling of DER assets into the planning and operational systems. Keystone project rolled out a fully integrated modeling process of DERs from interconnection to operational management. Lastly, customers were given an opportunity to learn about the advanced functions of the inverters and take full advantages of their benefits through participation in the pilot program. During the project, the technical effectiveness and economic feasibility of DER management were investigated and demonstrated in real life events and simulation studies. The project highlighted the importance of coordinated DER interconnection, installation and management with the rest of the distribution system.

14 SOLAR ENERGY↗
DOE OSTI2025

Assessment of ESM Readiness Level for Exascale HPC

Advancement of Earth System Models (ESMs) is becoming increasingly challenging due to a confluence of factors including increasing model complexity – to more fully represent the earth system, increasing spatial resolution - to achieve higher accuracy by resolving fine-scale dynamical to physical, biological, and chemical processes and their interaction, increasing ensemble size - to more accurately represent predictive uncertainty, and increased computing requirements – to enable more accurate and timely weather predictions and climate projections for societal benefit. The belief by many that computing will take care of itself is no longer valid given the disruptive changes in HPC that are driving up the cost of computing, increasing the difficulty of using emerging HPC effectively, and exposing limits in parallelism, portability and scalability of the ESM applications themselves.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

U.S. Wind Siting Regulation and Zoning Ordinances (2025)

A machine readable collection of documented wind siting ordinances at the state and local (e.g., county, township) level throughout the United States. The data were compiled using the Infrastructure Continuous Ordinance Mapping for Planning and Siting Systems (INFRA-COMPASS) tool, which leverages Large Language Models (LLMs) to automate the collection of local codes and ordinances applicable to energy infrastructure. URLs for the ordinance source documents are included in the Wind Ordinances spreadsheet. The GeoPackage file included below contains the jurisdiction shapes for each ordinance. Note that the GeoPackage file is formatted for ingestion by NREL's reVX setbacks tool and therefore does not contain any of the state-level regulations. NOTE: This data was collected with the help of generative AI. The Large Language Models used for this effort make mistakes. Always validate the data for critical use cases. This data is an update to a previously developed database of wind ordinances found in OEDI Submission 5733: see the "U.S. Wind Siting Regulation and Zoning Ordinances 2022" link below. INFRA-COMPASS version used for collection: v0.8.2 LLMs used for collection: GPT-4.1, GPT-4.1 mini, GPT-4.1 nano, GPT-4o mini

17 WIND ENERGY↗
DOE OSTI2025

Data-driven Community-centered Resilient Assessment and Planning Toolkit for Nexus of Energy and Water (DCRAPT-NEW)

Urban areas, including Detroit and Pittsburgh, have suffered significant dual outages of the electrical and water infrastructure in the past decade due, in part, to the increasing number of extreme weather events. With increasing temperatures and rainfall intensity, these regions need to prepare for increasing extreme events through community-based energy and water resilience analysis, planning, and enhancement. This project developed a suite of open-source, open-access, community-centered, data-driven assessment and distributed energy resource (DER) and planning tools for energy and water resilience enhancement in urban areas. Through establishing a multi-level community awareness and engagement mechanism and a comprehensive collection of power outage and flooding data, an innovative group of community energy and water resilience assessment and planning tools have been developed for a wide range of users with differing and variable sets of data available to them. The developed tools include (1) DOE EAGLE-I data-driven, deep-learning assisted resilience assessment and DER planning tools at the county level with socioeconomic factors incorporated; (2) Utility annual power outage data-driven tools for long term resilience assessment and DER planning and 15-min power outage data-driven tools for short term resilience assessment and planning; (3) Detailed engineering tools for energy and water systems resilience assessment and planning when the system topology and component fragility curves are available; (4) Alternative Resiliency Metric Calculation that extracts and separates outage and restoration processes; and (5) Co-optimization tools that evaluate the resilience of the power and sewage system and allow users to conduct joint planning with energy and wastewater systems. The developed tools provide planners, decision-makers, and stakeholders with powerful capabilities to systematically evaluate system/community resilience and optimal and actionable guidance for enhancing resilience while prioritizing DER investments. The tools have been used and validated in Detroit and Pittsburgh and can be used in other areas of the nation. In addition, this project will (1) advance the knowledge and applications of machine-learning methods in analyzing and fusing different layers of information and generating meaningful data points such as generating rare weather events; (2) significantly improve the energy and water resilience of the identified communities in Detroit and Pittsburgh and prepare for more frequent and severe weather conditions; (3) help communities assess extreme weather event impacts and address short-term and long-term resilience-related issues The developed tools have been made public via GitHub and demonstrated to community stakeholders and utility companies via the two annual workshops and numerous community engagement meetings. The project outcomes are also disseminated through publications in various journals and conference proceedings, and presentations at top conferences.

13 HYDRO ENERGY↗
DOE OSTI2024

Motivation and Design of the OCPP Security Service

Pacific Northwest National Laboratory is conducting in-depth research aimed at exploring how zero trust security principles can be effectively applied to electric vehicle charging infrastructure. This investigation seeks to enhance the resilience and reliability of these systems against cyber threats, ensuring secure and uninterrupted access to charging services for electric vehicle users and electric supply. Zero trust is a security concept centered on the belief that system operators should not automatically trust users or systems based on their location, whether inside or outside the organization, but instead must verify everything trying to connect to their systems before granting access. A key aspect of the project is to demonstrate and validate zero trust approaches targeted to electric vehicle (EV) charging infrastructure. It has been observed that both open-source and commercial solutions often overlook the specific protocols employed in managing EV charging stations and proceeded with a general, protocol-agnostic approach. While these strategies effectively block non-authorized routes to the charging infrastructure, they do not tackle the situations where attackers may exploit legitimate access channels, such as the inattentive operator model posited by the Idaho National Laboratory. To address this gap, this paper proposes and discusses a new security service targeted to the Open Charge Point Protocol (OCPP), which is the de facto protocol for the management of charging stations and serves a critical role in the broader adoption of electric vehicles. The design and architecture of the proposed OCPP security service are discussed in detail, outlining how it aims to safeguard charging station management system (CSMS) functions. The service is particularly important in scenarios where the charging station operator (CSO), responsible for the maintenance and operation of charging stations, and the charging network provider (CNP), which manages the charging network's accessibility and billing, are separate entities. This distinction is crucial because CSOs and CNPs often have different priorities, objectives, and operational responsibilities, which may not always align perfectly. For instance, a CSO might prioritize uptime and customer satisfaction, while a CNP might focus on maximizing revenue and network utilization. Such misalignment can create security vulnerabilities, as each entity might implement different policies and standards, potentially leaving gaps in the overall security posture.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Deploying E3’s RESERVE Tool to Enable Advanced Operation of Clean Grids

Energy and Environmental Economics, Inc. (E3) developed an open-source machine learning model, RESERVE, for deriving ancillary services timeseries in deeply decarbonized electricity grids. E3 used a bespoke PLEXOS production simulation model of the California Independent System Operator’s (CAISO) balancing area to validate RESERVE’s ability to enable production cost, greenhouse gas emissions (GHG), and renewable energy curtailment savings. These savings were modeled by comparing PLEXOS cases with RESERVE’s outputs to PLEXOS cases with CAISO’s incumbent reserve product in the Western Energy Imbalance Market (EIM)’s 15-minute market. E3 also tested cases with solar operating flexibly to provide reserves. E3 found that, in a 2030 modeling year, using RESERVE and flexible solar enabled significant production cost, GHG and curtailment savings versus the incumbent CAISO method in cases with low penetrations of lithium-ion batteries. However, with the full 14 gigawatts (about 30% of peak CAISO demand) of 4-hour lithium-ion batteries that are expected to be installed by 2030, these savings approach zero due to batteries saturating ancillary services markets. E3 also found significant savings under a 2019 benchmarking year.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Maximizing energy efficiency in wastewater treatment plants: A data-driven approach for waste heat recovery and an economic analysis using Organic Rankine Cycle and thermal energy storage

Maximizing energy efficiency through waste heat recovery (WHR) processes is crucial for sustainable and ecofriendly operations across multiple industries, notably in wastewater treatment plants (WWTPs). This work proposes a comprehensive approach for assessing the WHR feasibility in WWTPs, structured in two main objectives. Firstly, an Artificial Neural Network (ANN) model is developed to accurately predict WHR based on operational data, including biogas temperature, biogas pressure, daily production in kWh, and WHR values in kWh th . The second objective focuses on economically evaluating the WHR feasibility based on the estimated WHR values obtained by the ANN model, and then realistically assessing the economic feasibility of integrating the Organic Rankine Cycle (ORC) and Seasonal Thermal Energy Storage (STES) systems. With an application to the As-Samra WWTP located in Jordan, the developed ANN model demonstrates promising results in the validation phase, with a root mean square error (RMSE) of 2206 kWh/day, a mean absolute error (MAE) of 1674 kWh/day, and an R-squared (R 2 ) value of 68%. On the other hand, the economic analysis reveals that an optimal ORC system of 412.14 kW e capacity yields a Net Present Value (NPV) of 2.09 million US dollars, a Levelized Cost of Energy (LCOE) of 0.0749 USD/kWh, a Payback Period (PBP) of 4.8 years, and annual revenues of 428 kUSD. This work also investigates the techno-economic feasibility of integrating ORC-STES. Results indicate that the LCOE and PBP are highly affected by the ORC's capital cost, and integrating STES increases the LCOE to 0.0824 USD/kWh, rendering its integration with ORC infeasible. In conclusion, this study aims to advance the understanding and application of WHR in WWTPs, paving the way for more efficient and sustainable practices in the field.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Robust Scheduling of Networked Microgrids for Economics and Resilience Improvement

The benefits of networked microgrids in terms of economics and resilience are investigated and validated in this work. Considering the stochastic unintentional islanding conditions and conventional forecast errors of both renewable generation and loads, a two-stage adaptive robust optimization is proposed to minimize the total operating cost of networked microgrids in the worst scenario of the modeled uncertainties. By coordinating the dispatch of distributed energy resources (DERs) and responsive demand among networked microgrids, the total operating cost is minimized, which includes the start-up and shut-down cost of distributed generators (DGs), the operation and maintenance (O&M) cost of DGs, the cost of buying/selling power from/to the utility grid, the degradation cost of energy storage systems (ESSs), and the cost associated with load shedding. The proposed optimization is solved with the column and constraint generation (C&CG) algorithm. The results of case studies demonstrate the advantages of networked microgrids over independent microgrids in terms of reducing total operating cost and improving the resilience of power supply.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Incorporation of market signals for the optimal design of post combustion carbon capture systems

Recent studies have shown that fossil generators equipped with post-combustion carbon capture (PCC) systems are needed to reduce the cost of deep decarbonization. Such generators need to be flexible and responsive to grid conditions, particularly in a high variable renewable energy (VRE) environment. In this work, we evaluate the net present value (NPV) of retrofitting an existing natural gas combined cycle (NGCC) unit with a flexible PCC system while incorporating market signals from a high VRE grid. We use our industrial partner’s NGCC configuration as representative of existing NGCC units and Svante’s rapid-temperature swing adsorption (TSA) for PCC. Because of its ability to rapidly startup/shutdown and ramp-up/ramp-down, the chosen capture technology is very attractive for load-following operations. For a given set of market signals, we formulate a two-stage stochastic multi-period optimization problem, under the price-taker assumption, to simultaneously optimize the design of the capture system and operation of the entire plant. Rigorous models for the NGCC unit, PCC system, and compression system are developed using commercial process simulators and validated with either plant or vendor data. For computational tractability, we develop surrogate/reduced-order models for use in the optimization problem. The surrogate model for the NGCC plant is constructed by linearizing the rigorous dynamic model at 75% load, while data-driven nonlinear surrogate models for the capture and compression systems are constructed using simulation data from the rigorous models. The optimization problem, formulated as a mixed integer bilinear program, is implemented in the IDAES® integrated platform and solved to global optimality using Gurobi 9.5. Using this formulation, we determine the profitability of retrofitting an existing NGCC unit with the chosen capture system for multiple regions in the U.S. under two scenarios with different carbon prices. Importantly, the results show that the optimal decision strongly depends on the region and on the carbon price, thereby demonstrating the importance of the inclusion of market signals in the design process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

West Valley Demonstration Project (WVDP) Annual Site Environmental Report (ASER) for Calendar Year 2021

The report, prepared for the U.S. Department of Energy West Valley Demonstration Project office (DOE-WVDP), summarizes the environmental protection program at the WVDP for calendar year (CY) 2021. Monitoring and surveillance of the facilities used by the DOE are conducted to verify protection of public health and safety and the environment. The report is a key component of DOE’s effort to keep the public informed of environmental conditions at the WVDP. The quality assurance protocols applied to the environmental monitoring program ensure the validity and accuracy of the monitoring data. In addition to demonstrating compliance with environmental laws, regulations, and directives, evaluation of data collected in 2021 continued to indicate that WVDP activities pose no threat to public health or safety, or to the environment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Benefits and Critical Knowledge Gaps in Determining the Role of Floating Photovoltaics in the Energy-Water-Food Nexus

Floating solar photovoltaic (FPV) systems have become an increasingly attractive application of photovoltaics (PV) because of land-use constraints, the cost of land and site preparation, and the perceived energy and environmental co-benefits. Despite the increasing interest in FPV systems, a robust validation of their suggested co-benefits and impacts on the nexus of energy, water, and food (EWF) systems is lacking. This information gap makes it challenging for decision makers to justify its adoption—potentially suppressing FPV deployment. To address this gap and to help de-risk this PV deployment opportunity, we (1) review the suggested co-benefits of FPV systems with a focus on the impacts that could alleviate pressures on EWF systems and (2) identify areas where further research is needed to reduce uncertainty around FPV system performance. Our review reveals that EWF nexus-relevant co-benefits, such as improved panel efficiency and reduced land usage, are corroborated in the literature, whereas others, such as water quality impacts, lack empirical evidence. Our findings indicate that further research is needed to quantify the water-related and broader economic, environmental, social, sustainability, justice, and resilience co-benefits and impacts of FPV systems.

14 SOLAR ENERGY↗
DOE OSTI2022

Machine Learning for Automated Metadata Assignment in Buildings: Cooperative Research and Development (Final Report, CRADA Number CRD-18-00767)

RealTerm Energy and NREL have identified a shared vision to evaluate opportunities to facilitate the organization and assignment of metadata to building control system (BCS) data via industry-informed machine learning (ML). Manual metadata assignment is labor intensive and costly, slowing down any Energy Management and Information System (EMIS) deployment in the building space. This project aims to develop methodologies to accurately assign this metadata and significantly decrease the level of effort associated with deploying EMIS. The objective of this project is to identify/design methodologies to assign metadata to HVAC control points automatically. The identified methodologies will be programmed in analytics algorithms so they can ingest a list of points and produce a detailed tagging following the Haystack classification nomenclature. To validate the efficacy of each methodology, tagging results will be compared utilizing a list of points extracted from RealTerm's building database-as well as data extracted from the NREL campus via the Intelligent Campus program-enabling testing against large datasets with real world challenges. The developed methodologies may leverage building manager/operator input on a limited basis to add context to the classifying algorithms. The partnership aims to advance global efforts in areas related to the DOE missions through improving operational performance of commercial buildings. It is well documented that buildings fall out of commission after they are occupied, wasting significant energy and incurring associated costs simply due to poor operational performance. Emerging EMIS technologies that perform continuous commissioning help to address this issue, yet integration of these systems can be labor intensive both for the technology vendor and the building owner/operator. This project will enable more efficient and cost-effective analytics for buildings, enabling improvement in building operations at lower cost points.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗