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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 OSTI2023

Process-Oriented Diagnostics: Principles, Practice, Community Development, and Common Standards

Process-oriented diagnostics (PODs) aim to provide feedback for model developers through model analysis based on physical hypotheses. However, the step from a diagnostic based on relationships among variables, even when hypothesis driven, to specific guidance for revising model formulation or parameterizations can be substantial. The POD may provide more information than a purely performance-based metric, but a gap between POD principles and providing actionable information for specific model revisions can remain. Furthermore, in coordinating diagnostics development, there is a trade-off between freedom for the developer, aiming to capture innovation, and near-term utility to the modeling center. Best practices that allow for the former, while conforming to specifications that aid the latter, are important for community diagnostics development that leads to tangible model improvements. Promising directions to close the gap between principles and practice include the interaction of PODs with perturbed physics experiments and with more quantitative process models as well as the inclusion of personnel from modeling centers in diagnostics development groups for immediate feedback during climate model revisions. Examples are provided, along with best-practice recommendations, based on practical experience from the NOAA Model Diagnostics Task Force (MDTF). Common standards for metrics and diagnostics that have arisen from a collaboration between the MDTF and the Department of Energy’s Coordinated Model Evaluation Capability are advocated as a means of uniting community diagnostics efforts.

58 GEOSCIENCES↗

NASA NTRS2015

Risk Informed Philosophy: Using What We Fear to Lose to Guide Us to Success

When an organization sets out on a new effort, program, or project, one of the first steps undertaken is to understand the related requirements. Most often, these requirements come in the form of standards, directives, or other organizational processes, and are derived to meet a broad range of efforts, programs, and projects. The net result is that organizations or teams are forced to start with a maximum set of requirements and expend time and energy tailoring the set of requirements down to what is more appropriate for the effort, program, or project at hand. This presentation will present an alternate method for the application of requirements or best practices that is based upon the actual risks to the safety, performance, or success of the effort. This additive route for applying best practices and requirements also encourages an early exploration of the risks, thus yielding a better understanding of where resources should be applied. This presentation also extends this concept of risk-based application of best practices and requirements to the selection of organization-wide improvement or standardization efforts, such as Lean, Six Sigma, and Quality Management Systems.

Darpel, Scott↗

DOE OSTI2022

Energy Resilient Recovery in Puerto Rico: Hurricane Maria Recovery Support

This report covers microgrids as a special application of distributed energy resources (DERs) in Puerto Rico. This is one of a series of reports describing the U.S. Department of Energy (DOE) multi-laboratory efforts undertaken. To ensure the sustainable, long-term recovery of Puerto Rico's electric power grid from hurricanes Maria and Irma and to build capacity to manage future potential natural disasters in the most secure and resilient way, DOE convened experts from multiple national laboratories to develop a comprehensive set of data, models, analytic tools, and studies, considering inputs from a wide variety of stakeholder groups, to support technically sound recommendations for Puerto Rico's energy investment decisions. In Phase 1 of the multi-laboratory effort to support Puerto Rico's recovery, the National Renewable Energy Laboratory (NREL) provided the utility company Puerto Rico Electric Power Authority (PREPA) recommendations for a new framework of interconnection standards to accelerate the integration of utility-scale, transmission-connected, renewable electrical generation and energy storage that ensure cross-technology compatibility and enable high deployment levels without compromising grid reliability, safety, or security (https://www.nrel.gov/docs/fy19osti/73848.pdf). In Phase 2, NREL published a report focused on the interconnection of distributed energy resources (DERs) to the electric distribution system in Puerto Rico (https://www.nrel.gov/docs/fy21osti/77127.pdf). This report familiarized the reader with Puerto Rico's distribution infrastructure and operational practices and procedures that are relevant to DER interconnection. The report also provided considerations for streamlining the interconnection process given the expected increase in deployments resulting from Puerto Rico's renewable portfolio standard goal of 100% renewables by 2050. Accordingly, the report identifies considerations and concerns associated with the increase in intermittent generation, strategies for DER interconnection best practices, and the potential use of the latest technological solutions identified in the latest revision of the Institute of Electrical and Electronics Engineers 1547-2018 interconnection standard. Additionally, the report identified ways to improve the physical resiliency of installed DERs. This task describes how distributed energy systems may participate in and contribute to improving the resiliency of Puerto Rico's energy infrastructure in the future. This report presents an analysis of the Puerto Rico grid to illustrate the possible different microgrid and minigrid scenarios. The capability to form sustained microgrids and minigrids has the potential to provide a high level of resiliency during disturbances on the grid. DERs, on the other hand, have the capability to aid in the microgrid operation by providing grid support as well as grid-forming functionality. Other tasks in Phase 3 include voltage regulation in distribution networks using DERs and transmission-and-distribution co-simulation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2014

How to Develop and Interpret a Credibility Assessment of Numerical Models for Human Research: NASA-STD-7009 Demystified

In the wake of the Columbia accident, the NASA-STD-7009 [1] credibility assessment was developed as a unifying platform to describe model credibility and the uncertainties in its modeling predictions. This standard is now being adapted by NASAs Human Research Program to cover a wide range of numerical models for human research. When used properly, the standard can improve the process of code development by encouraging the use of best practices. It can also give management more insight in making informed decisions through a better understanding of the models capabilities and limitations.To a newcomer, the abstractions presented in NASA-STD-7009 and the sheer volume of information that must be absorbed can be overwhelming. This talk is aimed at describing the credibility assessment, which is the heart of the standard, in plain terms. It will outline how to develop a credibility assessment under the standard. It will also show how to quickly interpret the graphs and tables that result from the assessment and how to drill down from the top-level view to the foundation of the assessment. Finally, it will highlight some of the resources that are available for further study.

numerical analysis↗

DOE OSTI2021

Considerations for Distributed Energy Resource Integration in Puerto Rico: DOE Multi-Lab Grid Modeling Support for Puerto Rico; Analytical Support for Interconnection and IEEE Std 1547-2018 National Renewable Energy Laboratory (Task 3.0)

To ensure the sustainable long-term recovery of Puerto Rico's electric power grid from hurricanes María and Irma and to build capacity to manage future potential natural disasters in the most secure and resilient way, the U.S. Department of Energy (DOE) convened experts from multiple national laboratories to develop a comprehensive set of data, models, analytic tools, and studies, considering inputs from a wide variety of stakeholder groups, to support technically sound recommendations for Puerto Rico's energy investment decisions. A resilient electric grid is vital to Puerto Rico's security, economy, and way of life, and it will provide the foundation for essential services that people and businesses on the island rely on every day. This report shows progress for a grid modeling task under the DOE-sponsored project that is a collaboration among the National Renewable Energy Laboratory (NREL) and other national laboratories. In Phase 1 of the multilab effort to support Puerto Rico's recovery, NREL provided the utility company Puerto Rico Electric Power Authority (PREPA) recommendations for a new framework of interconnection standards to accelerate the integration of utility-scale, transmission-connected renewable electrical generation and energy storage that ensure cross-technology compatibility and enable high deployment levels without compromising grid reliably, safety, or security. This Phase 2 report focuses on the interconnection of distributed energy resources (DERs) to the electric distribution system in Puerto Rico. This report is intended to familiarize the reader with Puerto Rico's distribution infrastructure and operational practices and procedures that are relevant to DER interconnection. The report also provides considerations for streamlining the interconnection process given the expected increase in deployments resulting from Puerto Rico's renewable portfolio standard (RPS) goal of 100% renewables by 2050. Accordingly, the report identifies considerations and concerns associated with the increase in intermittent generation, strategies for DER interconnection best practices, and the potential use of the latest technological solutions identified in the latest revision of the Institute of Electrical and Electronics Engineers (IEEE) 1547-2018 interconnection standard.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

An Authentication Vulnerability Assessment of Connected Lighting Systems

Emerging connected lighting systems (CLS) that incorporate distributed intelligence, network interfaces, and sensors can become data-collection platforms that enable a wide range of valuable new capabilities as well as greater energy savings in buildings and cities. However, CLS technology is currently at an early stage of development, and its increased connectivity introduces cybersecurity risks that are new to the lighting industry and that must be addressed for successful integration with other systems. While a number of existing frameworks, guidelines, and tests for evaluating cybersecurity vulnerability may apply to CLS in whole or in part, there is currently no mandatory requirement for cybersecurity testing or certification. The lighting industry, including technology developers and specification organizations, is currently evaluating the suitability of existing frameworks and guidelines for CLS. To support these efforts, Pacific Northwest National Laboratory (PNNL) is conducting a series of studies intended to educate lighting industry stakeholders on specific cybersecurity practices and characterize their implementation in commercially available CLS with varying system architectures, network-communication technologies, and degrees of maturity. This study demonstrates that tests for authentication vulnerabilities can be developed with objective pass/fail criteria, therby facilitating comparisons between CLS. Based on the limited results of this study, it appears that the CLS that are being brought to market have varying levels of authentication vulnerability. It is hoped that these evaluations will support and perhaps accelerate industry discussions on the risks of specific security vulnerabilities, what vulnerabilities should be addressed by in-development of future lighting-specific best practices, and whether any such practices should be included in voluntary lighting standards.

42 ENGINEERING↗

DOE OSTI2021

Study of Hydrogen Fuel Cell Technology for Freight Rail Propulsion and Review of Relevant Industry Standards.

Alternatives to conventional diesel electric propulsion are currently of interest to rail operators. In the U.S., smaller railroads have implemented natural gas and other railroads are exploring hydrogen technology as a cleaner alternative to diesel. Diesel, battery, hydrogen fuel cell, or track electrification all have trade-offs for operations, economics, safety, and public acceptability. A framework to compare different technologies for specific applications is useful to optimize the desired results. Standards from the Association of American Railroads (AAR) and other industry best practices were reviewed for applicability with hydrogen fuel cell technology. Some technical gaps relate to the physical properties of hydrogen, such as embrittlement of metals, invisible flames, and low liquid temperatures. A reassessment of material selection, leak/flame detection, and thermal insulation methods is required. Hydrogen is less dense and diffuses more easily than natural gas, and liquid hydrogen is colder than liquefied natural gas. Different densities between natural gas and hydrogen require modifications to tank designs and flow rates. Leaked hydrogen will rise rather than pool on the ground like diesel, requiring a modification to the location of hydrogen tanks on rolling stock. Finally, the vibration and shock experienced in the rail environment is higher than light-duty vehicles and stationary applications for which current fuel cell technology has been developed, requiring a modification in tank design requirements and testing.

08 HYDROGEN↗

DOE OSTI2023

Bat Smart Curtailment: Efficacy and Operational Testing

Curtailment, or blanket curtailment, is a leading method to mitigate the impacts to bats from operating wind turbines. Although this strategy results in considerable decreases in bat fatalities, it also results in decreased energy production. In 2019, Natural Power was awarded funding by the Department of Energy to assess the readiness of the informed smart curtailment technology, EchoSense (formerly referred to as Detection and Active Response Curtailment, [DARC]). The research undertaken by this project expands the understanding of alternative methods, known as smart curtailment, to maintain a reduction in bat fatalities while simultaneously recovering lost energy associated with blanket curtailment. The overall project was composed of three major tasks; Task 1 was focused on cybersecurity compliance of the EchoSense system in accordance with the North American Electric Reliability Corporation Critical Infrastructure Protection (“NERC CIP”) standards, Task 2 assessed the mechanical loads exerted on turbines when operating under a smart curtailment regime, and Task 3 assessed the efficacy of the EchoSense system at an operational wind farm. Regarding Task 1, an external review by the National Renewable Energy Laboratory determined that the EchoSense system did not create any new cybersecurity weaknesses and was compliant with the NERC CIP standards. As a result of this process, Natural Power developed some best practices (10.1) for wind- wildlife technology developers. In conjunction with the National Renewable Energy Laboratory, the results (10.2) of the loads testing demonstrated that the periodic curtailment and release of turbines by the EchoSense system did not have any detrimental impact on the mechanical components of a wind turbine (Task 2). During the late summer to fall of 2020 and 2021, Natural Power demonstrated that the use of the EchoSense smart curtailment system resulted in no significant difference in bat fatalities compared to blanket curtailment with cut-in speeds at 6.9 m/s (2020) and 5.0 m/s (2021) while resulting in a significant difference in decreased lost energy (Task 3). This translates to an average of 41% (2020) and 56% (2021) reduction in per turbine energy loss compared to blanket curtailment. The reduction in energy loss that would have been achieved by EchoSense curtailment compared to blanket curtailment, if applied across all 69 turbines, is roughly equivalent to having an additional turbine on site. These results are notable for finding a balance between the environmental impact of wind energy and the economic feasibility in energy production associated with mitigating that impact. https://www.naturalpower.com/us/expertise/service/engineering-operations/echosense

17 WIND ENERGY↗

DOE OSTI2025

Floating photovoltaic power plants: A review of energy yield, reliability, and operation and maintenance

Photovoltaic (PV) systems are essential for the transition to sustainable energy, reducing fossil fuel dependence and mitigating climate change. Although PV requires minimal land area — PV can meet the European Union's energy needs using only 0.26% of its land — space for deployment is often scarce in densely populated regions. Floating photovoltaics (FPV) offer an effective solution to land-use challenges by installing PV systems on floating structures in water bodies. FPV is a growing niche within PV with a cumulative installed capacity reaching 7.7 GW globally by 2023. Almost 90% of the installed FPV capacity is in Asia, with close to 50% of in China alone, while the Netherlands and France are the largest markets outside Asia. FPV shows strong potential to support climate targets, but still faces challenges like regulatory barriers, cost competitiveness compared to ground-based PV (GPV), and uncertainties about environmental impacts and system reliability. FPV systems are currently installed mainly on sheltered inland waters, such as quarry lakes, irrigation ponds and reservoirs. FPV technical standards are still being developed. Guidelines have been published by the World Bank, DNV, and Solar Power Europe, and emerging national standards from South Korea, China, and Singapore address design, components, and safety. The International Electrotechnical Commission (IEC) is working on formal standards for floats, mooring systems, and electrical connectors. However, the published best practices lack quantitative guidance for yield modelling and reliability, which this report aims to address. It provides data-driven insights, models, and parameters essential for accurate energy yield, reliability, and maintenance predictions over FPV systems' lifetimes.

14 SOLAR ENERGY↗

DOE OSTI2023

Cybersecurity Guidance for Distributed Energy Resource Management Systems (DERMS)

As part of the Securing Solar for the Grid (S2G): Cybersecurity for Solar Systems workshop at RE + in Las Vegas, Nevada, NREL researchers discuss an ongoing effort to develop cybersecurity guidance for vendors and operators of distributed energy resource management systems (DERMS). This guide will prioritize cybersecurity best practices that can be testing and developed for a potential future standard. This presentation will highlight NREL's ongoing work in this area and future areas of research.

cyber↗

NASA NTRS2002

Program and Project Management Framework

The primary objective of this project was to develop a framework and system architecture for integrating program and project management tools that may be applied consistently throughout Kennedy Space Center (KSC) to optimize planning, cost estimating, risk management, and project control. Project management methodology used in building interactive systems to accommodate the needs of the project managers is applied as a key component in assessing the usefulness and applicability of the framework and tools developed. Research for the project included investigation and analysis of industrial practices, KSC standards, policies, and techniques, Systems Management Office (SMO) personnel, and other documented experiences of project management experts. In addition, this project documents best practices derived from the literature as well as new or developing project management models, practices, and techniques.

Butler, Cassandra D.↗

DOE OSTI2026

Electrocoagulation in Water Treatment: Targeted Contaminant Removal and Laboratory Best Practices

Electrocoagulation for water treatment offers many advantages over traditional treatment technologies, including improved energy efficiency and modularity. One challenge with electrocoagulation is the lack of standardization in the methodology and reporting. This review provides a novel contribution by examining the past literature using a uniform metric (charge loading) as a basis for comparison, highlighting the importance of uniform reporting practices in this field. Furthermore, this review provides practical guidance for experimentalists in standardizing the electrocoagulation design and operating procedures. First, we present a comprehensive overview of contaminant-specific electrocoagulation as an electrochemical treatment technology for processing industrial, municipal, and agricultural water, with a focus on aluminum and iron electrocoagulation. We detail the fundamental mechanisms that allow for constituent removal during pretreatment. Specifically, we highlight electrocoagulation’s potential for organics, metalloids, microbes, and hardness remediation, examining the optimal removal conditions in terms of charge loading and current density. We conclude this work with some experimental best practices for lab-scale electrocoagulation experiments.

aluminum↗

DOE OSTI2022

Data Curation for Machine Learning Applied to Geothermal Power Plant Operational Data for GOOML: Geothermal Operational Optimization with Machine Learning: Preprint

Geothermal Operational Optimization with Machine Learning (GOOML) is a transferable and extensible component-based geothermal asset modeling framework that considers complex steamfield relationships and identifies optimization prospects using a data-driven approach to physics-guided, data-centric machine learning. This framework has been used to develop digital twins that provide steamfield operators with operational environments to analyze and understand historical and forecasted power production, explore new steamfield configuration possibilities, and seek optimal asset management in real world applications. To create, test, and apply the GOOML framework, diverse time-series datasets spanning multiple years were sourced from various geothermal power plant components within several complex real-world geothermal operations. These operations are based in the United States and New Zealand and include a variety of technologies, end-uses and configurations, collectively covering nearly all relevant operating conditions for modern geothermal fields. Datasets were acquired from multiple sources to ensure that machine learning experiments generalized properly to various operating conditions. It was found that the data varied in quality, format, and completeness. To ensure consistency between the various datasets, a standardized data curation process was developed to reliably streamline data preparation. This paper will discuss best practices as learned from the GOOML data curation process which takes the following steps: 1) acquisition of large quantities of data from power plant operators, 2) digestion of data to gain an initial understanding of what is included, 3) data transformation, which includes converting the data into a standardized machine-readable format so that they can be visualized, quality checked, and cleaned, 4) quality assurance and quality control, involving identification of significant data gaps and apparent anomalies through mapping of data features to real world componentry via the GOOML historical model, followed by discussion with modelers and power plant operators to identify additional data needs and to resolve issues, 5) use in machine learning algorithms, and 6) repetition of steps one through five until all data needs are met and data are deemed suitable for producing trustworthy modeling results which may be disseminated, ideally along with the curated dataset. This iterative process is focused on improving the quality of the data rather than tuning machine learning model parameters and supports a shift towards data-centric AI as a means to improving real-world applicability of geothermal machine learning projects.

access↗

DOE OSTI2020

Guidelines for IAEA Small Specimen Test Techniques Master Curve Fracture Toughness Testing

Under the auspices of International Atomic Energy Agency (IAEA), a coordinated research project (CRP) entitled “Towards the Standardization of Small Specimen Test Techniques for Fusion Applications” has started since 2017. The overall objective of the project is to provide a set of guidelines for small specimen test techniques (SSTT) based on commonly agreed best practices on main test techniques including tensile, creep, low cycle fatigue, fracture toughness, and fatigue crack growth rate. This will act as the first step of a full standardization of the SSTT. Fusion structural materials, i.e., reduced activation ferritic/martensitic (RAFM) steels, are used for testing. In addition, the project will create a comprehensive mechanical property database of RAFM steels tested by SSTT. For the fracture toughness task of the CRP, three testing methods including Master Curve, local approach for ductile crack growth and cleavage fracture, and ductile approach at room temperature will be evaluated. This report focuses on developing guidelines for the round-robin Master Curve testing based on the ASTM standard E1921-19b “Standard Test Method for Determination of Reference Temperature, T 0 , for Ferritic Steels in the Transition Range” and commonly agreed best practice from researchers at Oak Ridge National Laboratory (ORNL), Centre for Energy, Environment and Technology (CIEMAT), and UK Atomic Energy Authority (UKAEA).

36 MATERIALS SCIENCE↗

DOE OSTI2022

Reference surface excess isotherms for carbon dioxide adsorption on ammonium ZSM-5 at various temperatures

Abstract This work is part of the effort at the Facility for Adsorbent Characterization and Testing (FACT lab) at the National Institute of Standards and Technology (NIST) to develop reference materials, reference data, and measurement best practices for adsorption metrology. High-pressure surface excess isotherms for CO 2 adsorption on NIST Reference Material 8852 (ammonium ZSM-5) at 15 °C, 25 °C, and 35 °C are reported, expanding on a FACT Lab-organized international interlaboratory study on this sorbent/sorbate pair at 20 °C. The range of temperatures of the present study is of interest for many CO 2 adsorption measurements and applications. Measurements were made using five different adsorption instruments, both manometric and gravimetric. Excellent agreement in the measured isotherms among the instruments was found. An empirical reference equation of the form, $${n}_{ex,ref}({P}_{eq})=\frac{c}{\{{1+\mathrm{exp}[\left(-\mathrm{ln}\left(P\right)+a\right)/b ]\}}^{b }} ,$$ n e x , r e f ( P eq ) = c { 1 + exp [ - ln P + a / b ] } b , [ n ex,ref is surface excess uptake (mmol/g); P eq is equilibrium pressure (MPa); P is ( P eq )/(1 MPa)]; a , b , c are constants] and the 95% uncertainty interval were determined for the isotherms at each of the temperatures. Lastly, the isosteric heat of adsorption is estimated from absolute isotherms derived from the surface excess reference data.

Nguyen, Huong Giang T. (ORCID:0000000210527565)↗

DOE OSTI2023

pvlib python: 2023 project update

pvlib python is a community-developed, open-source software toolbox for simulating the performance of solar photovoltaic (PV) energy components and systems. It provides reference implementations of over 100 empirical and physics-based models from the peer-reviewed scientific literature, including solar position algorithms, irradiance models, thermal models, and PV electrical models. In addition to individual low-level model implementations, pvlib python provides high-level workflows that chain these models together like building blocks to form complete “weather-to-power” photovoltaic system models. It also provides functions to fetch and import a wide variety of weather datasets useful for PV modeling. pvlib python has been developed since 2013 and follows modern best practices for open-source python software, with comprehensive automated testing, standards-based packaging, and semantic versioning. Its source code is developed openly on GitHub and releases are distributed via the Python Package Index (PyPI) and the conda-forge repository. pvlib python’s source code is made freely available under the permissive BSD-3 license. Here we (the project’s core developers) present an update on pvlib python, describing capability and community development since our 2018 publication (Holmgren, Hansen, & Mikofski, 2018).

14 SOLAR ENERGY↗

NASA NTRSDate not supplied

Summary of the First AIAA Stability and Control Prediction Workshop

Results from the First AIAA Stability and Control Prediction Workshop are summarized in this paper. The workshop series was developed in support of three primary objectives: (1) to establish best practices for the prediction of stability and control derivatives using industry-standard Computational Fluid Dynamics (CFD) solvers, (2) to provide an impartial forum for evaluating the effectiveness of Reynolds-averaged-Navier-Stokes- and Detached-Eddy-Simulation-based modeling techniques, and (3) to identify areas in need of additional research and development. To address these objectives, the inaugural workshop focused on generating computational aerodynamic predictions for the ONERA version of the NASA/Boeing Common Research Model. The configuration includes the wing, body, horizontal tail, and a vertical tail designed by ONERA. While longitudinal wind tunnel test data for the model had been previously documented, unpublished lateral test data at small sideslip angles provided a unique opportunity for participants to generate blind computational predictions for wind tunnel data comparisons. Additional test cases included assessments of the Mach number effect on static lateral/directional stability and the impact of the wind tunnel sting on longitudinal stability. Participants were invited to generate solutions using two workshop-provided series of structured overset and unstructured grids, in addition to any participant custom grids of interest. Total and component-level breakdowns for the force and moment coefficients for each test case are presented, as well as sectional pressure distribution data on the wing and tail components, to assess the agreement between several different Reynolds-averaged Navier-Stokes CFD solvers.

CFD↗

DOE OSTI2021

Quality Control Methods for Advanced Metering Infrastructure Data

While urban-scale building energy modeling is becoming increasingly common, it currently lacks standards, guidelines, or empirical validation against measured data. Empirical validation necessary to enable best practices is becoming increasingly tractable. The growing prevalence of advanced metering infrastructure has led to significant data regarding the energy consumption within individual buildings, but is something utilities and countries are still struggling to analyze and use wisely. In partnership with the Electric Power Board of Chattanooga, Tennessee, a crude OpenStudio/EnergyPlus model of over 178,000 buildings has been created and used to compare simulated energy against actual, 15-min, whole-building electrical consumption of each building. In this study, classifying building type is treated as a use case for quantifying performance associated with smart meter data. This article attempts to provide guidance for working with advanced metering infrastructure for buildings related to: quality control, pathological data classifications, statistical metrics on performance, a methodology for classifying building types, and assess accuracy. Advanced metering infrastructure was used to collect whole-building electricity consumption for 178,333 buildings, define equations for common data issues (missing values, zeros, and spiking), propose a new method for assigning building type, and empirically validate gaps between real buildings and existing prototypes using industry-standard accuracy metrics.

24 POWER TRANSMISSION AND DISTRIBUTION↗