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Thom, Daniel

Publications and source records attributed to Thom, Daniel.

At least 19 records

Powered by dsgrid [Slides]

NREL's demand-side grid (dsgrid) toolkit harnesses decades of sector-specific energy modeling expertise to understand current and future U.S. electricity load for power systems analyses. The primary purpose of dsgrid is to create comprehensive electricity load data sets at high temporal, geographic, sectoral, and end-use resolution. These data sets enable detailed analyses of current patterns and future projections of end-use loads. This presentation will include NREL power grid researcher Elaine Hale.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Sienna Modeling Framework [Slides]

NREL's Sienna modeling framework effectively builds, solves, and analyzes the scheduling problems and dynamic simulations of quasi-static infrastructure systems. It uses a modular framework to answer different questions about future energy systems, fundamentally advancing the nation's ability to model individual and integrated infrastructure systems at a range of spatial and temporal scales. This presentation will include NREL power grid researcher Clayton Barrows.

24 POWER TRANSMISSION AND DISTRIBUTION↗

GDM (Grid Data Models) [SWR-24-31]

Grid Data Models (GDM) is a collection of pydantic data models for power distribution and transmission system components. These data models can be easily serialized and deserialized. GDM provides a standard interface for accessing power system component data with built in validation. See also: https://pypi.org/project/grid-data-models/

Duwadi, Kapil↗

InfraSys (Infrastructure Systems) [SWR-24-42]

This package implements a data store for components and time series in support of Python-based modeling packages. While it is designed to support teams modeling transmission and distribution systems for electrical grids, it can be used by any package that needs to store components (e.g., generators and buses) that have quantities (e.g., power and voltage) which may vary over time. The package was inspired by InfrastructureSystems.jl (https://github.com/NREL-Sienna/InfrastructureSystems.jl).

Thom, Daniel↗

Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100): Final Report

The Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100) is a comprehensive analysis based on extensive stakeholder input of possible pathways for Puerto Rico to achieve its goal of 100% renewable energy by 2050. PR100 was an integrated effort drawing on expertise and capabilities of the contributing national laboratories that explored possible pathways for Puerto Rico to achieve its goal of 100% renewable energy in the long term (by 2050), increase reliability and resilience in the immediate term (within the next few years), and work toward energy justice. The purpose of the study is to provide decision support and inform investment decisions for implementers of Puerto Rico's energy transition. See NREL/TP-6A20-88614 for the Spanish translation of this report.

100% renewable energy target↗

El Estudio de Resiliencia de la Red Electrica de Puerto Rico y Transiciones a Energia 100% Renovable (PR100): Informe Final [Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100): Final Report]

El Estudio de Resiliencia de la Red de Puerto Rico y Transiciones a Energia 100% Renovable (PR100) es un analisis integral basado en amplios aportes de las partes interesadas sobre posibles caminos para que Puerto Rico alcance su meta de 100% de energía renovable para 2050. PR100 fue un esfuerzo integrado que se baso en experiencia y capacidades de los laboratorios nacionales contribuyentes que exploraron posibles caminos para que Puerto Rico logre su objetivo de 100% de energía renovable en el largo plazo (para 2050), aumente la confiabilidad y la resiliencia en el plazo inmediato (dentro de los proximos anos), y trabajar hacia la justicia energetica. El proposito del estudio es brindar apoyo a las decisiones e informar las decisiones de inversion para los implementadores de la transicion energetica de Puerto Rico. See NREL/TP-6A20-88384 for the English translation of this report.

100% renewable energy target↗

PR100 Final Results

This presentation includes a summary of the final results from the Puerto Rico Grid Resilience and Transition to 100% Renewable Energy Study (PR100). Led by the U.S. Department of Energy's Grid Deployment Office and the National Renewable Energy Laboratory, and funded by the Federal Emergency Management Agency, the PR100 Study was a two-year effort resulting in stakeholder-driven pathways for Puerto Rico to meet its clean energy goals. For Spanish version see https://www.nrel.gov/docs/fy24osti/88975.pdf.

100% renewable energy target↗

Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100) (Summary Report)

The Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100) is a comprehensive analysis based on extensive stakeholder input of possible pathways for Puerto Rico to achieve its goal of 100% renewable energy by 2050. In this summary report of the PR100 Final Report, we describe the background and motivation behind the study, provide an overview, summarize results, highlight key findings, and outline implementation actions for stakeholders to take in the immediate-, near-, mid-, and long-term to achieve Puerto Rico’s energy system goals.

100% renewable energy target↗

Estudio de Resiliencia de la Red Electrica de Puerto Rico y Transiciones a Energia 100% Renovable (PR100): Informe resumido [Spanish Translation of Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100) (Summary Report)]

The Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100) is a comprehensive analysis based on extensive stakeholder input of possible pathways for Puerto Rico to achieve its goal of 100% renewable energy by 2050. In this summary report of the PR100 Final Report, we describe the background and motivation behind the study, provide an overview, summarize results, highlight key findings, and outline implementation actions for stakeholders to take in the immediate-, near-, mid-, and long-term to achieve Puerto Rico’s energy system goals. For the English version of this report, see NREL/TP-6A20-88615 (https://www.nrel.gov/docs/fy24osti/88615.pdf).

100% renewable energy target↗

Presentacion del Webinar Publico sobre Resultados Finales del Estudio PR100

Esta presentacion incluye un resumen de los resultados finales del Estudio de Resiliencia de la Red Electrica de Puerto Rico y Transiciones a Energia 100% Renovable (PR100). Dirigido por el Departamento de Energia y el Laboratorio Nacional de Energias Renovables, y financiado por la Agencia Federal para el Manejo de Emergencias, el estudio PR100 fue un esfuerzo de dos anos que ha resultado en caminos impulsados por las partes interesadas para que Puerto Rico alcance sus metas de energia limpia. For the English version of this presentation, see NREL/PR-6A20-88773 (https://www.nrel.gov/docs/fy24osti/88773.pdf).

100% renewable energy target↗

PSI (PowerSimulations.jl) [SWR-23-104]

PowerSimulations.jl is a Julia-based BSD- licensed power system operations simulation tool developed as a flexible and open source software for quasi-static power systems simulations including Production Cost Models. PowerSimulations.jl tackles the issues of developing a simulation model in a modular way providing tools for the formulation of decision models and emulation models that can be solved independently or in an interconnected fashion. For further information regarding the Sienna modeling framework at NREL, see: https://www.nrel.gov/analysis/sienna.html

Lara Aguilar, Jose Daniel↗

PSY (PowerSystems.jl) [SWR-23-105]

PowerSystems.jl is a package to organize and manipulate data for the study of energy systems with diverse modeling requirements. This software serves two main purposes: to reduce the burden of large power system data set development, and to promote reproducible research and simulation. PowerSystems.jl implements an abstract hierarchy to represent and customize power systems data and includes data containers for quasi-static and dynamic simulation applications. Key features include efficient management of large quantities of time series data, optimized serialization, and comprehensive validation capabilities. For further information regarding the Sienna modeling framework at NREL, see: https://www.nrel.gov/analysis/sienna.html

Lara Aguilar, Jose Daniel↗

Demand-Side Grid (dsgrid) TEMPO Light-Duty Vehicle Charging Profiles v2022

Simulated hourly electric vehicle charging profiles for light-duty household passenger vehicles in the contiguous United States, 2018-2050. Profiles are differentiated by scenario, county, household and vehicle types, and charging type. Data was produced in 2022 using the Transportation Energy & Mobility Pathway Options (TEMPO) model and published in demand-side grid (dsgrid) toolkit format. Data are available for three adoption scenarios: "AEO Reference Case", which is aligned with the U.S. EIA Annual Energy Outlook 2018 (linked below), "EFS High Electrification", which is aligned with the High Electrification scenario of the Electrification Futures Study (linked below), and "All EV Sales by 2035", which assumes that average passenger light-duty EV sales reach 50% in 2030 and 100% in 2035. The charging shapes are derived from two key assumptions of which data users should be aware: "ubiquitous charger access", meaning that drivers of vehicles are assumed to have access to a charger whenever a trip is not in progress, and "immediate charging", meaning that immediately after trip completion, vehicles are plugged in and charge until they are either fully recharged or taken on another trip. These assumptions result in a bounding case in which vehicles' state of charge is maximized at all times. This bounding case would minimize range anxiety, but is unrealistic from the point of view of both electric vehicle service equipment (EVSE) (i.e., charger) access, and plug-in behavior as it can result in dozens of charging sessions per week for battery electric vehicles (BEVs) that in reality are often only plugged in a few times per week.

Array↗

PV Hosting Capacity Estimation: Experiences with Scalable Framework

Hosting capacity is an indication of the amount of solar photovoltaics (PV) that can be hosted in a distribution system without additional changes to infrastructure or oper-ations. This paper presents a framework for estimating the PV hosting capacity at scale. First, we analyze computational, modeling and other key challenges of performing relevant, large-scale simulations, provided along with the experiences and lessons learned. Then, we develop two open-source Python-based software tools to conduct repeatable distribution analyses: the Distribution Integration Solution Cost Options (DISCO) for configuring and analyzing simulations and the Job Automation and Deployment Engine (JADE) for parallelizing jobs on high-performance computing clusters. A case study of hosting capacity estimation for the SMART-DS San Francisco (SFO) 2000+ synthetic feeders, is used to demonstrate the capability of the developed DISCO+JADE framework and tools. The framework and tools can help utilities assess the overall hosting capacity of their service territory, which can help them better plan for the overall upgrade costs to integrate more PV in the future. The experiences are shared to aid the tool users and researchers to conduct relevant studies and research.

distributed energy resources↗

JADE

JADE provides a simple, flexible interface to submit jobs to an HPC. JADE is an HPC workflow management system that enables researchers to run simulations efficiently. It provides a simple, flexible interface to define jobs, as well as dependencies between jobs, and then dispatch them to an HPC with maximized parallelization. It also provides detailed error reporting and resource utilization statistics to aid in debugging problems.

Thom, Daniel↗

PV Hosting Capacity Estimation: Experiences with Scalable Framework; Preprint

Hosting capacity is an indication of the amount of photovoltaics (PV) can be hosted in a distribution system. This paper presents a framework for estimating distributed PV hosting capacity at scale. We first analyze the key challenges of performing relevant large scale simulation including computational and modeling challenges. Then, we develop two python-based software tools in order to conduct repeatable distribution analyses: Distribution Integration Solution Cost Options (DISCO) for configuring and analyzing simulations, and JADE for parallelizing jobs on HPC clusters. A case study of hosting capacity estimation for SMART-DS SFO 2000+ synthetic feeders is used to demonstrate the capability of the developed framework and tools. The framework and tools can help utilities assess the overall hosting capacity of their service territory, through which the overall upgrade cost can be better planned in order to integrate more PV in the future.

distributed energy resources↗

dsgrid (Demand-Side Grid Toolkit) [SWR-21-52]

The demand-side grid model harnesses decades of sector-specific energy modeling expertise to understand current and future U.S. electricity load for power systems analyses. The API provides tools for submitting datasets to dsgrid projects, validating individual datasets and project data as a whole, querying, analysis, and visualization.

Hale, Elaine↗