Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “planned”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Distribution Capacity Expansion Planning: Current Practice, Opportunities, and Decision Support

The distribution utility industry and its engineers are experiencing monumental shifts in consumer needs and expectations. Characterizing future native loads as compared to net load demand for long-term capacity planning is especially difficult, as consumers are increasingly adopting prosumer technologies. This paper is the culmination of 5 months of utility interviews coordinated by the National Renewable Energy Lab (NREL) and Kevala, Inc. (Kevala) to better understand distribution capacity planning challenges. The interviews covered all aspects of capacity planning including load and DER forecasting, criteria for assessing system constraints, solution types, and organizational and decision-making structures. Our intent is to provide insight into distribution capacity planning decision support needs for utilities and the increasing number of stakeholders involved, from state and regulatory agencies to community and solution providers with interest in increasing their understanding in the distribution capacity planning process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Community Energy Planning: Best Practices and Lessons Learned in NREL's Work with Communities

The clean energy transition is accelerating due to local, state, and national actions combined with external market forces. Regardless of where goals are set and decisions are made, clean energy deployment occurs on the ground in communities. As a result, communities increasingly need technical expertise and assistance with planning for and managing the energy transition. Building on decades of work with state, local, and tribal jurisdictions, the National Renewable Energy Laboratory (NREL) increasingly provides community-driven modeling, analysis, and technical assistance to enable more data-driven and equitable community energy planning. To inform and enhance NREL's capabilities in community energy planning and provide a resource for others working in this space, the Joint Institute for Strategic Energy Analysis (JISEA) Sustainable Communities Catalyzer supported this best-practices presentation based on interviews with seasoned NREL practitioners and a literature review on equitable community energy planning. Findings include five best practices for community energy planning that NREL practitioners and others can apply to strengthen their impact: 1) do your homework in preparation for community interactions; 2) be humble, authentic, and honest in your interactions with community members; 3) respect community agency in every step of the process; 4) meet the community where they are; 5) democratize participation.

best practices↗
DOE OSTI2026

Municipal Fleet Action Plan Guide

This action plan template and guide have been designed to support light-duty or medium-duty municipal fleet managers as they plan to adopt electric vehicles. The resource is an adaptation of content created by the National Laboratory of the Rockies (NLR), with support from World Resources Institute (WRI), for participants in the U.S. Department of Energy's Energy to Communities peer-learning cohort, Charting a Path to Municipal Fleet Electrification. Fifteen participating municipalities joined monthly cohort workshops from July through December 2024 to learn and plan for their own fleet electrification. Clean Cities and Communities coalitions supported participating municipalities throughout the cohort series by conducting fleet analysis and planning activities on their behalf. This template is an adapted version of cohort activities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Development and Clustering of Rate-Oriented Load Metrics for Customer Price-Plan Analysis

One of the few methods electric utilities can use to motivate and change customer energy consumption is through retail rate structures. Utilities are increasingly moving toward more dynamic rate plans to encourage energy conservation, utilization of onsite renewable generation, peak demand reduction and flattening of demand profiles. This paper creates a set of rate-oriented load metrics that are the determinants of customers' bills under four unique rate plans. These metrics are not only indicative of which rate structure can provide customer bill reductions based on their load profile characteristics, but also convey useful information about load consumption behavior. With these metrics, utilities can analyze their customers and identify classes that are rewarded under each rate plan. This can help inform utilities whether the customers rewarded under each rate plans are meeting their original objectives. To develop these customer classes, we calculate these rate-oriented load metrics for each customer and perform k-means clustering. The analysis is conducted on a set of 300 customer profiles, examining four different rate plans, different numbers of clusters, customer bills and cluster load profile characteristics.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Performance Evaluation of District Energy Microgrids Planning Tool for Non-Technical Users

Community Microgrids are increasingly gaining popularity worldwide for their efficiency, cost-effectiveness, and local resilience improvement. Microgrid planning tools play a crucial role in their deployment. In the process, tentative designs of the microgrid are simulated, analyzed, and optimized. Due to the complexity of the problem, planning tools must carefully balance computational efficiency while seeking the most optimal solutions. This paper investigates the impact of algorithm selection on CPU and memory utilization of a Community Microgrid planning tool that is specifically designed for non-technical users. We compare two version of the code with two alternatives for Community Microgrid planning tools: a Greedy Algorithm, and a Linear Programming Approach. This comparison examines scenarios spanning from 2 to 50 buildings. Our findings revealed a significant difference in performance between the two algorithms, underscoring the critical role of algorithm selection in optimizing the efficiency of Community Microgrid Planning Tools.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Long Range Community Planning Process for Fusion Sciences and Plasma Physics (Final Technical Report)

This grant facilitated the APS-DPP Community Planning Process (DPP-CPP) which was a strategic planning process with the goals of identifying scientific and technological opportunities in the fields of Plasma Physics and Fusion Energy Science, and making consensus recommendations for a strategy to address these opportunities to the DOE Office of Fusion Energy Science Advisory Committee (FESAC). The DPP-CPP was initiated by the APS-DPP executive committee in order to help FESAC fulfill a charge from DOE to develop a strategic plan for the DOE Office of Fusion Energy Science (FES). In this charge, the DOE Deputy Director for Science, Dr. Stephen Binkley, requests “that the Fusion Energy Sciences Advisory Committee (FESAC) undertake a new long-range strategic planning activity for the Fusion Energy Sciences (FES) program. The strategic planning activity - to encompass the entire FES research portfolio (namely, burning plasma science and discovery plasma science) - should identify and prioritize the research required to advance both the scientific foundation needed to develop a fusion energy source, as well as the broader FES mission to steward plasma science.” The process as set out in the proposal (and below) was successful in meeting all of its stated goals culminating in the final report to the FESAC subcommittee given the charge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Current Practices in Distribution Utility Resilience Planning for Winter Storms

This report is part of a series of hazard-focused case studies examining common practices in electric utility resilience planning. We use standard terminology defining resilience as the ability to anticipate, withstand, absorb, and recover from hazards that cause long duration outages. We distinguish between reliability and resilience using Institute of Electrical and Electronics Engineers (IEEE) 1366-2022, which defines major events as an event that exceeds reasonable design and/or operational limits of the electric power system. Resilience planning is focused on major event days and reliability planning is focused on nonmajor event days. Utility resilience plans are assessed according to common resilience components identified in existing resilience frameworks. The focus of this report is on winter storms in which the primary hazards are heavy snowfall, freezing rain, ice, extreme cold, severe wind, and flooding. These hazards can also contribute to generation shortages, resulting in bulk power system impacts that have consequences for the distribution system, such as load shedding. Stand-alone reports focusing on wildfires and nonwinter storms have been published in parallel with this report. This report can be used as a starting point for understanding potential investment prioritization processes and investment options. This report is intended to improve utility resilience planning by supporting constructive dialogue among utilities, regulators, and other stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Current Practices in Distribution Utility Resilience Planning for Wildfires

This report is part of a series of hazard-focused case studies examining common practices in electric utility resilience planning. We use standard terminology defining resilience as the ability to anticipate, withstand, absorb, and recover from hazards that cause long duration outages. We distinguish between reliability and resilience using IEEE 1366-2022, which defines major events as "an event that exceeds reasonable design and/or operational limits of the electric power system." Resilience planning is focused on major event days, and reliability planning is focused on non-major event days. Utility resilience plans are assessed according to common resilience components identified in existing resilience frameworks. The focus of this report is on wildfires. Standalone reports focusing on severe storms (including hurricanes and non-winter storms) and winter storms have been published in parallel with this report. This report can be used as a starting point for understanding potential investment prioritization processes and investment options. This report is intended to improve utility resilience planning by supporting constructive dialogue among utilities, regulators, and other stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Current Practices in Distribution Utility Resilience Planning for Hurricanes and Non-Winter Storms

This report is part of a series of hazard-focused case studies examining common practices in electric utility resilience planning. We use standard terminology defining resilience as the ability to anticipate, withstand, absorb, and recover from hazards that cause long duration outages. We distinguish between reliability and resilience using IEEE 1366-2022, which defines "major events" as "an event that exceeds reasonable design and/or operational limits of the electric power system." Resilience planning is focused on "major event days" and reliability planning is focused on non-major event days. Utility resilience plans are assessed according to common recommended resilience components that we have identified in existing resilience frameworks. The focus of this report is on hurricanes and severe storms in which the primary hazards are precipitation or high winds. We exclude winter storms with primary hazards of ice and extreme cold, as they are a unique set of hazards with different resilience considerations. Standalone reports focusing on wildfires and winter storms have been published in parallel with this report. This report can be used as a starting point for understanding potential investment prioritization processes and investment options. This report is intended to improve utility resilience planning by supporting constructive dialogue among utilities, regulators, and other stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Opportunities for Integrating Electric and Gas Planning

Growing demand for electricity in buildings is creating new opportunities and challenges for electric and natural gas planning. To date, electric and gas planning processes have largely been siloed, and only a few jurisdictions have started to examine how these two processes could be linked together. The report explores the current state of electric and gas system planning, and the benefits and challenges of integrating these planning processes. We frame the characteristics of an integrated electric and gas distribution planning process and identify indicators of progress toward the characteristics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Key Takeaways: First Cohort of Action Plans for Rapid Power Sector Decarbonization

The purpose of this synthesis report is to extract key takeaways from the first cohort of CEM Action Plans for rapid power sector decarbonization, developed by Australia, Chile, the European Union, India, and the United Kingdom. These Action Plans differ in their approach to power sector decarbonization based on the domestic resources available, governance structure, and regional context, among other factors. However, they also share common themes that were emphasized in the collaborative report released at CEM13. This report is not intended to be inclusive of all components in each Action Plan. Rather, this report highlights how select best practices for planning, building, and operating power systems are being implemented differently in these Action Plans, with equal focus given to each jurisdiction. Ministers and stakeholders from other governments with similar decarbonization goals can consider these examples within their own unique context.

Australia↗
DOE OSTI2025

Advanced Fuels Campaign Execution Plan

The Advanced Fuels Campaign (AFC) Execution Plan details the strategy, mission, scope, and goals—both near-term and long-term—along with the structure and organization of nuclear fuels and materials research, development, and demonstration (RD&D) activities within the Fuel Cycle Technologies (FCT) program. The FCT program, tasked by the U.S. Department of Energy (DOE), employs a science-based approach to advance fuel technologies. This approach integrates theory, experiments, and multi-scale modeling and simulation (M&S) to develop a predictive understanding of fuel fabrication processes and fuel/cladding performance under irradiation, moving beyond traditional empirical methods. The long-term goals of the AFC are guided by the AFC Strategic Plan and align with the DOE Office of Nuclear Energy (NE) Roadmap [1], which outlines a multi-decade vision for demonstrating and qualifying advanced fuel forms to support diverse fuel cycle options. Near-term goals focus on enhancing accident tolerant fuels (ATF) for Light Water Reactors (LWR), a significant challenge that demands balancing immediate objectives with ongoing progress toward advanced reactor missions. Accelerating the traditional fuel qualification process to meet ATF objectives is another critical challenge. A detailed set of 5-year goals, summarized below, has been developed in line with the overarching science-based fuel development approach: • Advanced LWR Fuel Technologies: By 2027, support the development of advanced LWR fuel technologies with improved performance and enhanced accident tolerance. This includes high burnup (HBu), low enriched uranium (LEU)+, coated cladding, and doped fuel, aimed at complementing industry-led significant LWR uprates and plant refurbishments. • Tristructural Isotropic (TRISO) Fuel: Achieve qualification by 2028 and develop improved designs for emerging markets. • Metal Fuel: Achieve qualification by 2028 and develop improved designs for emerging markets. • Molten Salt Fuel: By 2027, deploy a robust program that enables fuel salt qualification technologies needed to support fuel salt research and development (R&D), focusing on emergent needs to derisk fuel salt production and utilization in advanced reactors. • Long-Term ATF: Develop fuel technologies that enable significant power uprates (~50%) in refurbished or new LWRs while optimizing fissile material utilization and waste disposal. The 5-year milestones in the AFC Execution Plan are contingent on an assumed budget. This Execution Plan will be updated annually to reflect actual funding profiles as budget guidance becomes available, ensuring milestones are adjusted accordingly. In summary, the AFC Execution Plan presents a comprehensive strategy to advance nuclear fuel technologies through a science-based approach, addressing both near-term and long-term goals while adapting to funding realities.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Considerations for Resilience Guidelines for Clean Energy Plans: For the Oregon Public Utility Commission and Oregon Electricity Stakeholders

This document summarizes relevant approaches, research, models, and national examples for state utility regulators tasked with developing utility guidelines for risk-based resiliency planning. In 2021, the Oregon Legislature enacted a 100 percent clean electricity by 2040 standard that requires the Oregon Public Utility Commission (PUC) to oversee utility planning for aggressive clean energy deployment through Clean Energy Plans (House Bill 2021, Sec. 4). In addition to meeting emissions reductions targets, Clean Energy Plans must also: "Include a risk-based examination of resiliency opportunities that includes costs, consequences, outcomes, and benefits based on reasonable and prudent industry resiliency standards and guidelines established by the Public Utility Commission." This report will support the Oregon Public Utility Commission in developing resilience guidelines. Other state public utility commissions may also benefit from this research.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Selection of Global Climate Model Data for Downscaling With Generative Machine Learning and Use in the Power Planning for Alignment of Climate and Energy Systems Project

The range of results from climate models and scenarios is important to the understanding of uncertainty in power planning analysis. A U.S. Department of Energy-funded analytic project called Power Planning for Alignment of Climate and Energy Systems is developing data and analytic methods to reflect the effects of climate change on key variables for power system planning, as part of the Grid Modernization Lab Consortium. This project will select and prepare global climate model results for use in power system planning models. A related report (Evaluation of Global Climate Models for Use in Energy Analysis) assesses the performance of various global climate models from the Coupled Model Intercomparison Project Phase 6 data archive for their historical skill with respect to energy system performance and for their future projections under multiple climate change scenarios. Building from that report, we describe the selection of a climate scenario (Shared Socioeconomic Pathway [SSP] 2-4.5) and five climate models: TaiESM1, EC-Earth3-CC, GFDL-CM4, EC-Earth3-Veg, and MPI-ESM1-2-HR. We describe the model selection criteria, which were based on the quality of the match between model results under historical conditions and on the representation of the range of future values for several variables. These results will be downscaled via an open-source generative machine learning method called Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

The ReSWARM microgravity flight experiments: Planning, control, and model estimation for on‐orbit close proximity operations

Abstract On‐orbit close proximity operations involve robotic spacecraft maneuvering and making decisions for a growing number of mission scenarios demanding autonomy, including on‐orbit assembly, repair, and astronaut assistance. Of these scenarios, on‐orbit assembly is an enabling technology that will allow large space structures to be built in situ, using smaller building block modules. However, like many of these scenarios, robotic on‐orbit assembly involves several technical hurdles, such as changing system models. For instance, grappled modules moved by a free‐flying “assembler” robot can cause significant changes in the combined system inertia, which have cascading impacts on motion planning and control portions of the autonomy stack. Further, on‐orbit assembly and other scenarios require collision‐avoiding motion planning, particularly when operating in a “construction site” scenario of multiple assembler robots and structures. Multiple key technologies that address these complicating factors for autonomous microgravity close proximity operations are detailed in this work, in particular: (1) application of global long‐horizon planning, accomplished using offline and online sampling‐based planner options that consider the system dynamics; (2) adaptation of the recently proposed RATTLE information‐aware planning framework for on‐orbit reconfiguration model learning; and (3) connection with robust control tools to provide low‐level control robustness using current system knowledge. These approaches were demonstrated for an autonomous on‐orbit assembly use case by the RElative Satellite sWarming and Robotic Maneuvering (ReSWARM) experiments using NASA's Astrobee robots on the International Space Station. Results of the ReSWARM experiments are provided along with significant operational and implementation detail discussing the practicalities of hardware implementation and unique aspects of working with the Astrobee free‐flyer robots in microgravity. ReSWARM provides a base set of planning and control tools for robotic close proximity operations, demonstrates them in microgravity, and outlines some of the important hardware aspects that future autonomous free‐flyers will need to consider.

Robotics↗
DOE OSTI2026

Automated Signal Timing Plan Reconstruction Using High-Resolution Event-Based Controller Data for Digital Twins

Transportation digital twins are essential tools for evaluating emerging technologies such as connected and automated vehicles, adaptive traffic signal control, and mobility optimization strategies. Realistic digital twins require accurate emulation of real-world signal controllers and detailed signal timing plans. However, signal timing plans are often unavailable or difficult to access, forcing researchers and modelers to rely on assumed fixed timings or halt their analysis. To overcome this challenge, we present a method that directly estimates signal timing plan parameters using high-resolution, event-based data from traffic signal controllers. The proposed method extracts key parameters, including cycle length, offset, phase sequence, coordinated phases, phase-specific minimum and maximum green durations, vehicle extensions, and splits under coordination. A rule-based deterministic signal timing reconstruction algorithm based on traffic signal operation rules, such as those outlined in the Signal Timing Manual, is developed and validated. We evaluate this method, which uses high-resolution controller event logs and verified signal timing plans, on 94 signalized intersections in Nashville, Tennessee, demonstrating their ability to generate accurate, simulation-ready signal timing plans for tools such as SUMO and Vissim.

Saroj, Abhilasha [ORNL] (ORCID:0000000191178063)↗
DOE OSTI2020

Optimizing Individualized Treatment Planning for Parkinson’s Disease Using Deep Reinforcement Learning

More than one million people currently live with Parkinson's Disease (PD) in the U.S. alone. Medications, such as levodopa, can help manage PD symptoms. However, medication treatment planning is generally based on patient history and limited interaction between physicians and patients during office visits. This limits the extent of benefit that may be derived from the treatment as disease/patient characteristics are generally non-stationary. Wearable sensors that provide continuous monitoring of various symptoms, such as bradykinesia and dyskinesia, can enhance symptom management. However, using such data to overhaul the current static medication treatment planning approach and prescribe personalized medication timing and dosage that accounts for patient/care-giver/physician feedback/preferences remains an open question. We develop a model to prescribe timing and dosage of medications, given the motor fluctuation data collected using wearable sensors in real-time. We solve the resulting model using deep reinforcement learning (DRL). The prescribed policy determines the optimal treatment plan that minimizes patient's symptoms. Our results show that the model-prescribed policy outperforms the static a priori treatment plan in improving patients' symptoms, providing a proof-of-concept that DRL can augment medical decision making for treatment planning of chronic disease patients.

Watts, Jeremy↗
DOE OSTI2026

Netload Range Cost Curves for Coordinated Transmission-Distribution Planning Under DER Growth Uncertainty

The increasing penetration of distributed energy resources (DERs) requires better coordination between transmission and distribution (T&D) planning to ensure system security and cost efficiency. However, misaligned planning horizons, computational burdens, and privacy concerns hinder effective coordination, leading to either underutilized resources caused by overinvestments or reliability risks due to underinvestment. To address this challenge, we introduce netload range cost curves (NRCCs), a novel approach for managing long-term DER growth uncertainty through T&D coordination, while preserving existing data-sharing and regulatory structures. NRCCs provide pairs of (i) peak substation netload guarantees and (ii) corresponding distribution upgrade options and costs, enabling their seamless integration into transmission planning workflows. To compute NRCCs efficiently, we develop a transmission-aware distribution network planning (TADNP), which is subsequently integrated to an iterative computation procedure. These NRCCs are then embedded into an NRCC-informed transmission planning model to enable resource-efficient coordination. We illustrate our proposed approach with a case study based on realistic distribution and transmission systems in the San Francisco Bay Area, California. Our results indicate the possibility of dramatic savings in transmission investments by incorporating the proposed NRCC-integrated T&D coordination framework.

Li, Yujia↗