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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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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A framework to quantify mass flow and assess food loss and waste in the US food supply chain

Abstract Reducing food loss and waste can improve the efficiency of food supply chains and provide food security. Here we estimate mass flow as well as food loss and waste along the US food supply chain for 10 commodity groups and nine management pathways to provide a baseline for designing efficient strategies to reduce, recycle, and recover food loss and waste. We estimate a total food loss and waste of 335.4 million metric tonnes from the U.S. food supply chain in 2016. Water evaporation (19%), recycling (55%), and landfill, incineration, or wastewater treatment (23%) accounted for most of the loss and waste. The consumption stage accounted for 57% of the food loss and waste disposed of through landfill, incineration, or wastewater treatment. Manufacturing was the largest contributor to food loss and waste (61%) but had a high recycling rate. High demand, perishable products accounted for 67% of food waste. We suggest that funding for infrastructure and incentives for earlier food donation can promote efficiency and sustainability of the supply chain, promote FLW collection and recycling along the U.S. FSC, and improve consumer education in order to move towards a circular economy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Cooperative Automated Cohort Driving on Connected Infrastructure, Arterial Roadways, and Highways: Final Project Demonstration and System-of-Systems Model Correlation

This project seeks to synergize vehicle automated driving and connectivity data to improve mobility and energy efficiency of groups of mixed vehicles operating in close proximity (vehicle cohort) on various infrastructure. A custom cellular communication network links vehicles operating as a cohort with infrastructure to a centralized system-of-systems digital twin with an AI-based optimal behavior planner. The data contained in this set are from final testing and technology demonstrations to U.S. Department of Energy staff at the American Center for Mobility. The data contain single-lane, single-light scenarios; multi-lane, multi-light arterial scenarios; and limited-access highway scenarios. All test cases were derived from simulations and replicated on the test track. The project employed two and four light-duty vehicles with connectivity and drive automation for the testing. The baseline scenario without connectivity was run under the control of the system-of-systems centralized planner but operating each vehicle with an intelligent driver model controlling the velocity, lane utilization, and vehicle gap. This was to ensure the highest compatibility with the simulation in terms of dynamic behavior. The connected cohort case utilized AI optimization to perform coordinated and cooperative control for energy, as well as safe, comfortable behavior for the cohort. The dataset is appropriately named with unconnected and connected designations, with comparisons sharing the same run index number. The included PowerPoint and PDF files describe the test setup and provide an overview of results from the project. ![image](de-EE0009209_March_2023_Data_Arterial_Scenario_Results.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

OR-AGENT framework – Architecting electrified heavy-duty drayage applications

The widespread adoption of zero-emission vehicles in heavy-duty (HD) commercial freight transportation faces considerable technoeconomic challenges. For heavy-duty trucks, ensuring high uptime, cost parity with diesel, and safety standards is especially critical as these vehicles operate over long distances with heavy loads, where any downtime or off-nominal behaviors significantly impacts logistics, productivity, and the total cost of ownership. Unlike traditional diesel refueling, BEV charging infrastructure must be co-optimized with vehicle deployment, operational demands, and grid capacity to ensure cost-effective and reliable freight operations. However, the lack of a standardized ownership and service model has led to a fragmented approach—where commercial vehicle operators may invest in, own, and maintain both vehicle/batteries and charging/energy infrastructure. This disconnect may exclude energy service providers from the equation, forcing fleet operators to explore ‘behind-the-fence’ energy solutions that increase capital investment, operational downtime, overhead costs, and, in some cases, net carbon emissions. To address these issues, this study introduces OR-AGENT (Optimal Regional Architecture Generation for Efficient National Transport), a comprehensive modeling framework that integrates powertrain architectures, charging infrastructures, and energy backbone systems into a cohesive strategy. In this paper, OR-AGENT is applied to develop an interconnected systems architecture for energy efficiency and resiliency enhancement of heavy-duty drayage vehicles at the Port of Savannah, GA. This framework showcases an interconnected systems approach to electrifying heavy-duty drayage vehicles at the Port of Savannah, GA. The study assessed BEVs with 400–1200 kWh battery capacities, accounting for seasonal variations in weather and freight routing. A diverse charging mix (150 kW–1250 kW) was evaluated alongside grid capacity constraints, cost, and carbon intensity analysis, leading to the development of a strategic microgrid/Distributed Energy Resources (DER) deployment architecture to ensure a reliable and sustainable transition. However, the findings also highlight the need for alternative zero-emission solutions for remaining trips, such as larger batteries, electrified roadways, hydrogen powertrains, or net-zero emission fuels. In conclusion, the findings are incorporated into a Total Cost of Ownership (TCO) model to identify optimal architectures for an interconnected electrified ecosystem.

Commercial vehicles↗
DOE OSTI2025

Bridging paradigms: Designing for HPC-Quantum convergence

Here, this paper presents a comprehensive software stack architecture for integrating quantum computing (QC) capabilities with High-Performance Computing (HPC) environments. While quantum computers show promise as specialized accelerators for scientific computing, their effective integration with classical HPC systems presents significant technical challenges. We propose a hardware-agnostic software framework that supports both current noisy intermediate-scale quantum devices and future fault-tolerant quantum computers, while maintaining compatibility with existing HPC workflows. The architecture includes a quantum gateway interface, standardized APIs for resource management, and robust scheduling mechanisms to handle both simultaneous and interleaved quantum–classical workloads. Key innovations include: (1) a unified resource management system that efficiently coordinates quantum and classical resources, (2) a flexible quantum programming interface that abstracts hardware-specific details, (3) A Quantum Platform Manager API that simplifies the integration of various quantum hardware systems, and (4) a comprehensive tool chain for quantum circuit optimization and execution. We demonstrate our architecture through implementation of quantum–classical algorithms, including the variational quantum linear solver, showcasing the framework’s ability to handle complex hybrid workflows while maximizing resource utilization. This work provides a foundational blueprint for integrating QC capabilities into existing HPC infrastructures, addressing critical challenges in resource management, job scheduling, and efficient data movement between classical and quantum resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

POINT: Partially Observable Imitation Network for Traffic Signal Control

Smart traffic signals bring together transportation infrastructure and advance technologies to improve the mobility and efficiency of urban transportation network. Adaptive traffic signal control studies can be categorized into modeling-based approaches and learning-based approaches. In order to take advantages of these two systems, this study developed an offline-online combined Partial Observable Imitation Network for Traffic signal control (POINT). In the offline system, the traffic signal timing optimization problem was formulated as a Mixed Integer Nonlinear Programming (MINLP) given complete traffic information, i.e., second-by-second speeds and locations of all vehicles. Furthermore, the objective of MINLP is to minimize total travel delays considering individual vehicle trajectories under Connected Vehicle (CV) environment. The calculated optimal solutions under various traffic conditions were considered as the ”expert” decisions. In the online system, an imitation neural network model was developed to learn the ”expert” signal plans generated from offline system. Given partial observable traffic conditions in real time, e.g., the aggregate-level of traffic volume, the POINT model can compute the signal timing parameters in the online system. The numerical results demonstrated that the proposed method outperformed other state-of-the-art signal control method under high and unbalanced traffic demand levels in terms of reducing travel delays and queue length.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Sparsely Dispersed CeO x ‑Stabilized Pt Nanoparticles Overcome Pt Loading–Durability Trade-Off for Highly Durable Heavy-Duty Fuel Cells

Proton-exchange-membrane fuel cells (PEMFCs) are clean and sustainable mobile power sources for transportation. Recently, their deployment in heavy-duty vehicles (HDVs) has attracted growing interest owing to their high energy scalability and lower infrastructure requirements. However, to meet the stringent requirements for efficiency and long-term durability for HDV applications, PEMFCs typically employ a relatively high platinum group metal (PGM) loading (>0.2 mg PGM /cm 2 ). This elevated PGM loading significantly increases the stack and system costs, surpassing the U.S. Department of Energy (DOE) target of $\$ 60$/kW for commercial viability. Reducing PGM loading while maintaining performance and durability remains a central challenge for HDV fuel cells. Here we exploit metal oxide–Pt interactions and utilize the strong CeO x –Pt interaction to design a CeO x @Pt catalyst structure with exceptional durability. At a low total PGM loading (0.1 mg PGM /cm 2 ), the CeO x @Pt/C catalyst demonstrates high fuel cell performance (8.8 kW/g PGM ) and stability (power retention >90%) after the challenging HDV durability testing (90,000 accelerated-stress-test cycles). With the CeO x @Pt/C catalyst, we showcase over 70% reduction in Pt cost from the M2FCT target (to $\$ 9$/kW), highlighting its promising potential for enabling stable and cost-effective fuel cell systems for heavy-duty applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Mitigating urban heat island and enhancing indoor thermal comfort using terrace garden

The United Nations advocates for sustainable urban planning and design, emphasizing green infrastructure initiatives to mitigate urban heat island effects and enhance the resilience and livability of cities globally. To address urban heat challenges, a study was conducted in Chennai, India, from April to June 2023. The study focused on assessing temperature dynamics on a building's terrace by comparing a well-maintained garden area with an exposed region. Temperature and humidity sensors were deployed in both the garden and exposed areas of the terrace, as well as within rooms beneath it, to monitor hourly temperature fluctuations. The findings indicate a significant reduction in internal room temperatures in areas with rooftop gardens, ranging from 4 to 11 °C, depending on the time of year and sun's position, compared to rooms with fully exposed roof configurations. Additionally, simulation studies were performed to validate these findings, suggesting that optimizing the distribution of soil beds and plant density across the roof could yield an additional temperature reduction of 3–4 °C, resulting in an overall difference of up to 14–15 °C. The study highlights the efficacy of rooftop gardens in providing cooling effects during daylight hours and maintaining temperature parity post-sunset. Through analysis of sensor data, the research elucidates the intricate relationship between green infrastructure and thermal comfort, offering insights for energy-efficient building design and resilient urban planning. The findings underscore the potential of rooftop gardens in fostering a more comfortable, energy-efficient, and sustainable urban living environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Evaluating Supply Prioritization Strategies for Risk-Informed Decision Making in an Arbitrary Gas Network

Supply disruptions and infrastructure failures in natural gas networks present critical challenges to energy reliability and risk-informed planning. This study evaluates two supply prioritization strategies, Maximum Delivery Prioritization (MDP) and Demand-Based Prioritization (DBP), within an arbitrary natural gas network under conditions of supply shortage. Model performance under both strategies is assessed in response to node and edge failure using demand satisfaction metrics, system-wide and localized dependency scores, and geographic information system (GIS)-based spatial analysis. Results show that DBP better preserves supply for high-demand nodes, while MDP offers broader coverage. The underlying network topology plays a critical role in shaping prioritization outcomes. Integrated GIS visualization enhances the interpretability of vulnerability assessments, revealing structurally critical components and localized vulnerabilities. The proposed framework supports scalable, data-driven decision-making for infrastructure planners and engineers, enabling improved disruption recovery and efficiency in constrained natural gas networks. These insights contribute to the development of more robust energy systems capable of withstanding stress and disruptions.

Peterson, Steven [ORNL] (ORCID:0000000287672998)↗
DOE OSTI2020

Distribution Transformer Health Monitoring using Smart Meter Data

The distribution electric grid has become a highly complex and intelligent network with changing load and customer types. This has generated unprecedented challenges and opportunities for utility companies–opportunities especially in the area of asset health/performance management. Moreover, several utilities are increasingly moving from the traditional reactive and time-based asset monitoring approach to a more proactive condition based method. However, this needs to be done in a low-cost and efficient manner. Here, this paper explores how existing sensor infrastructure such as smart meters can be utilized to provide utility operators with more visibility into the health and operation of their assets. The paper focuses primarily on service transformers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

An Observational Understanding of Connected Lighting Systems

As part of the Internet of Things (IoT), connected lighting systems provide additional control capabilities and nonlighting-related services (such as communications and data infrastructure) to reduce energy use while increasing both application efficiency and system value. But the positive or negative energy impact of implementing these systems is still largely unknown due to the variety of human factors associated with installation, maintenance, and use. These complications interfere with adoption and acceptance rates of products that will play a significant role in achieving energy savings long-term. Next Generation Lighting Systems, or NGLS, developed and implemented an observational research methodology for connected lighting systems. The methodology was implemented at an indoor (classroom/office) Living Lab at Parsons School of Design in New York City, and an outdoor (parking lot) Living Lab at Virginia Tech Transportation Institute in Blacksburg, Virginia. Although this report focuses on the approach to indoor installations, observational research in both settings provides insight to the type, scale, and frequency of issues across available products as experienced by installing contractors, end users, and other stakeholders.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Resilient Communities, Maryland (RCM): A Framework for Community-Driven Energy Resilience (Final Technical Report)

The Resilient Communities, Maryland (RCM) project integrates community-based participatory research (CBPR) approaches into energy resilience planning. The combination of qualitative, community-driven data and quantitative utility data improves both the effectiveness and efficiency of assessing the impacts of disruptions to energy infrastructure. Centered around a metric of critical services access, RCM created a repeatable framework for evaluating and modeling energy resilience in communities and promoted community engagement, resulting in more equitable stakeholder participation and improved decision-making processes for siting infrastructure to improve community energy resilience.

14 SOLAR ENERGY↗
DOE OSTI2024

Improving the Concrete Crack Detection Process via a Hybrid Visual Transformer Algorithm

Inspections of concrete bridges across the United States represent a significant commitment of resources, given their biannual mandate for many structures. With a notable number of aging bridges, there is an imperative need to enhance the efficiency of these inspections. This study harnessed the power of computer vision to streamline the inspection process. Our experiment examined the efficacy of a state-of-the-art Visual Transformer (ViT) model combined with distinct image enhancement detector algorithms. We benchmarked against a deep learning Convolutional Neural Network (CNN) model. These models were applied to over 20,000 high-quality images from the Concrete Images for Classification dataset. Traditional crack detection methods often fall short due to their heavy reliance on time and resources. This research pioneers bridge inspection by integrating ViT with diverse image enhancement detectors, significantly improving concrete crack detection accuracy. Notably, a custom-built CNN achieves over 99% accuracy with substantially lower training time than ViT, making it an efficient solution for enhancing safety and resource conservation in infrastructure management. These advancements enhance safety by enabling reliable detection and timely maintenance, but they also align with Industry 4.0 objectives, automating manual inspections, reducing costs, and advancing technological integration in public infrastructure management.

42 ENGINEERING↗
DOE OSTI2024

Exploring impacts of electricity tariff on charging infrastructure planning: An activity-based approach

In the past decade, electric vehicles (EVs) have gained popularity for their efficiency and environmental benefits. Advances in battery technology and charging equipment have yielded long-range EVs and fast-charging. However, many major cities lack adequate charging infrastructure for daily EV use. This study addresses this gap by integrating activity-based modeling, charging behavior simulation, and charging infrastructure optimization. The research utilizes the POLARIS agent-based transportation model to accurately capture user activities, trip patterns, and traffic flows. Additionally, the study investigates the impact of fixed and spatiotemporal electricity rate distributions on optimal charging infrastructure deployment. The framework is applied to the Chicago regional area network and analyzed under various EV ownership scenarios. Further, the results reveal significant impacts of the charging pricing strategy on user decision-making and charging demand distribution. There is also a need for consistent pricing policies in charging infrastructure planning and operational phases to avoid drops in service quality.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Kansas City, Missouri, Streetlight Electric Vehicle Charging: Strategies and challenges for site selection of streetlight electric vehicle infrastructure in Kansas City, Missouri (Final Report)

Public streetlight charging, whether on streets in central business districts or residential areas, provides easy charging access for apartment residents and homeowners alike. While most electric vehicle (EV) drivers charge at home, they do so in garages or on driveways they own. For renters and residents of multifamily housing (MFH), however, this may not be an option. EVs have a lower cost of ownership compared to conventional vehicles, and a used EV may be an affordable option for a lower-income household. But without easy access to charging, even a low-cost used EV may not be an option for a prospective buyer. An affordable curbside charging network has the potential to expand EV adoption into neighborhoods that have to date seen minimal interest and uptake of the technology and associated charging infrastructure. Streetlight charging networks can provide an economical, scalable, and effective approach to providing equitable and convenient charging. Metropolitan Energy Center (MEC) is dedicated to the mission of creating resource efficiency, environmental health, and economic vitality in the Kansas City region and beyond. Since 1983, MEC has provided resources, outreach, and training to make alternative fuels and energy efficiency commonplace. MEC led a streetlight charging pilot project that installed limited EV charging infrastructure on the streetlight system in Kansas City, Missouri, to demonstrate and test the benefits of curbside charging for EVs at existing on-street parking locations. The project aimed to cost-effectively expand the charging network in Kansas City to support residential charging and provide infrastructure in one or more charging deserts throughout the city. This pilot evaluates the impact and overall success of streetlight charging based on community feedback, utilization of charging infrastructure, technical feasibility, and cost. The project has pursued a data- and community-driven site selection process designed to identify sites with high demand and high opportunity for EV charging. This project was funded by the U.S. Department of Energy (DOE) and awarded to MEC through a competitive proposal process. The novelty and complexity of this project required an organization that could facilitate collaboration across levels of government, community members, and industry partners. For the past 25 years, through Kansas City Regional Clean Cities, MEC has worked with numerous public and private fleets on a variety of projects to improve the environmental performance and efficiency of the regional vehicle fleet. To advance affordable, efficient, and clean transportation efforts, DOE Clean Cities and Communities coalitions create local networks of public and private sector stakeholders and engage communities. Rooted within their local communities, the coalitions serve as experts and ambassadors, bringing to bear the collective knowledge, experience, and practical know-how of the entire network from within DOE, its national laboratories, and diverse stakeholders in the field. MEC and its project partners made in-kind contributions to leverage federal dollars for the benefit of the Kansas City community. Findings from this project will help determine the best applications for streetlight charging technologies to maximize funding impact and serve community needs. The team evaluated locations based on expected charging demand, technical feasibility, safety considerations, and enhanced charging network siting needs. Throughout the project, the team gathered feedback and evaluated ways to make public charging for EVs available to all community members. The insights will help Kansas City and other communities streamline future efforts to support EV drivers through public charging in the city right-of-way. Furthermore, this project will inform citywide guidance for future installations. MEC is committed to a transparent and publicly accessible approach that encourages the collaborative evaluation of streetlight charging. The project has engaged the community to proactively identify and evaluate the benefits and impacts of streetlight charging. It was a priority for the project to ensure the benefits of this pilot are distributed equitably to all members of the Kansas City community and that new charging opportunities and associated resources are available in diverse neighborhoods across the city. The charging infrastructure supports an affordable curbside charging network that will enable more drivers to choose EVs and provide easy charging access for all community members interested in driving an EV. The community feedback received through this project informed future resources and opportunities to make EVs more accessible to all members of the Kansas City community. MEC worked with several community partners on this project, including Missouri University of Science and Technology (MST), Pennsylvania State University (Penn State), the National Renewable Energy Laboratory (NREL); the city of Kansas City, Missouri; Evergy; Black and McDonald (B&M); LilyPad EV; EVNoire; and Westside Housing Organization (WHO). Project partners contributed to the cost match required for DOE grants through capital expenditures, personnel, and other in-kind contributions. Detailed descriptions of project team organizations can be found in Appendix A. Project Partners. Analysts at NREL and MST/PennState developed site maps based on demand and equity considerations. MEC conducted outreach to community members to garner input on project design and site selection, and received approval from the Missouri Public Service Commission (PSC) for Evergy’s EV charging station ownership. MEC worked with all partners to gather additional siting criteria and developed a site selection evaluation checklist, and partners conducted site visits to proposed installation sites. Next, B&M, Evergy, and the city executed all site agreements, conducted site-specific engineering design, acquired associated permits, and issued notices to proceed site by site or in small batches. Finally, from January to April 2023, the project team installed 23 EV charging stations built on Kansas City’s streetlight system in six council districts. Evergy will own, operate, and monitor the stations for 10 years, sharing charging data with MEC for at least 1 year.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Simulation-Guided Decision-Making for Enhancing Energy Resilience in a Remote Alaskan Community

The increasing frequency and severity of extreme weather events underscore the need to bolster the resilience of energy infrastructure in remote coastal communities exposed to climate hazards. In recent years, considerable effort has been made to harden the grid infrastructure of remote communities through investment in energy storage, advanced metering, renewable generation and energy-efficient loads. However, simulation-based studies are still needed to identify appropriate locations for investment and determine the adequacy of existing infrastructure in supporting new resources. Preparing the required models may often be challenging due to insufficient metering, disparate data sources and workforce limitations. This paper describes modeling efforts undertaken to represent, within a unified co-simulation platform: (a) the electric distribution network and (b) the thermal behavior of a community medical center, in the remote community of Cordova, Alaska. With the help of case-studies, it is shown how the developed simulation platform can help the local utility in making decisions regarding capital investment aimed at enhancing community resilience.

Microgrid, energy storage, resilience↗
DOE OSTI2023

Policy Framework to Improve Mobility Efficiency and Electrify Transportation in Tonga

The Kingdom of Tonga, like many small island developing states, is heavily dependent on imported fossil fuels to meet its current energy needs, especially for transportation. The Kingdom has requested a policy framework that benefits its land transportation sector by saving cost and time, increasing resilience, and reducing petroleum and greenhouse gas (GHG) emissions. This framework was developed by building on past work, namely the Tonga Energy Efficiency Master Plan 2020-2030 (TEEMP), the Tonga Energy Road Map 2021-2035 (TERMPLUS), and the Regional Electric Mobility Policy for Pacific Island Countries and Territories developed by the Pacific Centre for Renewable Energy and Energy Efficiency (PCREEE). The strengths, weaknesses, opportunities, and threats to Tonga's land transportation system were identified at stakeholder working group meetings in Tonga in June 2023. A set of appropriate policies that have been effective in relevant jurisdictions were then discussed and refined by the working group. The resulting 27 policies are defined according to intended outcomes, relationship to other proposed policies, applications in other relevant jurisdictions, hurdles to implementation, resilience impact, equity impact, and government revenue impact. Some of the policies are also accompanied by implementation recommendations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Catalytic Fast Pyrolysis Oil Stand-Alone and Co-Hydroprocessing Case Studies: Design, Cost, and Sustainability Based on Process Model Predictions

Refined liquid fuels provide conveniences for road, rail, air, and marine transportation due to high energy density, ease of transport and storage, and existing production and distribution infrastructure. Biomass conversion technologies can help diversify and increase the supply of liquid fuels towards a more robust energy future. The backbone of such development must include reliable, high-volume biomass supply chains and efficient utilization of those resources. These activities, if pursued, will lead to rural infrastructure development and new jobs.

09 BIOMASS FUELS↗
DOE OSTI2020

Spatio-temporal impacts of a utility’s efficiency portfolio on the distribution grid

Energy Efficiency has historically focused on delivering savings to offset growth in energy supply. Today’s growing emphasis on decarbonization of the energy supply is driving renewables adoption and increased interest in electrification. As a result, energy efficiency is being assessed not just in its ability to offset load growth, but also for its ability to alleviate location-specific constraints on transmission and distribution infrastructure. This work demonstrates that advanced measurement and verification modeling techniques can be used to estimate the spatio-temporal grid impact of a portfolio of energy efficiency programs. It extends measurement-based methods to an entire Demand Side Management portfolio and uses a single model to predict annual as well as seasonal building energy use with near-zero bias. In addition, new metrics are introduced to assess grid level impacts of energy efficiency. The results show that the efficiency program portfolio delivers savings of over 12% at the territory-wide proxy level, with substation and feeder level savings ranging from 0.4% to 26%, and ~5%-42% respectively. Overall, these savings impacted 1.0%–1.4% of the energy used at these locations in the grid. This work provides a methodology with potential to connect efficiency with distribution planning, carrying implications for non-wires alternatives and targeted delivery of efficiency programs.

24 POWER TRANSMISSION AND DISTRIBUTION↗