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At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Rising infrastructure inequalities accompany urbanization and economic development

Impending global urban population growth is expected to occur with considerable infrastructure expansion. However, our understanding of attendant infrastructure inequalities is limited, highlighting a critical knowledge gap in the sustainable development implications of urbanization. Using satellite data from 2000 to 2019, we examine country-level population-adjusted biases in infrastructure distribution within and between regions of varying urbanization levels and derive four key findings. First, we find long-run positive associations between infrastructure inequalities and both urbanization and economic development. Second, our estimates highlight increasing infrastructure inequalities across most of the countries examined. Third, we find greater future infrastructure inequality increases in the global south, where inequalities will rise more in countries with substantial urban primacy. Fourth, we find that infrastructure inequality may evolve differently than economic inequalities. Overall, advancing sustainable development vis-à-vis urbanization and economic development will require intentional infrastructure planning for spatial equity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Emissions leakage and economic losses may undermine deforestation-linked oil crop import restrictions

Import restrictions on deforestation-linked commodities are being considered strategies to reduce global deforestation and emissions. However, limited market share of importers imposing such restrictions and the potential for emissions leakage could reduce their effectiveness. Moreover, they could result in negative economic implications for producers and consumers. We quantify future emissions and economic implications of oil palm and soybean import restrictions. Current EU restrictions will likely have minimal impact due to the EU’s otherwise small and diminishing share of global palm and soy demand. If extended beyond the EU, such import restrictions could drive reductions in cumulative LUC emissions by 2050 in key oil crop exporting regions— up to 0.9% in Indonesia, 1.5% in the rest of Southeast Asia, 3.8% in Argentina and 6.7% in Brazil, relative to a scenario with no import restrictions. However, these key exporters could also face losses ranging $\$$4.1-$\$$61 billion in cumulative agricultural production revenue by 2050.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Materials Data Science Ontology(MDS-Onto): Unifying Domain Knowledge in Materials and Applied Data Science

Ontologies have gained popularity in the scientific community as a way to standardize terminologies in organizations’ data. Although certain cohorts have created frameworks with rules and guidelines on creating ontologies, there exist significant variations in how Materials Science ontologies are currently developed. We seek to provide guidance in the form of a unified automated framework for developing interoperable and modular ontologies for Materials Data Science that simplifies the ontology terms matching by establishing a semantic bridge up to the Basic Formal Ontology(BFO). This framework provides key recommendations on how ontologies should be positioned within the semantic web, what knowledge representation language is recommended, and where ontologies should be published online to boost their findability and interoperability. Two fundamental components of the MDS-Onto framework are the bilingual package called FAIRmaterials for ontology creation and FAIRLinked, for FAIR data creation. To showcase the practical capabilities of FAIRmaterials, we present two exemplar domain ontologies of MDS-Onto: Synchrotron X-Ray Diffraction and Photovoltaics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Hybrid renewable energy systems

In the pursuit of ecologically sustainable and resilient energy systems, increasingly more attention is being devoted to a diversity of energy generation and storage methods. As the landscape of generation technology gains nuance and complexity, a wide-ranging set of technical questions has emerged, touching on topics that range from control and optimization of hybrid systems to finance and economic viability to multi-fidelity modeling and scientific machine learning. In the context of this special issue, hybrid renewable energy systems are any systems that consider the combined dynamics of more than one form of generation, storage, or grid subsystem. Research endeavors have delved into improving the flexibility of energy systems by utilizing existing resources, introducing novel operational strategies, deploying enhanced renewable forecasts, and exploring emerging technologies. In conclusion, the interconnection among various sectors has garnered heightened attention, not only due to the provision of additional tradable energy products but also for furnishing flexible headroom to system operators.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

The CanBikeCO Full Pilot: Long-Term Results and Analysis From an E-Bike Program in Colorado, USA

Personal micromobility devices like bicycles, e-bikes, and scooters are low- or zero-energy alternatives to single-occupancy vehicles. However, a lack of data has led to a dearth of data-driven research on personally owned e-bike usage. We present longitudinal findings from the CanBikeCO program, focused on e-bike adoption and use across demographics, trip characteristics, and geographies in the state of Colorado. CanBikeCO recorded travel survey data from low-income individuals provided with personal e-bikes by the Colorado Energy Office in six communities across Colorado from July 2021 to December 2022. The data were collected using a custom instance of the National Renewable Energy Laboratory OpenPATH platform, which combines passive data collection with semantic information such as trip mode and purpose labels. To our knowledge, there are no prior travel survey data on personally owned e-bikes with this range and scope. Insights from this unique dataset include: (i) work trips were 17% more likely than average trips to be taken on an e-bike, (ii) e-bikes were most often reported to replace cars (34% of e-bike trips) and other personal micromobility devices (22%), and (iii) participants favored walking for trips less than 1 mile, e-bikes for trips of 1-3 miles, and e-bikes, cars, or shared rides for trips of 3-20 miles. The data used to generate these results have been made available in the Transportation Secure Data Center. We find e-bike use is appealing across age groups and may be related to characteristics of land use, urban form, occupation, income, and car ownership. We conclude for this population that the energy demand added by e-bike use (induced demand and replacing non-motorized modes) is outweighed by the reduction in energy demand from replacement of single-occupancy vehicle trips with e-bike trips. Our findings suggest considerable potential for energy savings from personal e-bike ownership.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Optimal Economic Dispatch and Load-Following Strategies for Nuclear Integrated Energy Systems

The need for distributed and adaptable energy resources that can handle the growing unpredictability in both supply and demand is rising as the power system continues to modernize. In order to satisfy those needs and maintain grid resilience, nuclear power plants can dynamically control their output, despite typically being used as baseload generators. By incorporating energy storage and renewable energy sources, nuclear integrated energy systems are designed to satisfy the electrical and thermal demands of different end-user applications while ensuring flexible power operation. These systems generate revenue by participating in both wholesale and ancillary services electricity markets, as well as commodity markets for various byproducts generated from coupled industrial processes. This study addresses the economic dispatch efficiency of a tightly coupled nuclear integrated energy system comprising a gigawatt-scale light water reactor, commercialized in the U.S., a high-temperature steam electrolysis unit, a district heating network, and specified electrical loads. To demonstrate the nuclear power plant’s flexibility within the day-ahead unit commitment and economic dispatch framework, while maintaining equilibrium even during periods of refueling outages, this paper develops a mixed-integer linear programming framework that models the subsystems and components of its nuclear steam supply system. A systematic comparative analysis of flexible versus baseload nuclear power plant operation under varying levels of renewable energy integration indicates that flexible operation enhances system profitability by more than 18% while also increasing energy storage utilization, improving reactor responsiveness to load fluctuations, and allowing for greater participation across numerous electricity markets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Flexibility Options: A Proposed Product for Managing Imbalance Risk

The presence of variable renewable energy resources with uncertain outputs in day-ahead electricity markets results in additional balancing needs in real-time. Addressing those needs cost-effectively and reliably within a competitive market with unbundled products is challenging as both the demand for and the availability of flexibility depends on day-ahead energy schedules. Existing approaches for reserve procurement usually rely either on oversimplified demand curves that do not consider how system conditions that particular day affect the value of flexibility, or on bilateral trading of hedging instruments that are not co-optimized with day-ahead schedules. This article proposes a new product, ‘Flexibility Options', to address these two limitations. The demand for this product is endogenously determined in the day-ahead market and it is met cost-effectively by considering real-time supply curves for product providers, which are co-optimized with the energy supply. As we illustrate with numerical examples and mathematical analysis, the product addresses the hedging needs of participants with imbalances cost-effectively, provides a less intermittent revenue stream for participants with flexible outputs, promotes value-driven pricing of flexibility, and ensures that the system operator is revenue-neutral. This article provides a comprehensive design that can be further tested and applied in large-scale systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Limitations of Fault-Tolerant Quantum Linear System Solvers for Quantum Power Flow

Quantum computers hold promise for solving problems intractable for classical computers, especially those with high time or space complexity. Practical quantum advantage can be said to exist for such problems when the end-to-end time for solving such a problem using a classical algorithm exceeds that required by a quantum algorithm. Reducing the power flow (PF) problem into a linear system of equations allows for the formulation of quantum PF (QPF) algorithms, which are based on solving methods for quantum linear systems such as the Harrow-Hassidim-Lloyd (HHL) algorithm. Speedup from using QPF algorithms is often claimed to be exponential when compared to classical PF solved by state-of-the-art algorithms. Here, we investigate the potential for practical quantum advantage in solving QPF compared to classical methods on gate-based quantum computers. Notably, this paper does not present a new QPF solving algorithm but scrutinizes the end-to-end complexity of the QPF approach, providing a nuanced evaluation of the purported quantum speedup in this problem. Our analysis establishes a best-case bound for the HHL-based quantum power flow complexity, conclusively demonstrating that the HHL-based method has higher runtime complexity compared to the classical algorithm for solving the direct current power flow (DCPF) and fast decoupled load flow (FDLF) problem. Notably, our analysis and conclusions can be extended to any quantum linear system solver with rigorous performance guarantees, based on the known complexity lower bounds for this problem. Additionally, we establish that for potential practical quantum advantage (PQA) to exist it is necessary to consider DCPF-type problems with a very narrow range of condition number values and readout requirements.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

GreenThrift: Optimizing Carbon and Cost for Flexible Residential Loads

Reducing buildings’ carbon emissions is an important sustainability challenge. While scheduling flexible building loads has been previously used for a variety of grid and energy optimizations, carbon footprint reduction using such flexible loads poses new challenges since such methods need to balance both energy and carbon costs while also reducing user inconvenience from delaying such loads. This paper highlights the potential conflict between electricity prices and carbon emissions and the resulting trade-offs in carbon-aware and cost-aware load scheduling. To address this trade-off, we propose GreenThrift, a home automation system that leverages the scheduling capabilities of smart appliances and knowledge of future carbon intensity and cost to reduce both the carbon emissions and costs of flexible energy loads. At the heart of GreenThrift is an optimization technique that automatically computes schedules based on user configurations and preferences. We evaluate the effectiveness of GreenThrift using real-world carbon intensity data, electricity prices, and load traces from multiple locations and across different scenarios and objectives. Our results show that GreenThrift can replicate the offline optimal and retains 97% of the savings when optimizing the carbon emissions. Moreover, we show how GreenThrift can balance the conflict between carbon and cost and retain 95.3% and 85.5% of the potential carbon and cost savings, respectively.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Optimization of a Mixed Fleet of Aerial Drones for Medical Supplies: A Case Study of Blood Delivery Logistics

Aerial drones have emerged as an innovative solution for faster transportation of time-sensitive items (e.g., emergency medical supplies), potentially reducing the transmission of contagious diseases and enhancing healthcare availability through contactless autonomous delivery. We study fleet sizing and efficient scheduling of a mixed fleet of drones for delivering time-sensitive medical items having distinct release and due times to minimize the required fleet size and fleet composition, the required number of additional batteries, and the total energy consumption. We continuously track the remaining battery energy of drones to determine the optimal timing for battery replacement, rather than replacing the battery at each node. Using actual drone flight test data, we employed a machine learning (ML) method to estimate the energy consumption of different drone types during flight segments for different operating parameters. We present a novel mixed-integer programming model to efficiently formulate the problem that integrates the estimated energy consumption functions from ML. We propose a new greedy heuristic (GH) algorithm and a customized genetic algorithm (GA) for solving large-scale instances of this problem faster. Results demonstrate that the GH algorithm is substantially faster than the accelerated CPLEX and the GA, while sacrificing the solution quality by a small amount. Results based on an actual blood sample delivery case study from Pendleton, Oregon, United States, show that using a mixed fleet of drones reduces the total cost and total energy consumption up to 18.18% and 28.7%, respectively, compared to using a homogeneous fleet.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗
DOE OSTI2026

An On-Demand Electric Transit Case Study of New Rochelle, New York

Here, this article characterizes the performance and ridership patterns of an on-demand transit (ODT) service utilizing lightweight electric vehicles (EVs) in New Rochelle, New York. Ridership sociodemographics, travel patterns (both temporal and spatiotemporal), and energy use from the service were explored using travel and survey data from September 2019 through December 2023. The ODT service was found to be used more by women (nearly 60%) and younger demographics (>65% under the age of 42), with peak use in the middle of the day and a grocery store as a top origin and destination. The service was utilized primarily for short trips (86% under 2 mi), with approximately one-third of riders using the ODT service to connect to a train or bus. The costs associated with fueling/charging were compared for different types of fleet vehicles, and the small, right-sized EVs were found to have annual charging costs that were roughly half of the refueling costs for conventional hybrid vans, and 24 times lower than a fleet of diesel buses. Evaluating the vehicle fleet and mapping current socio-spatial travel demand can inform system performance, guide service area development, and support future planning such as expansion to nearby communities and transit hubs. The findings in this case study suggest that on-demand electric transit may be a significant and growing space for advancing highly valued public mobility services. Public transport interventions that consider right-sized, electric, on-demand vehicles can help improve mobility access and reduce energy use and refueling costs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Resilient U.S. Land Ports of Entry

The continued operation of Land Ports of Entry (LPOE), managed by the Customs and Border Protection (CBP) and General Services Administration% is vital to the U.S. economy and security. Border faculties are included in the Department of Homeland Security (DHS) Government Facilities Sector2, one of the 16 critical infrastructures "whose assets, systems, and networks, whether physical or virtual, are considered so vital to the United States that their incapacitation or destruction would have a debilitating effect on security, national economic security, national public health or safety, or any combination thereof.'" Specifically, disruptions to the flow of border crossing traffic, in the form of closures or increased border crossing wait times, impact the economy and security of all countries involved. This paper describes a process for analyzing and improving the resilience of U.S. Land Ports of Entry. For LPOE, the team believes that energy resilience is the primary objective due to the complete reliance on the e-manifest system and the increasing use of Multi-Energy Portals (MEPs). Emanifests are part of CPB's Automated Commercial Environment (ACE). They document several key pieces of information about cargo vehicles wishing to cross the border into the United States and are submitted before arriving at the port. Vehicles can be flagged for more invasive inspection based on the content of the e-manifest. MEPs are a non-intrusive inspection (NII) technology used to scan the contents of the cargo. Together MEPs and ACE serve an important role in aiding CBP with their mission to protect "the public from dangerous people and materials", and "enabling legitimate trade and travel.'" To analyze resilience of a port, the team would need to understand the port's current energy usage, which systems depend on energy and what backup systems exist, and any emergency operation plans that dictate how systems are operated in the event of a power outage. The team would also need to determine the design basis threats (DBTs) for the LPOE which could include natural disasters, manmade events, and accidents. The magnitudes of the DBTs are calculated and are then translated to expected impacts on the infrastructure and systems at the port. With this information gathered, existing LPOE models developed here at Sandia National Laboratories could be extended to support decisions about resilience. Current models are implemented in FlexSim, a 3rd party discrete event simulator. FlexSim provides 3-D visuals of physical layout that can reveal valuable insights, allows input to be variable (e.g. time it takes to interact with the CBP officer at primary inspection can vary) so that a whole range of possibilities can be captured in the results, and can be used to collect user-defined output metrics. Current LPOE models focus on cargo vehicle traffic, and process changes caused by the installation of new drive-through MEPs. Extending them to address resilience questions would require the addition of key pieces of information learned during the resilience analysis including critical systems, failure rates, and process changes for when failures occur. The primary output metric for current models is border crossing wait time. Additional metrics would also be added to the model to gain a more complete understanding of impacts related to resilience, for example, MEP scan rate. Once complete, the model could be used to analyze the effectiveness of mitigation strategies representing some future state.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

2022 Standard Scenarios Report: A U.S. Electricity Sector Outlook

This report documents the eighth edition of the annual Standard Scenarios. It summarizes 70 forward-looking scenarios of the U.S. electricity sector that have been designed to capture a wide range of possible futures. In August 2022, the United States Congress passed the Inflation Reduction Act (IRA), a law aimed at accelerating U.S. decarbonization, clean energy manufacturing, and deployment of new power and end-use technologies. This year’s scenarios include representations of the main electricity-sector provisions from IRA and the potential impact on electricity demand. The Standard Scenarios are simulated using the Regional Energy Deployment System (ReEDS) model, which projects utility-scale electricity sector evolution for the contiguous United States using a system-wide, least-cost approach subject to policy and operational constraints. A subset of the scenarios are simulated in the PLEXOS production cost model to obtain a broader suite of metrics at the hourly resolution, which are made available through the National Renewable Energy Laboratory’s (NREL’s) annual Cambium data sets. The scenarios can be viewed and downloaded from NREL’s Scenario Viewer. Annual results are available for the full suite of scenarios in the Standard Scenarios projects in the viewer, whereas the Cambium projects contain hourly data for a subset of scenarios. The Standard Scenarios includes a scenario called the Mid-case, which has central or median values for core inputs such as technology costs and fuel prices, moderately paced demand growth averaging 1.3% per year, and electricity sector policies as they existed in September 2022 (including IRA). The remaining 69 scenarios are created by varying inputs such as technology and fuel prices, resource availability, demand growth, whether nascent generation technologies are allowed, and by introducing national decarbonization constraints.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Industrial Assessment Center

Established in 1990, San Diego State University’s (SDSU) Industrial Assessment Center (IAC) is proud of its years of service. During this period, it has served over 620 small and medium-sized manufacturing plants in Southern California. SDSU/IAC’s efforts to transfer state-of-the-art technologies to industry have increased revenues, cultivated creativity, improved energy efficiencies, and benefited the environment. The Center has contributed to the region's economic growth and stability by assisting small and medium size companies to better compete in the global market. It has helped mitigate climate change by reducing greenhouse gas emissions. IAC activities have fostered productive relationships between the University and local industry, assisted industrial sectors to improve their energy efficiency and enhance their manufacturing productivity, in turn impacting the material and working conditions of their employees. In addition to financial savings and environmental benefits, we have trained tens of students who became energy specialists in various companies. Thus, a substantial benefit of the IAC has been the ongoing training of engineering faculty and students. All IAC graduates were offered jobs before or within weeks of their graduation. The activities of the SDSU/IAC have expanded the institutional expertise of the College and improved the knowledge base of the faculties involved leading to several related publications, master’s theses, and senior student projects. Significant number of peer-reviewed publications of the IAC director at SDSU have greatly benefitted from the experience of the Center. As a result of this extensive exposure to manufacturing processes, the SDSU/IAC has grown to be an integral component of SDSU’s engineering research and training. We have successfully built upon these established achievements and academic excellence. IAC service to industry is particularly vital in Southern California, a region with one of the highest manufacturing concentrations in the country. SDSU/IAC has understood and implemented the overall objectives of DOE’s IAC program and guidelines except for the pandemic years when the country’s manufacturing sector was put in dire stress. In addition to student training and service to industry, IAC’s contribution to state and local governments as well as utility companies to assess energy policies and design rebate and incentive strategies cannot be undermined.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Integration of the NCRC Database and Other INL Databases

The Nuclear Computational Resource Center provides a portal by which industry professionals, educational staff, students, national laboratory employees, and others may request access to certain engineering software tools. As the tools provided through the Nuclear Computational Resource Center portal are not open-source and freely available, a set of approvals are necessary before access is granted. All code recipients must be associated with an institution that has a license with Idaho National Laboratory for the code requested. Information about these licenses is controlled by Idaho National Laboratory’s Technology Deployment organization and housed in a Technology Deployment database. Those requesting code access who are not citizens of the United States must also have a security plan, mandated by Idaho National Laboratory policy. Security plans are managed by the International Access Program and are stored in an International Access Program database known as IFacts. Granting access to software thus depends on information stored in the Technology Deployment database and IFacts. In the past, no connection between the Nuclear Computational Resource Center portal and these databases existed, making checking the status of license agreements and security plans time consuming and error prone. This report demonstrates that the Nuclear Computational Resource Center portal now connects to both the Technology Deployment database and IFacts, greatly improving the ease of use of the Nuclear Computational Resource Center system for administrators, which leads to a better overall experience for those requesting code access.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Analyzing Potential Greenhouse Gas Emissions Reductions from Plug-In Electric Vehicles: Report for CRC Project, "Carbon Return on Investment for Electrified Vehicles"

Investment in battery and electrification technologies has the potential to greatly reduce vehicular greenhouse gas (GHG) emissions, as a battery-electric vehicle (BEV) will have zero tailpipe emissions. However, there will be GHG emissions associated with production of the vehicle including its battery, and with any carbon-emitting electricity sources used to charge the vehicle. This study explores the GHG reduction benefits of different plug-in electric vehicle (PEV) designs in the context of factors such as electricity production mix, per-vehicle battery requirements, and varying battery market growth scenarios. The analyses focus on the U.S. light-duty vehicle (LDV) market, which accounts for nearly 60% of U.S. transportation sector GHG emissions - over twice as much as the next largest contributing transportation sub-sector.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Alaska Hydrogen Opportunities Report

This inaugural report on Alaska's hydrogen energy opportunities introduces key themes for developing a hydrogen economy in Alaska, establishes a baseline understanding of Alaska's infrastructure and resources relevant to hydrogen, and contextualizes this baseline in terms of national and global initiatives focused on hydrogen. This report could be further developed into a hydrogen roadmap or a statewide hydrogen strategy in the future. The driving group behind this report, the Alaska Hydrogen Working Group, was formed in 2022 to address the increasing interest in hydrogen energy opportunities in Alaska. As of December 2023, there were nearly 200 members representing industry, government, academia, communities, tribal entities, and interested citizens from both inside and outside Alaska. Since its inception, the group has met monthly to discuss issues of interest and to share insights and questions. One task is to synthesize Alaska's hydrogen energy opportunities and potential into a report. This task not only reflects grassroots interest but also responds to objectives outlined in Alaska Statewide: Comprehensive Economic Development Strategy 2022-2027 (Alaska Department of Commerce, Community, and Economic Development, 2022), one of which is to develop and implement a hydrogen roadmap for Alaska. The goals of this report are to enhance knowledge and information sharing, spur innovation and investment that could help transform Alaska's energy systems, and identify economic and workforce development opportunities across the state. Following the elements of the hydrogen economy outlined in the U.S. National Clean Hydrogen Strategy and Roadmap, published in June 2023, this report explores the production, storage/delivery, and end-use options in evolving markets for Alaska, both within and outside the state. It also outlines key opportunities to identify and develop infrastructure investments, policy and regulatory frameworks, future research and demonstration priorities, economic and investment considerations, and workforce programs. These goals and opportunities are intended to support a statewide hydrogen energy economy that is equitable, diverse, environmentally just, and supportive of Indigenous rights and value systems.

08 HYDROGEN↗
DOE OSTI2024

Advances on CHP District Energy and Microgrids Deployment: Simplified Tool for Rapidly Deploying Feasibility Analytics for the Non-Technical User (Final Technical Report)

Community energy systems have proven to have the potential to improve cost efficiency, resilience, and decarbonize. However, investing in community energy systems such as community microgrids or district energy systems is a complex decision due to the high initial investment and the uncertainties associated with the long development time and lifecycle of the project. Tools that make feasibility assessments accessible to non-technical users like investors, policymakers, and other stakeholders will result in more feasibility analyses completed, more candidate projects identified, and more community energy systems deployed. The pilot tool developed under this award is named Energy Fellow. Energy Fellow allows technical and non-technical users to complete feasibility analyses for district energy systems and community microgrids. This is the first software tool of its kind designed for non-technical users and available at no cost. Its scope was adjusted to a 25x25-mile region within the Houston area in Texas to make its development compatible with the funding available. However, the findings and models developed make this pilot tool easily scalable to the US. The lessons learned during the design, implementation, and testing stages have helped find trade-off solutions to software and hardware challenges related to implementing 3D models in online tools. Green software strategies has been successfully applied to the design and operations of the tool, and the team has researched the aspects of the (non-technical) user experience that will make commercial developments of this tool even more impactful.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗