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DOE OSTI2013

Designing a graph-based approach to landscape ecological assessment of linear infrastructures

The development of major linear infrastructures contributes to landscape fragmentation and impacts natural habitats and biodiversity in various ways. To anticipate and minimize such impacts, landscape planning needs to be capable of effective strategic environmental assessment (SEA) and of supporting environmental impact assessment (EIA) decisions. To this end, species distribution models (SDMs) are an effective way of making predictive maps of the presence of a given species. In this paper, we propose to combine SDMs and graph-based representation of landscape networks to integrate the potential long-distance effect of infrastructures on species distribution. A diachronic approach, comparing distribution before and after the linear infrastructure is constructed, leads to the design of a species distribution assessment (SDA), taking into account population isolation. The SDA makes it possible (1) to estimate the local variation in probability of presence and (2) to characterize the impact of the infrastructure in terms of global variation in presence and of distance of disturbance. The method is illustrated by assessing the impact of the construction of a high-speed railway line on the distribution of several virtual species in Franche-Comté (France). The study shows the capacity of the SDA to characterize the impact of a linear infrastructure either as a research concern or as a spatial planning challenge. SDAs could be helpful in deciding among several scenarios for linear infrastructure routes or for the location of mitigation measures. -- Highlights: • Graph connectivity metrics were integrated into a species distribution model. • SDM was performed before and after the implementation of linear infrastructure. • The local variation of presence provides spatial indicators of the impact.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Assessment of online public opinions on large infrastructure projects: A case study of the Three Gorges Project in China

Public opinion becomes increasingly salient in the ex post evaluation stage of large infrastructure projects which have significant impacts to the environment and the society. However, traditional survey methods are inefficient in collection and assessment of the public opinion due to its large quantity and diversity. Recently, Social media platforms provide a rich data source for monitoring and assessing the public opinion on controversial infrastructure projects. This paper proposes an assessment framework to transform unstructured online public opinions on large infrastructure projects into sentimental and topical indicators for enhancing practices of ex post evaluation and public participation. The framework uses web crawlers to collect online comments related to a large infrastructure project and employs two natural language processing technologies, including sentiment analysis and topic modeling, with spatio-temporal analysis, to transform these comments into indicators for assessing online public opinion on the project. Based on the framework, we investigate the online public opinion of the Three Gorges Project on China's largest microblogging site, namely, Weibo. Assessment results present spatial-temporal distributions of post intensity and sentiment polarity, reveals major topics with different sentiments and summarizes managerial implications, for ex post evaluation of the world's largest hydropower project. The proposed assessment framework is expected to be widely applied as a methodological strategy to assess public opinion in the ex post evaluation stage of large infrastructure projects. - Highlights: • We developed a framework to assess online public opinion on large infrastructure projects with environmental impacts. • Indicators were built to assess post intensity, sentiment polarity and major topics of the public opinion. • We took the Three Gorges Project (TGP) as an example to demonstrate the effectiveness proposed framework. • We revealed spatial-temporal patterns of post intensity and sentiment polarity on the TGP. • We drew implications for a more in-depth understanding of the public opinion on large infrastructure projects.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Enabling human–infrastructure interfaces for inspection using augmented reality

Decaying infrastructure maintenance cost allocation depends heavily on accurate and safe inspection in the field. New tools to conduct inspections can assist in prioritizing investments in maintenance and repairs. The industrial revolution termed as “Industry 4.0” is based on the intelligence of machines working with humans in a collaborative workspace. Contrarily, infrastructure management has relied on the human for making day-to-day decisions. New emerging technologies can assist during infrastructure inspections, to quantify structural condition with more objective data. However, today’s owners agree in trusting the inspector’s decision in the field over data collected with sensors. If data collected in the field is accessible during the inspections, the inspector decisions can be improved with sensors. New research opportunities in the human–infrastructure interface would allow researchers to improve the human awareness of their surrounding environment during inspections. This article studies the role of Augmented Reality (AR) technology as a tool to increase human awareness of infrastructure in their inspection work. The domains of interest of this research include both infrastructure inspections (emphasis on the collection of data of structures to inform management decisions) and emergency management (focus on the data collection of the environment to inform human actions). This article describes the use of a head-mounted device to access real-time data and information during their field inspection. The authors leverage the use of low-cost smart sensors and QR code scanners integrated with Augmented Reality applications for augmented human interface with the physical environment. This article presents a novel interface architecture for developing Augmented Reality–enabled inspection to assist the inspector’s workflow in conducting infrastructure inspection works with two new applications and summarizes the results from various experiments. The main contributions of this work to computer-aided community are enabling inspectors to visualize data files from database and real-time data access using an Augmented Reality environment.

Maharjan, D.↗

DOE OSTI2017

Synthesis Study on Transitions in Signal Infrastructure and Control Algorithms for Connected and Automated Transportation

Documenting existing state of practice is an initial step in developing future control infrastructure to be co-deployed for heterogeneous mix of connected and automated vehicles with human drivers while leveraging benefits to safety, congestion, and energy. With advances in information technology and extensive deployment of connected and automated vehicle technology anticipated over the coming decades, cities globally are making efforts to plan and prepare for these transitions. CAVs not only offer opportunities to improve transportation systems through enhanced safety and efficient operations of vehicles. There are also significant needs in terms of exploring how best to leverage vehicle-to-vehicle (V2V) technology, vehicle-to-infrastructure (V2I) technology and vehicle-to-everything (V2X) technology. Both Connected Vehicle (CV) and Connected and Automated Vehicle (CAV) paradigms feature bi-directional connectivity and share similar applications in terms of signal control algorithm and infrastructure implementation. The discussion in our synthesis study assumes the CAV/CV context where connectivity exists with or without automated vehicles. Our synthesis study explores the current state of signal control algorithms and infrastructure, reports the completed and newly proposed CV/CAV deployment studies regarding signal control schemes, reviews the deployment costs for CAV/AV signal infrastructure, and concludes with a discussion on the opportunities such as detector free signal control schemes and dynamic performance management for intersections, and challenges such as dependency on market adaptation and the need to build a fault-tolerant signal system deployment in a CAV/CV environment. The study will serve as an initial critical assessment of existing signal control infrastructure (devices, control instruments, and firmware) and control schemes (actuated, adaptive, and coordinated-green wave). Also, the report will help to identify the future needs for the signal infrastructure to act as the nervous system for urban transportation networks, providing not only signaling, but also observability, surveillance, and measurement capacity. The discussion of the opportunities space includes network optimization and control theory perspectives, and the current states of observability for key system parameters (what can be detected, how frequently can it be reported) as well as controllability of dynamic parameters (this includes adjusting not only the signal phase and timing, but also the ability to alter vehicle trajectories through information or direct control). The perspective of observability and controllability of the dynamic systems provides an appropriate lens to discuss future directions as CAV/CV become more prevalent in the future.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2019

University of New Hampshire Center for Ocean Renewable Energy (CORE) Infrastructure Enhancements

Several key components of the University of New Hampshire (UNH) Center for Ocean Renewable Energy (CORE) research, development and evaluation infrastructure for marine renewable energy (MRE) systems were enhanced under this project. These consisted of (1) A Tidal Turbine Deployment Platform (TDP) for marine hydrokinetic (MHK) turbines for use at the two UNH tidal energy test sites in Great Bay Estuary/Piscataqua River, (2) Laboratory Upgrades at Chase Ocean Engineering Laboratory (COEL), including a new towing mechanism for the UNH tow tank, a one-meter scale turbine test bed with instrumentation and a new test section for a high-speed cavitation tunnel, and the (3) Refurbishment of a Wave/Wind Offshore Test Site Environmental Buoy (for use with WEC testing). The UNH-CORE Infrastructure Enhancement Project was very successful. Existing MRE infrastructure was improved and upgraded and new MRE infrastructure was created at UNH. The infrastructure has already been extensively utilized by MHK industry and collaborators from National Laboratories and other universities, and will continue to serve the R&D mission in support of the Marine Renewable Energy and Powering the Blue Economy (PBE) industries. Testing infrastructure for marine hydrokinetic turbines was created which enables very cost-effective testing of intermediate scale turbines in a real tidal flow. A floating Turbine Deployment Platform (TDP) of dimensions 50 ft x 20 ft (15 m x 6 m), which can be used to deploy and test axial-flow or cross-flow MHK turbines with diameters up to approximately 10 ft (3 m), is now available for the marine energy industry. The platform is currently moored via pile-guides in a “floating-dock” configuration next to a bridge pier at Memorial Bridge in Portsmouth, NH, and turbines can be rotated in and out of the water via a turbine pitching mechanism. Using this new test infrastructure, the MHK industry can perform medium-to-long-term testing with inexpensive device deployment and retrieval, and re-deployment to facilitate low-cost incremental testing.

13 HYDRO ENERGY↗

DOE OSTI2021

Electric Vehicle Charging Infrastructure Trends from the Alternative Fueling Station Locator: First Quarter 2021

The U.S. Department of Energy’s (DOE’s) Alternative Fueling Station Locator contains information on public and private non-residential alternative fueling stations in the United States and Canada and currently tracks ethanol (E85), biodiesel, compressed natural gas, electric vehicle (EV) charging, hydrogen, liquefied natural gas, and propane stations. Of these fuels, EV charging continues to experience rapidly changing technology and growing infrastructure. This report provides a snapshot of the state of EV charging infrastructure in the United States in the first calendar quarter of 2021 (Q1). Using data from the Station Locator, this report breaks down the growth of public and private charging infrastructure by charging level, network, and location. Additionally, this report measures the current state of charging infrastructure compared with the target infrastructure volume for 2030. This information is intended to help transportation planners, policymakers, researchers, infrastructure developers, and others understand the rapidly changing landscape for EV charging. This is the fifth report in a series. Previous reports from 2020 can be found in the Alternative Fuels Data Center (AFDC) and National Renewable Energy Laboratory (NREL) publication databases, as well as the AFDC Charging Infrastructure Trends page (https://afdc.energy.gov/fuels/electricity_infrastructure_trends.html).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

Public water supply infrastructure extensification and diversification in surface waters is insufficient to meet future demands in Texas

The data were developed to evaluate the capacity of existing and potential new surface water supply infrastructure to meet projected public water demands across districts in Texas under multiple future socioeconomic and climate scenarios. The database integrates hydrologic, water quality, infrastructure, energy, cost, demographic, and demand-projection information for candidate surface water supply locations. Candidate sites include stream reaches, waterbodies, reservoir surplus locations, and potential new reservoir sites. Water availability is characterized using historical and projected flow conditions, while site suitability is evaluated using five indicators: Water Availability Index (WAI), Water Quality Index (WQI), Energy Requirement Index (ERI), Water Treatment Cost (WTC), and Water Infrastructure Cost (WIC). The datasets include statewide candidate-site information, district-level demand projections under Shared Socioeconomic Pathways (SSPs), runoff-based allocation constraints, climate-stress metrics, and optimization outputs evaluating alternative infrastructure planning strategies. Optimization results compare Business-as-Usual (BAU) and All Surface Water (AllSW) demand-management approaches under both scaled and fixed cost-cap strategies. Associated validation datasets provide district-level feasibility assessments, infrastructure selection outcomes, cost-cap utilization, demand satisfaction metrics, and constraint diagnostics. Additional datasets quantify projected changes in storage and flow conditions as well as water availability stress for both existing and newly selected intake locations under the SSP5 scenario for mid-century and late-century climate conditions. Together, these datasets support assessment of the extent to which surface-water infrastructure expansion and diversification strategies can satisfy future public water demands while accounting for hydrologic, economic, and planning constraints across Texas. Dataset(s) Description Dataset_preoptimization.xlsx Comprehensive pre-optimization dataset containing candidate water-supply sites and associated hydrologic, water-quality, infrastructure, climate, demographic, runoff, and demand-projection variables used as inputs to the optimization analyses. Includes variable descriptions and the full statewide candidate-site database. District_level_site_selection.zip - Compressed archive containing all SSP-specific district-level optimization result files MESIO_ssp1_results.xlsx District-level site selection results for SSP1 (MESIO). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. MESID_ssp2_results.xlsx District-level site selection results for SSP2 (MESID). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. LCMRD_ssp3_results.xlsx District-level site selection results for SSP3 (LCMRD). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. IRDev-Low_ssp4l_results.xlsx District-level site selection results for SSP4-Low (IRDev-Low). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. IRDev-High_ssp4h_results.xlsx District-level site selection results for SSP4-High (IRDev-High). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. RSIM_ssp5_results.xlsx District-level site selection results for SSP5 (RSIM). Includes variable descriptions, BAU and AllSW site-selection results under scaled and fixed cost strategies, and district-level validation diagnostics. tx_hydrological_stress.xlsx Hydrological stress dataset for existing and newly selected intake locations. Includes projected mid-century and late-century changes, gain/loss classifications, planning strategy information, and accompanying variable descriptions. Also includes water-stress metrics derived from historical and projected low-flow conditions.

Okoye, Perpetua I. (ORCID:0000000215545033)↗

DOE OSTI2016

Defense strategies for infrastructures with multiple systems of components

In several critical infrastructures correlations between the constituent systems represent certain vulnerabilities: disruptions to one may propagate to others and possibly to the entire infrastructure. The correlations between the systems are characterized in two ways in this paper: (i) the aggregate failure correlation function specifies the conditional failure probability of the infrastructure given the failure of an individual system, and (ii) the pairwise correlation function between two systems specifies the failure probability of one system given the failure of the other. The survival probabilities of individual systems satisfy firstorder differential conditions that generalize the contest success functions and statistical independence conditions. We formulate a problem of ensuring the resilience of an infrastructure as a game between the provider and attacker; their utility functions are sums of infrastructure survival probability terms and cost terms, both expressed in terms of the numbers of system components attacked and reinforced. We derive Nash Equilibrium conditions and sensitivity functions that highlight the dependence of infrastructure resilience on the cost terms, correlation functions, and individual system survival probabilities. We apply these results to models of distributed cloud computing and energy grid infrastructures.

Rao, Nageswara S↗

DOE OSTI2022

Offshore Oil and Gas Infrastructure Reuse for CCS: Opportunities and Challenges in the U.S. Gulf of Mexico

The United States Gulf of Mexico has historically been a significant oil and gas producing region and continues to produce hydrocarbons today. As such, significant investments have been made to install oil and gas infrastructure such as pipelines, platforms, and wells. As these assets reach the end of their useful life or production associated with the assets is curtailed, the assets become a liability for both the owner/operators and the U.S. and state governments responsible for regulating the assets. There are costs and risks associated with safely decommissioning the assets, and in some cases, the assets may be abandoned (e.g., the owner is no longer a going concern). In parallel, carbon capture and storage (CCS) technology has developed in the United States and interest and incentives for CCS projects have accelerated in recent years, with many public announcements of CCS projects in development in the U.S. Gulf of Mexico region. The region is particularly well-suited to CCS due to the high density of industry on the coastline (i.e., CO 2 sources) and favorable geology in the near-offshore region. CCS also requires the use of many of the same assets required for oil and gas production (pipelines, platforms, wells) and the oil and gas industry has direct experience with CO 2 transport and injection (i.e., EOR). Therefore, the combination of existing infrastructure in close proximity to potential CCS project sites appears to provide a potential “win-win” solution for re-use of existing oil and gas assets. This paper presents a high-level evaluation of oil and gas infrastructure in the Gulf of Mexico with the goals of identifying the scale of the opportunity (e.g., how much existing infrastructure is realistically re-usable), identifying gaps in knowledge/policy/information required to evaluate existing infrastructure for re-use, and proposing key actions that could be pursued to further the assessment of existing infrastructure re-use for CCS.

Infrastructure, reuse, re-purpose, oil and gas, pi↗

DOE OSTI2022

Leveraging SETS resilience capabilities for safe-to-fail infrastructure under climate change

As the rehabilitation of infrastructure is outpaced by changes in the profile, frequency, and intensity of extreme weather events, infrastructure’s service disruptions and failures become increasingly likely. Safe-to-fail approaches for infrastructure planning and design improve the capacity of cities to adapt for uncertain climate futures by identifying social, ecological, and technological systems (SETS) capabilities to prepare for potential failure scenarios. In this work, we argue for transforming infrastructure planning and design to effectively utilize safe-to-fail approaches by navigating the opportunities and trade-offs of SETS resilience capabilities. From a technological vantage point, traditional infrastructure planning approaches account for social and ecological domains as external design conditions rather than embedded system characteristics. Safe-to-fail approaches directly challenge the isolation of the technological domain by necessitating a recognition that SETS domains are interconnected and interdependent in infrastructure systems, as such risks and system capabilities for resilience must be managed cohesively.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Public charging infrastructure for plug-in electric vehicles: What is it worth?

A lack of charging infrastructure is an important barrier to the growth of the plug-in electric vehicle (PEV) market. Public charging infrastructure has tangible and intangible value, such as reducing range anxiety or building confidence in the future of the PEV market. Quantifying the value of public charging infrastructure can inform analysis of investment decisions and can help predict the impact of charging infrastructure on future PEV sales. Estimates of willingness to pay (WTP) based on stated preference surveys are limited by consumers' lack of familiarity with PEVs. As an alternative, we focus on quantifying the tangible value of public PEV chargers in terms of their ability to displace gasoline use for PHEVs and to enable additional electric (e-) vehicle miles for BEVs, thereby mitigating the limitations of shorter range and longer recharging time. Simulation studies provide data that can be used to quantify e-miles enabled by public chargers and the value of additional e-miles can be inferred from econometric estimates of WTP for increased vehicle range. Functions are synthesized that estimate the WTP for public charging infrastructure by plug-in hybrid and battery electric vehicles, conditional on vehicle range, annual vehicle travel, pre-existing charging infrastructure, energy prices, vehicle efficiency, and household income. A case study based on California's public charging network in 2017 indicates that, to the purchaser of a new BEV with a 100-mile range and home recharging, existing public fast chargers are worth about $1500 for intraregional travel, and fast chargers along intercity routes are valued at over $6500.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

CHARGE-MAP: An integrated framework to study the multicriteria EV charging infrastructure expansion problem

The widespread adoption of electric vehicles (EVs) in recent years has necessitated the development of effective charging infrastructures. However, charging infrastructure expansion is a multifaceted problem that requires careful consideration of the existing infrastructure, spatiotemporal distribution of charging demands, power-grid capacity, and budget constraints. Here, to approach this complex problem, we present CHARGE-MAP, a data-driven simulation-optimization framework, focused on ensuring meaningful charging experience for individual EV owners. CHARGE-MAP integrates three modules: an agent-based simulation module that estimates spatiotemporal distribution of charging demands by modeling EV adopter mobility and charging behavior; an optimization module that determines optimal new charging station/charger locations and capacities, while minimizing expected detour distances and wait-times with a limited number of new stations; and a power module that determines how to connect the stations to the power grid while maintaining its stability. Using the state of Virginia (consisting of 95 counties and 38 independent cities) as a case study, our results show that CHARGE-MAP can meet the demand of ~198,600 predicted EVs with 1,305 new public charging stations and 2,164 new chargers. It reduces average detour distances for charging by 66% and wait-times at stations by 72% compared to the existing infrastructure. Furthermore, transformer capacity requirement analysis reveals that only 1.8% of residential transformers require upgrades, while over 80% of commercial charging locations can be supported with modest transformer infrastructure (25 to 50 kVA). This indicates that targeted investments can facilitate cost-effective EV integration. Consequently, CHARGE-MAP provides policymakers and urban planners with crucial data-driven insights for effective EV charging infrastructure expansion. Sign up for PNAS alerts.

charging infrastructure↗

DOE OSTI2012

MFC Communications Infrastructure Study

Unprecedented growth of required telecommunications services and telecommunications applications change the way the INL does business today. High speed connectivity compiled with a high demand for telephony and network services requires a robust communications infrastructure. The current state of the MFC communication infrastructure limits growth opportunities of current and future communication infrastructure services. This limitation is largely due to equipment capacity issues, aging cabling infrastructure (external/internal fiber and copper cable) and inadequate space for telecommunication equipment. While some communication infrastructure improvements have been implemented over time projects, it has been completed without a clear overall plan and technology standard. This document identifies critical deficiencies with the current state of the communication infrastructure in operation at the MFC facilities and provides an analysis to identify needs and deficiencies to be addressed in order to achieve target architectural standards as defined in STD-170. The intent of STD-170 is to provide a robust, flexible, long-term solution to make communications capabilities align with the INL mission and fit the various programmatic growth and expansion needs.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Nuclear Energy Infrastructure Database Fitness and Suitability Review

In 2014, the Deputy Assistant Secretary for Science and Technology Innovation (NE-4) initiated the Nuclear Energy-Infrastructure Management Project by tasking the Nuclear Science User Facilities (NSUF) to create a searchable and interactive database of all pertinent NE supported or related infrastructure. This database will be used for analyses to establish needs, redundancies, efficiencies, distributions, etc. in order to best understand the utility of NE’s infrastructure and inform the content of the infrastructure calls. The NSUF developed the database by utilizing data and policy direction from a wide variety of reports from the Department of Energy, the National Research Council, the International Atomic Energy Agency and various other federal and civilian resources. The NEID contains data on 802 R&D instruments housed in 377 facilities at 84 institutions in the US and abroad. A Database Review Panel (DRP) was formed to review and provide advice on the development, implementation and utilization of the NEID. The panel is comprised of five members with expertise in nuclear energy-associated research. It was intended that they represent the major constituencies associated with nuclear energy research: academia, industry, research reactor, national laboratory, and Department of Energy program management. The Nuclear Energy Infrastructure Database Review Panel concludes that the NSUF has succeeded in creating a capability and infrastructure database that identifies and documents the major nuclear energy research and development capabilities across the DOE complex. The effort to maintain and expand the database will be ongoing. Detailed information on many facilities must be gathered from associated institutions added to complete the database. The data must be validated and kept current to capture facility and instrumentation status as well as to cover new acquisitions and retirements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2015

Idaho National Laboratory’s Analysis of ARRA-Funded Plug-in Electric Vehicle and Charging Infrastructure Projects: Final Report

Battelle Energy Alliance, LLC, managing and operating contractor for the U.S. Department of Energy’s (DOE) Idaho National Laboratory (INL), is the lead laboratory for U.S. Department of Energy’s Advanced Vehicle Testing Activity (AVTA). INL’s conduct of the AVTA resulted in a significant base of knowledge and experience in the area of testing light-duty vehicles that reduced transportation-related petroleum consumption. Due to this experience, INL was tasked by DOE to develop agreements with companies that were the recipients of The American Recovery and Reinvestment Act of 2009 (ARRA) grants, that would allow INL to collect raw data from light-duty vehicles and charging infrastructure. INL developed non-disclosure agreements (NDAs) with several companies and their partners that resulted in INL being able to receive raw data via server-to-server connections from the partner companies. This raw data allowed INL to independently conduct data quality checks, perform analysis, and report publicly to DOE, partners, and stakeholders, how drivers used both new vehicle technologies and the deployed charging infrastructure. The ultimate goal was not the deployment of vehicles and charging infrastructure, cut rather to create real-world laboratories of vehicles, charging infrastructure and drivers that would aid in the design of future electric drive transportation systems. The five projects that INL collected data from and their partners are: • ChargePoint America - Plug-in Electric Vehicle Charging Infrastructure Demonstration • Chrysler Ram PHEV Pickup - Vehicle Demonstration • General Motors Chevrolet Volt - Vehicle Demonstration • The EV Project - Plug-in Electric Vehicle Charging Infrastructure Demonstration • EPRI / Via Motors PHEVs – Vehicle Demonstration The document serves to benchmark the performance science involved the execution, analysis and reporting for the five above projects that provided lessons learned based on driver’s use of the vehicles and recharging decisions made. Data is reported for the use of more than 25,000 vehicles and charging units.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2019

Meeting 2025 Zero Emission Vehicle Goals: An Assessment of Electric Vehicle Charging Infrastructure in Maryland

The National Renewable Energy Laboratory (NREL) has been enlisted to conduct a statewide assessment of the electric vehicle charging infrastructure requirements for Maryland to meet its goal of supporting 300,000 zero emission vehicles by 2025. NREL's Electric Vehicle Infrastructure Projection Tool (EVI-Pro) was used to generate scenarios of statewide charging infrastructure to support consumer plug-in electric vehicle (PEV) adoption based on travel patterns provided by INRIX (a commercial mapping/traffic company) that are used to characterize regional travel in Maryland and to anticipate future demand for PEV charging. Results indicate that significant expansion of Maryland's electric vehicle charging infrastructure will be required to support the state's PEV goal for 2025. Analysis shows that a fleet of 300,000 PEVs will require 17,400 workplace Level 2 plugs, 9,300 public Level 2 plugs, and 1,000 fast charge plugs. These estimates assume that future PEVs will be driven in a manner consistent with present day gasoline vehicles and that most charging will happen at residential locations. A sensitivity study explores edge cases pertaining to several assumptions, highlighting factors that heavily influence the projected infrastructure requirements. Variations in the makeup of the PEV fleet, evolving consumer charging preferences, and availability of residential charging are all shown to influence 2025 infrastructure requirements.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

MRCI Task 4: Evaluating Regional Infrastructure Technical Summary Report

The infrastructure required to enable carbon capture and sequestration (CCS) goes beyond the equipment and materials needed to capture, transport, and store carbon dioxide (CO2) but includes people and policy that make CCS feasible. The Infrastructure Assessment task of the Midwest Regional Carbon Initiative (MRCI) seeks to determine the infrastructure requirements for the MRCI study area through four activities: • Infrastructure Readiness: Strategizing the buildout of capture, transport, and storage infrastructure in the Midwest, Northeast, and Mid-Atlantic Offshore. • Site Readiness: Determining the CCS readiness of each state in the MRCI region in the categories of subsurface readiness; infrastructure readiness; regulations, permitting, and incentives; and social dynamics. • Jobs, Economics, and Social Characteristics: Quantifying the economic potential, job opportunities, and training opportunities for CCS as well as the social characteristics of the region with a focus on energy and environmental justice (EJ) issues. • Policy and Regulations: Providing an updated accounting of the CCS-relevant policy and regulations in the MRCI region.

CCUS,Carbon storage,Midwest,Midwest Regional Carbo↗

DOE OSTI2014

Perspective: The Climate-Population-Infrastructure Modeling and Simulation Fertile Area for New Research

Managing the risks posed by climate change and extreme weather to energy production and delivery is a challenge to communities worldwide. As climate conditions change, populations will shift, and demand will re-locate; and networked infrastructures will evolve to accommodate new load centers, and, hopefully, minimize vulnerability to natural disaster. Climate effects such as sea level rise, increased frequency and intensity of natural disasters, force populations to move locations. Displaced population creates new demand for built infrastructure that in turn generates new economic activity that attracts new workers and associated households to the new locations. Infrastructures and their interdependencies will change in reaction to climate drivers as the networks expand into new population areas and as portions of the networks are abandoned as people leave. Thus, infrastructures will evolve to accommodate new load centers while some parts of the network are underused, and these changes will create emerging vulnerabilities. Forecasting the location of these vulnerabilities by combining climate predictions and agent based population movement models shows promise for defining these future population distributions and changes in coastal infrastructure configurations. By combining climate and weather data, engineering algorithms and social theory it has been only recently possible to examine electricity demand response to increased climactic temperatures, population relocation in response to extreme cyclonic events, consequent net population changes and new regional patterns in electricity demand. These emerging results suggest a research agenda of coupling these disparate modelling approaches to understand the implications of climate change for protecting the nation s critical infrastructure.

Climate↗