SAI-R: Strengthening American Electricity Infrastructure for an Electric Vehicle Future: An Energy Justice Approach
SAI-R: Strengthening American Electricity Infrastructure for an Electric Vehicle Future: An Energy Justice Approach
批准号:
2228603
负责人:
Jie Xu
金额:
$75.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-09-15 至 2025-08-31
中文摘要
加强美国基础设施(SAI)是NSF的一项计划,旨在促进以人为本的基础和潜在的变革性研究,以加强美国的基础设施。有效的基础设施为社会经济活力和广泛改善生活质量奠定了坚实的基础。强大、可靠和有效的基础设施刺激私营部门创新,促进经济增长,创造就业机会,提高公共部门服务提供的效率,加强社区建设,促进机会平等,保护自然环境,增强国家安全,并推动美国的领导地位。为了实现这些目标,需要来自科学和工程学科的专业知识。SAI专注于人类推理和决策,治理以及社会和文化过程的知识如何使建设和维护有效的基础设施,改善生活和社会,并建立在技术和工程的进步之上。广泛采用电动汽车(EV)被视为遏制碳排放,减少空气污染和改善公共健康的关键战略之一。然而,电动汽车也会产生高需求,并对当前和未来的电力基础设施施加额外的压力。过去对电动汽车的研究没有充分关注电动汽车的部署和所需的基础设施升级如何导致能源不公平并扩大现有的公平差距。SAI研究项目开发了一种能源正义方法,以评估和减少电动汽车部署对非用户的负面影响。它侧重于基础设施升级和电力消耗的成本。制定公平干预措施,并提出政策指导建议,以便在电气化过渡期间为社会各阶层带来惠益。一个多学科的项目团队使用创新的数据分析和先进的计算建模方法来衡量各种形式的能源正义。 与利益攸关方的合作有助于促进政策的设计和执行。 通过加强美国的电力基础设施,国家更有能力走向可持续和公正的电动汽车未来。该项目整合了社会和技术工程方法,以全面评估和减轻电动汽车转型带来的潜在不公正。在社会层面,该项目开发了一个能源正义框架,映射到电动汽车的未来。 它还制定了衡量标准,以指导对转型所产生的潜在不公正进行定性和定量评估。该框架旨在保护非电动汽车用户,特别是那些低收入和中等收入社区的用户,否则他们可能会承担电力基础设施升级和电力消费激增的不成比例的成本。在技术工程方面,创建了新的社会经济和时空方法来分析多模态数据集,并提供电动汽车电力需求和发电增长的准确预测。开发了新的计算优化和分析工具,以应用基于代理的模型来研究未来的电网,电动汽车和利益相关者的互动。制定政策指南,提供社会和技术上可行的解决方案,以减少电动汽车转型中的不公正现象,从而促进公平的电动汽车未来包容所有人。该奖项由社会,行为,经济(SBE)该奖项反映了NSF的法定使命,并通过使用基金会的智力价值进行评估,被认为值得支持和更广泛的影响审查标准。
英文摘要
Strengthening American Infrastructure (SAI) is an NSF Program seeking to stimulate human-centered fundamental and potentially transformative research that strengthens America’s infrastructure. Effective infrastructure provides a strong foundation for socioeconomic vitality and broad quality of life improvement. Strong, reliable, and effective infrastructure spurs private-sector innovation, grows the economy, creates jobs, makes public-sector service provision more efficient, strengthens communities, promotes equal opportunity, protects the natural environment, enhances national security, and fuels American leadership. To achieve these goals requires expertise from across the science and engineering disciplines. SAI focuses on how knowledge of human reasoning and decision-making, governance, and social and cultural processes enables the building and maintenance of effective infrastructure that improves lives and society and builds on advances in technology and engineering.Widespread adoption of electric vehicles (EVs) is seen as one key strategy to curb carbon emissions, reduce air pollution, and improve public health. However, EVs also generate high demand and exert additional pressure on current and future electricity infrastructure. Past research on EVs has not sufficiently attended to how EV deployment and the needed infrastructure upgrades may contribute to energy injustice and widen existing equity gaps. This SAI research project develops an energy justice approach to assessing and reducing the negative effects of EV deployment on non-users. It focuses on the costs of infrastructure upgrades and electricity consumption. Equity interventions are developed and policy guidance is suggested in ways that produce benefits for all segments of society during the electrification transition. A multidisciplinary project team uses innovative data analytics and advanced computational modeling methods to measure various forms of energy justice. Collaboration with stakeholders helps to facilitate policy design and implementation. By strengthening American electric infrastructure, the nation is better positioned to move toward a sustainable and just EV future.This project integrates social and techno-engineering approaches to holistically assess and mitigate potential injustice introduced by the EV transition. On the social dimension, the project develops an energy justice framework mapped to an EV future. It also formulates metrics to guide qualitative and quantitative assessments of potential injustices stemming from the transition. The framework specifically aims to protect non-EV users, particularly those in low- and moderate-income communities that may otherwise bear disproportionate costs for electric infrastructure upgrades and electricity consumption surges. On the techno-engineering dimension, new socioeconomic and spatiotemporal methods are created to analyze multimodal datasets and to provide accurate predictions of EV electricity demand and electricity generation growth. New computational optimization and analytics tools are developed to apply agent-based models to study the future electric grid, EV, and stakeholder interactions at fine resolutions. A policy guide is developed to provide socially and technically feasible solutions to reduce injustice in the EV transition, thereby facilitating a just EV future inclusive of all.This award is supported by the Directorate for Social, Behavioral, and Economic (SBE) Sciences and the Directorate for Engineering.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Collaborative Research: CCSS: Hierarchical Federated Learning over Highly-Dense and Overlapping NextG Wireless Deployments: Orchestrating Resources for Performance
-
批准号:2319780
-
项目类别:Standard Grant
-
资助金额:$22.5万
-
财政年份:2023
-
负责人:Jie Xu
-
依托单位:
Elucidating Mechanisms of Metal Sulfide-Enabled Growth of Anoxygenic Photosynthetic Bacteria Using Transcriptomic, Aqueous/Surface Chemical, and Electron Microscopic Tools
-
批准号:2311021
-
项目类别:Standard Grant
-
资助金额:$59.07万
-
财政年份:2023
-
负责人:Jie Xu
-
依托单位:
CAREER: Wireless InferNets: Enabling Collaborative Machine Learning Inference on the Network Path
-
批准号:2044991
-
项目类别:Continuing Grant
-
资助金额:$50.0万
-
财政年份:2021
-
负责人:Jie Xu
-
依托单位:
Collaborative Research: SWIFT: SMALL: Understanding and Combating Adversarial Spectrum Learning towards Spectrum-Efficient Wireless Networking
-
批准号:2029858
-
项目类别:Standard Grant
-
资助金额:$18.2万
-
财政年份:2020
-
负责人:Jie Xu
-
依托单位:
CCSS: Collaborative Research: Towards a Resource Rationing Framework for Wireless Federated Learning
-
批准号:2033681
-
项目类别:Standard Grant
-
资助金额:$20.0万
-
财政年份:2020
-
负责人:Jie Xu
-
依托单位:
Collaborative Research: CNS Core: Small: Towards Automated and QoE-driven Machine Learning Model Selection for Edge Inference
-
批准号:2006630
-
项目类别:Standard Grant
-
资助金额:$25.0万
-
财政年份:2020
-
负责人:Jie Xu
-
依托单位:
Collaborative Research: Improving Power Grids Weather Resilience through Model-free Dimension Reduction and Stochastic Search for Optimal Hardening
-
批准号:1923145
-
项目类别:Standard Grant
-
资助金额:$7.25万
-
财政年份:2019
-
负责人:Jie Xu
-
依托单位:
Collaborative Research: Towards High-Throughput Label-Free Circulating Tumor Cell Separation using 3D Deterministic Dielectrophoresis (D-Cubed)
-
批准号:1917295
-
项目类别:Standard Grant
-
资助金额:$27.77万
-
财政年份:2019
-
负责人:Jie Xu
-
依托单位:
Collaborative Research: NSF/ENG/ECCS-BSF: Complex liquid droplet structures as new optical and optomechanical materials
-
批准号:1711798
-
项目类别:Standard Grant
-
资助金额:$14.81万
-
财政年份:2017
-
负责人:Jie Xu
-
依托单位:
EAGER-Dynamic Data: A New Scalable Paradigm for Optimal Resource Allocation in Dynamic Data Systems via Multi-Scale and Multi-Fidelity Simulation and Optimization
-
批准号:1462409
-
项目类别:Standard Grant
-
资助金额:$24.94万
-
财政年份:2015
-
负责人:Jie Xu
-
依托单位:
WRG Phase III: The White Rose Grid e-Science Centre
-
批准号:EP/F057644/1
-
项目类别:Research Grant
-
资助金额:$81.99万
-
财政年份:2008
-
负责人:Jie Xu
-
依托单位:
The White Rose Grid e-Science Centre
-
批准号:EP/D055334/1
-
项目类别:Research Grant
-
资助金额:$34.67万
-
财政年份:2006
-
负责人:Jie Xu
-
依托单位:
CoLab: e-Science Collaboration between Leeds and Beihang in China For Grid-Enabled Visualisation Applications
-
批准号:EP/D077249/1
-
项目类别:Research Grant
-
资助金额:$9.79万
-
财政年份:2006
-
负责人:Jie Xu
-
依托单位:
海外基金