SAI-R: Strengthening American Electricity Infrastructure for an Electric Vehicle Future: An Energy Justice Approach

加强美国基础设施(SAI)是一项NSF计划，旨在刺激以人类为中心的基础性研究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的生活质量改善提供了坚实的基础。强大、可靠和有效的基础设施刺激私营部门创新，增长经济，创造就业机会，提高公共部门服务提供效率，加强社区力量，促进机会均等，保护自然环境，增强国家安全，推动美国的领导地位。要实现这些目标，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能够建立和维护有效的基础设施，以改善生活和社会，并建立在技术和工程进步的基础上。电动汽车(EVS)的广泛采用被视为遏制碳排放、减少空气污染和改善公众健康的关键战略。然而，电动汽车也产生了高需求，并对当前和未来的电力基础设施施加了额外的压力。过去对电动汽车的研究没有充分注意到电动汽车的部署和必要的基础设施升级可能会导致能源不公平并扩大现有的股权差距。该SAI研究项目开发了一种能源公平方法，以评估和减少电动汽车部署对非用户的负面影响。它关注的是基础设施升级和电力消耗的成本。在电气化过渡期间，制定了公平干预措施，并提出了政策指导，使社会各阶层都能从中受益。多学科项目团队使用创新的数据分析和高级计算建模方法来衡量各种形式的能源公平。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，美国更好地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，以全面评估和缓解电动汽车转型带来的潜在不公正。在社会层面，该项目制定了一个面向电动汽车未来的能源公平框架。它还制定了衡量标准，以指导对过渡所产生的潜在不公正的定性和定量评估。该框架特别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不成比例的电力基础设施升级和用电量激增的成本。在技术工程方面，创造了新的社会经济和时空方法来分析多模式数据集，并提供对电动汽车电力需求和发电量增长的准确预测。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电网、电动汽车和利益相关者在精细分辨率下的相互作用。政策指南旨在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，从而促进公平的电动汽车未来，包括所有人。该奖项得到了社会、行为和经济局(SBE)和工程局的支持。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和更广泛的影响审查标准进行评估，被认为值得支持。

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.