SAI: Integration of Electric Vehicles and the Electric Grid

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的重点是人类推理和决策，治理，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。该项目探讨了人们如何从改善电动汽车（EV）和电网之间的能源和信息流中受益。许多美国人正在经历频繁的停电和不断上涨的能源成本。电动汽车提供了一个有前途的解决方案，因为它们可以在停电期间作为备用电源，在更便宜的时间充电，支持电网，并促进可再生能源的整合。然而，为了充分利用电动汽车的优势，鼓励优先考虑电网稳定性和经济激励的电动汽车充电实践至关重要。SAI的研究项目结合了经济、行为和技术概念，开发了一个车辆-电网集成（VGI）系统，该系统最大限度地发挥了电动汽车在解决停电问题、降低能源成本和创建强大且可持续的能源系统方面的优势。该项目探讨了VGI的潜在好处，与其实施相关的成本和挑战，以及如何最好地在人们之间分享利益。此外，该项目还研究了人们最喜欢如何参与并获得补偿，以使用他们的建筑物和电动汽车作为资源，使电网更具弹性。在与政策制定者，行业和非营利组织现有合作的基础上，SAI项目分为四个研究方向。重点1侧重于寻找定价机制和体制安排，以促进方便用户的虚拟地理信息系统服务。Thrust 2进行潮流研究，以确保电网能够处理VGI，并设计一个系统来优化EV充电和放电时间表。重点3研究了受益于VGI的社会经济差异，并探讨了消费者参与双向电动汽车充电的意愿。Thrust 4开发了一个机器学习模型和一个合成数据集，其中包括消费者如何采用和使用VGI服务的数据，以及这些采用和使用模式的影响。通过结合来自实验室实验、调查、访谈和VGI基础设施的实际实施的数据，该项目提供了一个模型，用于预测VGI系统在全国范围内广泛采用的影响和模式。经济（SBE）该奖项反映了NSF的法定使命，并被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准。

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.This project explores how people can benefit from improving the flow of energy and information between electric vehicles (EVs) and the electric grid. Many Americans are experiencing frequent power outages and rising energy costs. EVs offer a promising solution as they can serve as backup power sources during outages, charge at cheaper times, support the grid, and promote the integration of renewable energy. However, to fully harness the advantages of EVs, encouraging EV charging practices that prioritize grid stability and economic incentives is vital. This SAI research project combines economic, behavioral, and technical concepts to develop a Vehicle-Grid Integration (VGI) system that maximizes the advantages of EVs in addressing power outages, reducing energy costs, and creating a strong and sustainable energy system. This project explores the potential benefits of VGI, the costs and challenges associated with its implementation, and how best to share the benefits among people. Additionally, this project examines how people most prefer to participate and be compensated for using their buildings and EVs as resources to make the electric grid more resilient.Building on existing collaborations with policymakers, industry, and nonprofits, this SAI project is organized into four research thrusts. Thrust 1 focuses on finding pricing mechanisms and institutional arrangements that promote user-friendly VGI services. Thrust 2 performs power flow studies to ensure the power grid can handle VGI and designs a system for optimizing EV charging and discharging schedules. Thrust 3 examines socio-economic disparities in benefiting from VGI and explores consumer willingness to participate in bidirectional EV charging. Thrust 4 develops a machine learning model and a synthetic dataset that includes data on how consumers adopt and use VGI services, as well as the impact of these adoption and usage patterns. By combining data from laboratory experiments, surveys, interviews, and real-world implementations of VGI infrastructure, this project offers a model for predicting the effects and patterns of widespread adoption of VGI systems across the country.This award is supported by the Directorate for Social, Behavioral, and Economic (SBE) Sciences.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.