Collaborative Research: RII Track-2 FEC: STORM: Data-Driven Approaches for Secure Electric Grids in Communities Disproportionately Impacted by Climate Change

RII Track-2 FEC：Storm：受气候变化影响不成比例的社区安全电网的数据驱动方法涉及缅因州、阿拉斯加、南达科他州和波多黎各的司法管辖区。拟议的研究、教育和劳动力发展活动将推动国家的智能电网技术，以支持受气候变化和相关恶劣天气(如飓风、暴风雪、洪水和气温快速变化)影响不成比例的社区。Storm将受益于电气、计算机和土木工程、经济学、社区和环境恢复能力、气候学以及数学和统计方面的专家。教师和学生将使用对解决复杂问题至关重要的融合方法，与社区利益相关者共同创造知识。研究和劳动力发展目标围绕三个交叉主题建立：(1)服务不足的社区参与当地气候变化解决方案和微电网设计的知识转化；(2)通过加速大数据建模、估计和安全控制框架，提高服务不足社区的电网复原力；以及(3)开发区域相关的网络物理研究基础设施，以研究社区参与的电网数据驱动的运行。每个主题都将涉及早期职业生涯和资深教职员工，以确保有效的指导。研究和劳动力发展活动旨在开发试点计划和研究数据，从而从联邦机构和行业获得可持续的资金。项目合作伙伴包括学区、土著部落、市政当局、电力公用事业/合作社、非营利组织、初创公司和老牌公司以及联邦实验室。Storm将通过与社区成员、本科生和研究生、早期职业教师、联邦实验室和行业合作，鼓励多样化和包容性的参与。将特别通过两个机构加强扩大对科技教育管理的参与的努力。阿拉斯加大学费尔班克斯分校(UAF)是阿拉斯加原住民、夏威夷原住民和美国原住民服务的非部落机构。波多黎各大学马亚圭兹是一所西班牙裔服务机构。根据美国工程教育学会的数据，它是美国最大的拉美裔工程师生产商之一。电网是最复杂的人造系统之一，对美国的安全和生活质量至关重要。更频繁和更强烈的极端天气事件以及其他人为威胁，包括物理和网络攻击，正在考验我们国家关键基础设施的韧性。风暴围绕着三个相互关联的主题来应对这一挑战。主题1侧重于让未得到充分服务的社区参与当地气候变化解决方案和微电网设计的知识转化。在以下方面，主题1的方法是新颖的：在社区成员之间共同产生研究和知识；在地理和文化上不同的区域；与具有社会科学和工程背景的研究人员组成的跨学科团队共同设计解决方案，他们的经验跨越研究区域；以及将从三个研究区域中的每一个区域学到的经验应用于其他区域。主题1侧重于微电网规划，以满足受气候变化影响过大的社区的复原力目标，主题2力求提高对服务不足社区的情况认识，并根据极端天气事件期间和之后的社区复原力目标减轻对电网的影响。主题2‘S新的多微电网系统恢复策略将基于新的多时间尺度预测控制和估计框架，在社区和个人层面确定关键负荷的优先顺序，该框架利用GFM逆变器在恢复过程中提供最佳的动态支持。新的硬件木马预防、检测和缓解技术将提高整个系统在恶劣天气下的网络攻击弹性。主题3旨在发展与区域相关的网络物理研究基础设施，以研究社区参与、数据驱动的电网运行。新的、具有区域相关性的合成电力系统、气候和社会经济数据将对推动数据科学、机器学习和人工智能应用于这些服务不足的司法管辖区的电力行业具有极大的价值。Storm将受益于强大的现有合作伙伴关系，包括能源部成功的EPSCoR项目，该项目旨在对以变流器为主的电力系统进行建模。STORM还建立了高级人员与桑迪亚国家实验室、国家可再生能源实验室和太平洋西北国家实验室的合作伙伴关系。此外，该项目还将利用与主要行业/社区合作伙伴(卡尔特姆、Kotzebue电气协会、East River Electric Co-op、密苏里河能源服务、全国农村电力合作协会、西门子、苏谷能源、Galena可持续能源和Versant Power)的关系。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

RII Track-2 FEC: STORM: Data-Driven Approaches for Secure Electric Grids in Communities Disproportionately Impacted by Climate Change involves the jurisdictions of Maine, Alaska, South Dakota and Puerto Rico. The proposed research, education, and workforce development activities will advance the nation’s smart grid technologies to support communities disproportionately impacted by climate change and related severe weather such as hurricanes, blizzards, flooding, and rapid shifts in temperature. STORM will benefit from experts in electrical, computer and civil engineering, economics, community and environmental resilience, climatology, and mathematics and statistics. Faculty and students will co-produce knowledge with community stakeholders, using convergent approaches that are critical to solving complex problems. Research and workforce development objectives are built around three intersecting themes: (1) Engagement of underserved communities in local climate change solutions and knowledge translation for microgrid design; (2) Improvement of power grid resilience in underserved communities through accelerated big data modeling, estimation, and secure control frameworks, and (3) Development of regionally relevant cyber-physical research infrastructure for studying community engaged data-driven operation of power grids. Each theme will involve early career and senior faculty to ensure effective mentoring. Research and workforce development activities are designed to develop pilot programs and research data that will lead to sustainable funding from federal agencies and industry. Project partners include school districts, indigenous tribes, municipalities, electrical utilities/cooperatives, nonprofits, start-up and established companies, and federal laboratories. STORM will encourage diverse and inclusive participation through its work with community members, undergraduate and graduate students, early career faculty, federal laboratories and industry. Efforts to broaden participation in STEM will be enhanced through two institutions in particular. The University of Alaska, Fairbanks (UAF) is an Alaska Native and Native Hawaiian and Native American-Serving Nontribal Institution. The University of Puerto Rico Mayaguez an Hispanic Serving Institution. It is one of the top producers of Hispanic engineers in the United States of America according to the American Society of Engineering Education. The electric grid, among the most complex human-made systems, is vital to U.S. security and quality of life. More frequent and intense extreme weather events as well as other anthropogenic threats, including physical and cyber-attacks, are testing the resilience of our nation’s critical infrastructure. STORM is built around three interrelated themes in response to this challenge. Theme 1 focuses on engaging underserved communities in local climate change solutions and knowledge translation for microgrid design. Theme 1 approaches are novel in terms of the co-production of research and knowledge among community members geographic and culturally distinct regions; the co-design of solutions with an interdisciplinary team of researchers with social science and engineering backgrounds whose experiences span the study regions, and applications of lessons learned from each of the three study regions, to the others. While Theme 1 focuses on microgrid planning to meet the resiliency goals of communities disproportionately impacted by climate change, Theme 2 seeks to increase the situational awareness of underserved communities and mitigate the impact in the electric grid according to the community resilience goals during and after an extreme weather event. Theme 2’s new multi-microgrid system restoration strategy will prioritize critical loads at the community and individual levels based on a new multi-timescale predictive control and estimation framework that utilizes GFM inverters to provide optimal dynamic support during the process. Novel hardware Trojan prevention, detection, and mitigation techniques will advance cyber-attack resilience of the entire system during severe weather. Theme 3 seeks to develop regionally-relevant cyber-physical research infrastructure for studying community-engaged, data-driven operation of power grids. The new, regionally relevant synthetic power systems, climate, and socioeconomic data will be immensely valuable to the advancement of data science, machine learning, and artificial intelligence applied to the electric industry in these underserved jurisdictions. STORM will benefit from strong existing partnerships including a successful Department of Energy EPSCoR project on modeling converter dominated power systems. STORM also builds upon senior personnel’s partnerships with Sandia National Laboratory, National Renewable Energy Laboratory, and Pacific Northwest National Laboratory. In addition, the project will leverage relationships with key industry/community partners (Kartorium, Kotzebue Electric Association, East River Electric Co-op, Missouri River Energy Services, National Rural Electric Cooperative Association, Siemens, Sioux Valley Energy, Sustainable Energy for Galena, and Versant Power).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.