Collaborative Research: Proactive Recovery of Electric Power Assets for Resiliency Enhancement (PREPARE)

该项目旨在开发一个全面的框架和支持理论，以提高关键电网基础设施应对飓风的弹性，并相应地加快恢复过程，以最大限度地减少相关的经济，社会和物理破坏。这项研究对地方和国家能源安全，可靠性和可持续性产生了深远的影响，促进了与极端天气事件和自然灾害相关的先进技术的健康发展，这些事件和自然灾害被确定为美国最大停电的第二大原因。该项目的成果将通过帮助电网运营商更好地管理可用资源，减少飓风和其他自然灾害的后果，从而节省数十亿美元的电网停电和恢复相关成本，从而直接影响社会。这项研究将提高公众意识，促进对飓风复杂性的理解，以及利益相关者、纳税人、监管机构、公用事业高管和市场参与者之间所需的恢复计划。此外，这项研究将使智能电网新技术的快速和广泛部署成为可能，这将在这一领域创造大量的就业机会。在更广泛的范围内，该项目将促进未来劳动力的教学和培训，扩大代表性不足群体的参与，加强研究和教育，并通过计划的教育和外联活动以及向学术界、工业界、为了实现研究目标并提出当前电网响应和恢复方案的重大变化，将制定一个电力资产主动回收框架，以增强恢复能力。在这个框架内，将提出下一代主动恢复决策工具，将开发几个协调模型，包括（1）停电模型，以表明飓风对电力系统组件的影响，（2）随机飓风前船员动员模型，用于管理事件前的资源，（3）确定性飓风后恢复模型，用于管理事件后的资源，以及（4）将包含在机组动员和恢复模型中的停机和修理模型。这些模型将得到扩展，以确保适用于具有不同技术和监管问题的各种电网。随机飓风前船员动员模型将使用数学优化的最新进展，其中包括蒙特卡洛抽样，追索权建模和机会约束建模，以找到最适合的方法。该框架将被验证，其适用性，以大规模的实际电网将被验证，利用从该项目的电力公司合作者获得的数据。研究结果的理论和实践意义将推动电网主动响应和恢复方案的研究前沿。这项研究的变革性质支持应用于各种基础设施，并应对各种极端天气事件和自然灾害。

This project aims at developing a comprehensive framework and the supporting theory for increasing resiliency of the critical electric power grid infrastructure in response to hurricanes and accordingly expediting recovery process for minimizing the associated economic, social, and physical disruptions. This research has profound impacts on local and national energy security, reliability, and sustainability by promoting the sound development of advanced techniques related to extreme weather events and natural disasters which are identified as the second cause of the largest blackouts in the United States. The project results will directly impact the society through helping electric power grid operators better manage available resources, reducing aftermath of hurricanes and other natural disasters, and accordingly saving billions of dollars in electric power grid outage and recovery related costs. This research will increase public awareness and facilitate the understanding of the complexity of hurricanes and the required recovery plans among stakeholders, ratepayers, regulators, utility executives, and market participants. Furthermore, this research will enable a rapid and wide-spread deployment of new technologies in smart grid, which will create substantial job opportunities in this area. In a broader scope, the project will promote teaching and training of future workforce, broaden participation of underrepresented groups, enhance research and education, and improve scientific and technological understanding via planned education and outreach activities as well as dissemination of findings to academia, industry, and the general public.In order to fulfill research objectives and present a significant change in current electric power grid response and recovery schemes, a framework for Proactive Recovery of Electric Power Assets for Resiliency Enhancement (PREPARE) will be developed. Within this framework, which will present the next generation decision making tool for proactive recovery, several coordinated models will be developed including (1) outage models to indicate the impact of hurricanes on power system components, (2) a stochastic pre-hurricane crew mobilization model for managing resources before the event, (3) a deterministic post-hurricane recovery model for managing resources after the event, and (4) outage and repair models to be incorporated in crew mobilization and recovery models. The models will be extended to ensure applicability to a variety of electric power grids with different technologies and regulatory issues. The stochastic pre-hurricane crew mobilization model will be developed using latest advances in mathematical optimization, which includes Monte Carlo Sampling, Recourse Modeling, and Chance Constraint Modeling, to find the best suited approach. The framework will be validated and its applicability to large-scale practical electric power grids will be verified by leveraging the data obtained from the electric utility collaborator of the project. The theoretical and practical implications of the developed results will push the research frontier of proactive response and recovery schemes in electric power grids. The transformative nature of this research supports application to a variety of infrastructures, and in response to a wide range of extreme weather events and natural disasters.