CyberSEES: Type 1: Collaborative Research: Sustainability-aware Management of Interdependent Power and Water Systems

Cyber​​SEES：类型 1：协作研究：相互依赖的电力和水系统的可持续性意识管理

• 批准号: 1830746
• 负责人: Josue Medellin-Azuara
• 金额: $ 0.84万
• 依托单位: University of California - Merced
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-02-01 至 2019-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1830746&HistoricalAwards=false
• 关键词: CyberSEES; Type; Collaborative; Research; Sustainability

While extensive attention has been given to sustainability in the energy systems, including the subsystems of electricity, petroleum, and natural gas, an oft-overlooked aspect is the interdependence between energy and other infrastructure systems, such as water and transportation systems, and the potential adverse impacts to economics, reliability, and sustainability caused by such interdependence. For example, regulations in the water sector to preserve freshwater may restrict water usage in the power sector, likely causing reduced available generation capacities and hence jeopardizing the reliability of power systems. On the other hand, environmental policies only focused on the power sector, such as those encouraging retrofitting or installing carbon dioxide capture and sequestration capabilities to existing and new coal plants would further constrain the water system as coal plants with carbon sequestration are among the heaviest users of water. Thus, there is a clear need to better understand and manage the interdependence of critical infrastructure systems to promote sustainability across all systems, while not undermining economic and reliability considerations. This proposed work aims to address this need through the theory, modeling and computation of large-scale, interdependent complex systems by way of distributed, highly scalable computing. The results will be widely disseminated through publications and seminars. Further, the project team will leverage established institutional outreach programs to the general public, especially to high-school students and teachers, such as through the Engineering Projects In Community Service program and Purdue?s Energy Academy. The grand vision of this project is to promote sustainability across interdependent systems, as well as to achieve economic efficiency and to maintain reliability through decentralized yet coordinated management of individual systems by establishing a complete modeling, analytical, and computational framework based upon the general class of augmented Lagrangian methods originating from convex optimization. While the augmented Lagrangian method is not a new algorithm, the current implementation of such algorithms has not taken advantage of its distributed feature, which would be particularly suitable to deal with large-scale, interlinked systems. One of the major goals of this work is to establish the theoretical foundations of distributed Lagrangian methods and to implement the algorithms on supercomputer clusters to demonstrate the benefits of distributed computing. This research aims to pave the way for cloud computing such that the algorithms can be used by decision-makers even without access to supercomputers. Another contribution is that the augmented Lagrangian method algorithms will be extended to incorporate stochastic data, both in terms of theoretical issues such as algorithm convergence as well as practical implementation. The computational methods will be tested and validated through real-world models of interdependent power and water systems.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.

虽然人们广泛关注能源系统的可持续性，包括电力、石油和天然气等子系统，但一个经常被忽视的方面是能源和其他基础设施系统（如水和运输系统）之间的相互依赖性，以及这种相互依赖性对经济、可靠性和可持续性造成的潜在不利影响。例如，水部门保护淡水的条例可能会限制电力部门的用水，从而可能导致可用发电能力减少，从而危及电力系统的可靠性。另一方面，环境政策只侧重于电力部门，如鼓励现有和新的燃煤电厂改造或安装二氧化碳捕获和封存能力的政策，将进一步限制供水系统，因为具有碳封存功能的燃煤电厂是用水量最大的电厂之一。因此，显然需要更好地理解和管理关键基础设施系统的相互依存性，以促进所有系统的可持续性，同时不损害经济和可靠性方面的考虑。这项工作的目的是通过分布式，高度可扩展的计算方式，通过理论，建模和计算的大规模，相互依存的复杂系统，以满足这一需求。调查结果将通过出版物和研讨会广泛传播。此外，项目组将利用既定的机构外展计划，以广大公众，特别是高中学生和教师，如通过工程项目在社区服务计划和普渡大学？能源学院。该项目的宏伟愿景是促进相互依赖的系统的可持续性，以及通过建立一个完整的建模，分析和计算框架，基于源自凸优化的一般类增强拉格朗日方法，通过分散但协调的单个系统管理来实现经济效率和保持可靠性。虽然增广拉格朗日方法不是一个新的算法，目前的实现，这样的算法没有利用其分布式功能，这将是特别适合于处理大规模的，互联的系统。这项工作的主要目标之一是建立分布式拉格朗日方法的理论基础，并在超级计算机集群上实现算法，以证明分布式计算的好处。这项研究旨在为云计算铺平道路，使决策者即使没有超级计算机也可以使用这些算法。另一个贡献是，增广拉格朗日方法算法将扩展到纳入随机数据，无论是在理论问题，如算法收敛以及实际执行。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。