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: 1539593
• 负责人: Josue Medellin-Azuara
• 金额: $ 4.04万
• 依托单位: University of California-Davis
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-01-01 至 2018-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1539593&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.

虽然人们对能源系统的可持续性给予了广泛关注，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与其他基础设施系统之间的相互依赖，以及这种相互依赖对经济、可靠性和可持续性造成的潜在不利影响。例如，水务部门保护淡水的规定可能会限制电力部门的用水，可能会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，只关注电力部门的环境政策，例如那些鼓励对现有和新的燃煤电厂进行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，因为具有固碳功能的燃煤电厂是用水量最大的电厂之一。因此，显然需要更好地了解和管理关键基础设施系统之间的相互依存关系，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。这项拟议的工作旨在通过分布式、高度可扩展计算的方式，通过大规模、相互依赖的复杂系统的理论、建模和计算来满足这一需求。结果将通过出版物和研讨会广泛传播。此外，项目团队将利用已建立的面向公众的机构外展计划，特别是针对高中生和教师的计划，例如通过社区服务工程项目和普渡？S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，并通过分散但协调地管理单个系统来实现经济效率和保持可靠性，方法是基于源于凸优化的增广拉格朗日方法的一般类建立完整的建模、分析和计算框架。虽然增广拉格朗日方法并不是一个新的算法，但目前这类算法的实现并没有利用它的分布式特性，而这一特性特别适合于处理大规模的、相互关联的系统。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，以展示分布式计算的好处。这项研究旨在为云计算铺平道路，以便决策者即使在没有超级计算机的情况下也可以使用这些算法。另一个贡献是，增广拉格朗日方法的算法将被扩展，以纳入随机数据，无论是在算法收敛的理论问题上，还是在实际实现方面。计算方法将通过相互依赖的电力和供水系统的真实世界模型进行测试和验证。