CRII: NeTS: Enabling Demand Response from Cloud Data Centers -- from Sustainable IT to IT for Sustainability

CRII：NeTS：实现云数据中心的需求响应——从可持续 IT 到 IT 促进可持续发展

• 批准号: 1464388
• 负责人: Zhenhua Liu
• 金额: $ 17.5万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-05-01 至 2018-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1464388&HistoricalAwards=false
• 关键词: CRII; NeTS; Enabling; Demand; Response

It is now recognized that cloud data centers are a significant consumer of energy resources and a substantial source of greenhouse gas emission. On the other hand, the intermittency and uncertainty of renewable energy present a daunting operating challenge for the electricity grid. The key idea behind this CRII: Cyber-Physical Systems project is that these two challenges are in fact symbiotic: data centers can be virtual batteries for the electricity grid. Specifically, data centers are large loads, but are also flexible. If the electricity grid can call on the flexibilities of data centers via appropriate demand response programs, this will be a crucial tool for easing the incorporation of renewable energy into the electricity grid. Unfortunately, despite the great potential, the current reality is that data centers perform little demand response. This project aims at the interdisciplinary challenges of enabling demand response from cloud data centers to realize the societal benefits.The overarching goal of this project is to develop an intellectual framework to understand and guide the realization of demand response from cloud data centers, to address engineering and economic challenges in order to manage the daunting risk. This project will first quantify the potential economic and environmental benefits of demand response from cloud data centers. The quantification includes the societal cost savings and emission reductions from networked data centers through geographical load balancing, and the impacts of demand response taxonomy. Built upon the first thrust, this project will continue to tackle the interdisciplinary challenges of both local control algorithm design and global market design for data center demand response in order to facilitate their participation in various demand response programs. The researchers will study prediction-based pricing design and analysis, demand response program design based on optimization decomposition, and distributed online algorithm design for risk management and distributed control. The results of this project will, at the societal level, help utility companies and load serving entities realize the great potential that lies in the Cloud, and, furthermore, design demand response programs that provide right incentives for data center operators to participate. At a local level, this project will help guide the management of geographically distributed data centers in participating in the right demand response programs. The control algorithms and demand response programs, as well as the methodology, can be applied beyond data centers. This research will create new knowledge in distributed online algorithm design and optimization-based market design. Additionally, this project will help design an interdisciplinary course Sustainable IT and IT for Sustainability. Personnel involved in this project, graduates and undergraduates, will receive innovation experiences through the algorithm design, analysis, implementation, and testing.

现在人们认识到，云数据中心是能源资源的重要消耗者，也是温室气体排放的重要来源。另一方面，可再生能源的不稳定性和不确定性给电网带来了严峻的运营挑战。CRII：网络物理系统项目背后的关键思想是，这两个挑战实际上是共生的：数据中心可以成为电网的虚拟电池。具体而言，数据中心是大负载，但也是灵活的。如果电网能够通过适当的需求响应计划来调用数据中心的灵活性，这将是将可再生能源纳入电网的关键工具。不幸的是，尽管有巨大的潜力，但目前的现实是数据中心很少执行需求响应。该项目旨在解决云数据中心需求响应实现社会效益的跨学科挑战，其总体目标是开发一个知识框架，以理解和指导云数据中心需求响应的实现，解决工程和经济挑战，以管理令人生畏的风险。该项目将首先量化云数据中心需求响应的潜在经济和环境效益。量化包括通过地理负载平衡从网络数据中心节省的社会成本和减少的排放，以及需求响应分类的影响。基于第一个目标，该项目将继续解决数据中心需求响应的本地控制算法设计和全球市场设计的跨学科挑战，以促进他们参与各种需求响应计划。研究人员将研究基于预测的定价设计和分析，基于优化分解的需求响应程序设计，以及用于风险管理和分布式控制的分布式在线算法设计。该项目的结果将在社会层面上帮助公用事业公司和负载服务实体实现云计算的巨大潜力，并设计需求响应计划，为数据中心运营商提供正确的激励措施。在地方一级，该项目将帮助指导地理上分散的数据中心的管理人员参与正确的需求响应计划。控制算法和需求响应程序以及方法可以应用于数据中心之外。本研究将为分布式在线算法设计和基于优化的市场设计提供新的知识。此外，该项目将帮助设计一个跨学科的课程可持续的IT和IT的可持续性。参与该项目的人员，研究生和本科生，将通过算法设计，分析，实现和测试获得创新经验。