权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

CAREER: Optimization, Control, and Incentive Design for Power Networks with High Levels of Distributed Energy Resources

职业：高水平分布式能源电力网络的优化、控制和激励设计

基本信息

批准号：
1553407
负责人：
Na Li
金额：
$ 50万
依托单位：
Harvard University
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：
2016-02-01 至 2022-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1553407&HistoricalAwards=false
关键词：
CAREER Optimization Control Incentive Design

项目摘要

To improve the energy and environmental sustainability, the power grid is increasing the penetration of distributed energy resources, such as photovoltaic (PV) arrays, wind turbines, electric vehicles, batteries, and responsive demands. However, high levels of distributed energy resources can change the behavior of the grid, with potential undesirable effects on the grid stability and power quality. This necessitates transformative approaches to coordinate the large number of distributed energy resources. These approaches need to handle the high uncertainty involved in the renewable generation and to call upon customers to actively participate. Additional challenges are placed by the still-undeveloped sensing, communication, and computation resources for the grid. To address these challenges, this CAREER proposal is to develop distributed coordination rules to optimize, control, and incentivize the distributed energy resources in order to ensure efficient, adaptive, and reliable performance of the grid. The proposal will integrate multidisciplinary approaches, in particular, mathematics, engineering, and economics. Results can also be transferred to other large-scale socio-technical systems, such as transportation systems and water/gas distribution systems. Broad impacts will follow from an integrated educational dissemination plan, involvement of undergraduates especially under-represented groups in research, transition of new ideas to industry, and outreach to the general public and K-12 students.As a socio-technical system, two factors distinguish the power grid from other networks, its intrinsic physics and its close human interactions. Accordingly, this proposal will design automated distributed algorithms to optimize the performance of the energy resources at slow-time scales and to control them to ensure energy balance at fast-time scales, and design incentive schemes such as pricing, rewards, payoff, and trading rules to promote human participants to take desired actions. The automated algorithms will tackle the challenges brought by the power system physics (e.g. physical laws such as Kirchhoff's law and system dynamics such as swing dynamics), limited communication, and uncertain generation/consumption. The algorithms will also maximize the use of physics in order to lower sensing, communication, and computation overhead. The incentive schemes will tackle the challenges brought by the self-interested nature of humans. Owners of distributed energy resources are mostly profit-maximizing entities, seeking their own best interest and lacking incentives to reveal truthful private information. Lastly the proposal will jointly design the distributed architecture, algorithms and incentive schemes by strongly integrating the engineering and economics in order to ensure high-performance and high-confidence operation of distributed energy resources to facilitate a smoother transition for the grid into the next age of a smarter grid.

为了提高能源和环境的可持续性，电网正在增加分布式能源的渗透，如光伏（PV）阵列、风力涡轮机、电动汽车、电池和响应式需求。然而，高水平的分布式能源会改变电网的行为，对电网的稳定性和电力质量产生潜在的不良影响。这就需要变革的方法来协调大量的分布式能源。这些方法需要处理可再生能源发电的高度不确定性，并呼吁客户积极参与。网格的传感、通信和计算资源尚未开发，这给网格带来了额外的挑战。为了应对这些挑战，本CAREER建议开发分布式协调规则来优化、控制和激励分布式能源，以确保电网的高效、自适应和可靠性能。该提案将整合多学科方法，特别是数学、工程和经济学。成果也可以转移到其他大型社会技术系统，如运输系统和水/气分配系统。综合教育传播计划、本科生（尤其是代表性不足的群体）参与研究、新思想向工业的转变以及向公众和K-12学生的推广将产生广泛的影响。作为一个社会技术系统，电网有别于其他网络的两个因素是其内在的物理特性和与人类的密切互动。因此，本提案将设计自动化的分布式算法来优化慢时间尺度下的能源性能并控制它们以确保快时间尺度下的能源平衡，并设计诸如定价、奖励、报酬和交易规则等激励方案来促进人类参与者采取期望的行动。自动化算法将解决电力系统物理（如基尔霍夫定律等物理定律和摆动动力学等系统动力学）、有限通信和不确定发电/消耗带来的挑战。这些算法还将最大限度地利用物理，以降低传感、通信和计算开销。这些激励机制将解决人类自利天性带来的挑战。分布式能源的所有者大多是利润最大化的实体，追求自身的最大利益，缺乏披露真实私人信息的激励。最后，将工程与经济相结合，共同设计分布式架构、算法和激励方案，以确保分布式能源的高性能、高置信度运行，促进电网向下一个智能电网时代的平稳过渡。