EAGER: A Dynamical Systems Approach to Modeling and Controlling Responsive Demand in Electric Power Systems
EAGER:电力系统响应需求建模和控制的动态系统方法
基本信息
- 批准号:1546682
- 负责人:
- 金额:$ 29.75万
- 依托单位:
- 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:2015-08-15 至 2018-07-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This project envisions a novel framework that will enable power grid operators to close the loop around flexible demand. The researchers will introduce and test a transfer function dynamical systems view of responsive demand, where the response can be to price or other variables that can influence demand response, such as temperature. The project will provide a fresh perspective on modeling the dynamical response of consumer behavior subject to incentives and other influence variables, as well insights into how independent system operators can incorporate demand response fully into consideration. Once successful, this initiative could unlock the collective flexibility untapped in today's demand response markets. The exploratory research is likely to have a transformative impact on the systematic modeling, analysis, and control of tens of millions of access points in the future grid. It will benefit future grid operators and Energy Management Systems (EMS) in characterizing responsive customers. The team will continue its collaboration with the local grid operator, and will present research findings to Electric Reliability Council of Texas (ERCOT) through site visits.The project will also address quantification of uncertainty associated with aggregating many price-based demand responses. This modeling approach will enable system operators and load serving entities to consider load flexibility in a manner similar to how generators are currently modeled. Thereby it makes possible a holistic closure of loops simultaneously around generation and demand. The intellectual merit of this project is three-fold. First, it offers a unifying dynamical systems approach to modeling both demand as well as supply in the smart grid. While most generators are well characterized by first principles, responsive demand (including demand that is responsive to price) has not been similarly modeled in a manner that reflects the salient feature of electricity consumption. Modeling both genrators and demand response as dynamical systems makes possible a holistic treatment of electricity generation and consumption. Second, this project investigates the aggregated uncertainty associated with responsive demand. This difficult problem will address both the spatial and temporal correlations associated with different demands. Third, a novel optimal contract design for load serving entities will be investigated, to elicit a desirable level of demand response. This early-stage research puts forward an ambitious and potentially highly rewarding plan for modeling and control of responsive demand from a transfer function perspective.
该项目设想了一种新颖的框架,使电网运营商能够围绕灵活的需求形成闭环。研究人员将引入并测试响应需求的传递函数动态系统观点,其中响应可以是价格或其他可能影响需求响应的变量,如温度。该项目将提供一个新的视角来建模受激励和其他影响变量影响的消费者行为的动态响应,以及对独立系统运营商如何充分考虑需求响应的见解。一旦成功,这一举措将释放当前需求响应市场尚未开发的集体灵活性。探索性研究可能会对未来电网中数千万接入点的系统建模、分析和控制产生变革性影响。它将使未来的电网运营商和能源管理系统(EMS)在响应客户方面受益。该团队将继续与当地电网运营商合作,并将通过实地考察向德克萨斯州电力可靠性委员会(ERCOT)提交研究成果。该项目还将解决与汇总许多基于价格的需求响应相关的不确定性的量化问题。这种建模方法将使系统操作员和负载服务实体能够以类似于当前对生成器建模的方式考虑负载灵活性。因此,它使同时围绕发电和需求的循环整体封闭成为可能。这个项目的智力价值是三重的。首先,它提供了一种统一的动态系统方法来对智能电网的需求和供应进行建模。虽然大多数发电机都很好地体现了第一原则,但响应需求(包括对价格有响应的需求)并没有以类似的方式反映电力消耗的显著特征。将发电机和需求响应建模为动态系统使得对发电和用电的整体处理成为可能。其次,本项目研究了与响应性需求相关的总体不确定性。这一难题将涉及与不同需求相关的空间和时间相关性。第三,将研究一种新的负荷服务实体的最优契约设计,以获得理想的需求响应水平。这个早期阶段的研究提出了一个雄心勃勃的、潜在的高回报的计划,从传递函数的角度来建模和控制响应性需求。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Persistent-homology-based detection of power system low-frequency oscillations using PMUs
- DOI:10.1109/globalsip.2016.7905952
- 发表时间:2016-12
- 期刊:
- 影响因子:0
- 作者:Yang Chen;H. Chintakunta;Le Xie;yuliy baryshnikov;P. Kumar
- 通讯作者:Yang Chen;H. Chintakunta;Le Xie;yuliy baryshnikov;P. Kumar
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Le Xie其他文献
Robust and real-time guidewire simulation based on Kirchhoff elastic rod for vascular intervention training
基于基尔霍夫弹性杆的鲁棒实时导丝模拟用于血管介入训练
- DOI:
10.1007/s12204-014-1551-1 - 发表时间:
2014 - 期刊:
- 影响因子:0
- 作者:
Maisheng Luo;Hong;Le Xie;Ping Cai;Li - 通讯作者:
Li
Multi-scale Integration of Physics-Based and Data-Driven Models in Power Systems
电力系统中基于物理和数据驱动的模型的多尺度集成
- DOI:
10.1109/iccps.2012.21 - 发表时间:
2012 - 期刊:
- 影响因子:0
- 作者:
Le Xie;Yun Zhang;M. Ilić - 通讯作者:
M. Ilić
Review on the interlimb neural coupling and its potential usage in walking rehabilitation
肢间神经耦合及其在步行康复中的潜在应用综述
- DOI:
10.1007/s12204-014-1541-3 - 发表时间:
2014 - 期刊:
- 影响因子:0
- 作者:
Juan Fang;Le Xie;Guo - 通讯作者:
Guo
Stress changes of lateral collateral ligament at different knee flexion with or without displaced movements: a 3-dimensional finite element analysis.
不同膝关节屈曲时外侧副韧带的应力变化,有或没有移位运动:3维有限元分析。
- DOI:
- 发表时间:
2011 - 期刊:
- 影响因子:0
- 作者:
Y. Zhong;You Wang;Hai;Ke Rong;Le Xie - 通讯作者:
Le Xie
Engineering IT-Enabled Sustainable Electricity Services
工程 IT 支持的可持续电力服务
- DOI:
- 发表时间:
2013 - 期刊:
- 影响因子:0
- 作者:
M. Ilić;Le Xie;Qixing Liu - 通讯作者:
Qixing Liu
Le Xie的其他文献
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{{ truncateString('Le Xie', 18)}}的其他基金
Workshop: Towards Carbon-neutral Electricity and Mobility: The Infrastructure Challenges and Opportunities; Houston, Texas; 28 February - 1 March 2022
研讨会:迈向碳中和电力和交通:基础设施的挑战和机遇;
- 批准号:
2203357 - 财政年份:2022
- 资助金额:
$ 29.75万 - 项目类别:
Standard Grant
RAPID: A Cross-Infrastructure Data-driven Approach to Modeling and Simulation of the 2021 Texas Power Outage
RAPID:跨基础设施数据驱动的 2021 年德克萨斯州停电建模和仿真方法
- 批准号:
2130945 - 财政年份:2021
- 资助金额:
$ 29.75万 - 项目类别:
Standard Grant
A Cross-Domain Data-driven Approach to Analyzing and Predicting the Impact of COVID-19 on the U.S. Electricity Sector
跨域数据驱动方法分析和预测 COVID-19 对美国电力行业的影响
- 批准号:
2035688 - 财政年份:2020
- 资助金额:
$ 29.75万 - 项目类别:
Standard Grant
Collaborative Research: High-Dimensional Spatio-Temporal Data Science for a Resilient Power Grid: Towards Real-Time Integration of Synchrophasor Data
合作研究:弹性电网的高维时空数据科学:同步相量数据的实时集成
- 批准号:
1934675 - 财政年份:2019
- 资助金额:
$ 29.75万 - 项目类别:
Continuing Grant
NSF Workshop on Real-time Learning and Decision Making of Dynamical Systems. To Be Held at NSF, February 12-13, 2018.
NSF 动态系统实时学习和决策研讨会。
- 批准号:
1818201 - 财政年份:2018
- 资助金额:
$ 29.75万 - 项目类别:
Standard Grant
EAGER: Real-Time: Precision Reserves from Flexible Loads: An Online Reinforcement Learning Approach
EAGER:实时:灵活负载的精度储备:在线强化学习方法
- 批准号:
1839616 - 财政年份:2018
- 资助金额:
$ 29.75万 - 项目类别:
Standard Grant
RAPID: Powering through the hurricane: self-organizing power electronics intelligence at the network edge
RAPID:渡过飓风:网络边缘的自组织电力电子智能
- 批准号:
1760554 - 财政年份:2017
- 资助金额:
$ 29.75万 - 项目类别:
Standard Grant
Microgrid Interconnections Control via Voltage Angle Droop Methods
通过电压角下垂方法进行微电网互连控制
- 批准号:
1611301 - 财政年份:2016
- 资助金额:
$ 29.75万 - 项目类别:
Standard Grant
Capacity Building: Collaborative Research: Integrated Learning Environment for Cyber Security of Smart Grid
能力建设:协作研究:智能电网网络安全的集成学习环境
- 批准号:
1303378 - 财政年份:2013
- 资助金额:
$ 29.75万 - 项目类别:
Standard Grant
Collaborative Research: CyberSEES: Coupon Incentive-based Risk Aware Demand Response in Smart Grid
合作研究:CyberSEES:智能电网中基于优惠券激励的风险意识需求响应
- 批准号:
1331863 - 财政年份:2013
- 资助金额:
$ 29.75万 - 项目类别:
Standard Grant
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