AMPS: Collaborative Research: Stochastic Modeling of the Power Grid
AMPS:协作研究:电网随机建模
基本信息
- 批准号:1736439
- 负责人:
- 金额:$ 17万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-09-01 至 2022-03-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This project will develop mathematical models for the interactions between the economic stake-holders in the modern power grid. While the electricity market is becoming decentralized, understanding the underlying market forces in the presence of fluctuating market conditions and regulations remains inadequate. Providing higher quality information and modeling aids to decision makers is crucial in the drive to achieve grid efficiency and enhanced stability. It is also central to avoiding unintended consequences that have plagued economic policy-making for the grid and for making effective regulations that incentivize aligning stakeholder behavior with societal goals, such as climate change adaptation and investment in new technologies.The project will construct rigorous stochastic models and related numerical algorithms for quantitative assessment and analysis of how to guide the grid in its "smart" evolution. The research will address (i) long-term grid evolution, in particular investment in renewable generation and competition between different producer sectors; (ii) behavior of electricity prices and related financial contracts in the new era of deep renewable penetration, micro-grids, and new requirements on grid stability. The project blends together applied mathematics, game theory, and control, and extends the reach of stochastics to a key application area. The project will contribute to inter-disciplinary training in mathematical sciences at the PhD level and will enhance the exchange of ideas between mathematicians, operations researchers, engineers, and statisticians.
该项目将为现代电网中经济利益相关者之间的相互作用建立数学模型。虽然电力市场正在变得分散,但在市场条件和法规不断波动的情况下,了解潜在的市场力量仍然不够。为决策者提供更高质量的信息和建模辅助工具对于实现电网效率和增强稳定性至关重要。对于避免困扰电网经济政策制定的意外后果,以及制定有效的法规,激励利益相关者的行为与社会目标保持一致,如适应气候变化和投资新技术,这也是至关重要的。该项目将构建严格的随机模型和相关的数值算法,用于定量评估和分析如何引导电网的“智能”演变。研究将涉及(I)电网的长期演变,特别是对可再生能源发电的投资和不同生产者部门之间的竞争;(Ii)可再生能源深入渗透的新时代的电价和相关金融合同的行为、微电网以及对电网稳定性的新要求。该项目融合了应用数学、博弈论和控制,并将随机学的范围扩展到一个关键的应用领域。该项目将促进博士级数学科学的跨学科培训,并将加强数学家、运筹学研究人员、工程师和统计学家之间的思想交流。
项目成果
期刊论文数量(5)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
The effect of rate design on power distribution reliability considering adoption of distributed energy resources
考虑采用分布式能源的费率设计对配电可靠性的影响
- DOI:10.1016/j.apenergy.2020.114964
- 发表时间:2020
- 期刊:
- 影响因子:11.2
- 作者:Maheshwari, Aditya;Heleno, Miguel;Ludkovski, Michael
- 通讯作者:Ludkovski, Michael
Regression Monte Carlo for Impulse Control
- DOI:10.5802/msia.18
- 发表时间:2022-03
- 期刊:
- 影响因子:0
- 作者:M. Ludkovski
- 通讯作者:M. Ludkovski
Statistical Learning for Probability-Constrained Stochastic Optimal Control
概率约束随机最优控制的统计学习
- DOI:10.1016/j.ejor.2020.08.041
- 发表时间:2020
- 期刊:
- 影响因子:6.4
- 作者:Balata, Alessandro;Ludkovski, Michael;Maheshwari, Aditya;Palczewski, Jan
- 通讯作者:Palczewski, Jan
An Impulse-Regime Switching Game Model of Vertical Competition
纵向竞争的脉冲机制切换博弈模型
- DOI:10.1007/s13235-021-00381-4
- 发表时间:2021
- 期刊:
- 影响因子:1.5
- 作者:Aïd, René;Campi, Luciano;Li, Liangchen;Ludkovski, Mike
- 通讯作者:Ludkovski, Mike
Simulation methods for stochastic storage problems: a statistical learning perspective
随机存储问题的模拟方法:统计学习的角度
- DOI:10.1007/s12667-018-0318-4
- 发表时间:2019
- 期刊:
- 影响因子:0
- 作者:Ludkovski, Michael;Maheshwari, Aditya
- 通讯作者:Maheshwari, Aditya
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Michael Ludkovski其他文献
Sequential tracking of a hidden Markov chain using point process observations
- DOI:
10.1016/j.spa.2008.09.003 - 发表时间:
2009-06-01 - 期刊:
- 影响因子:
- 作者:
Erhan Bayraktar;Michael Ludkovski - 通讯作者:
Michael Ludkovski
Probabilistic spatiotemporal modeling of day-ahead wind power generation with input-warped Gaussian processes
具有输入扭曲高斯过程的日前风力发电概率时空建模
- DOI:
10.1016/j.spasta.2025.100906 - 发表时间:
2025-08-01 - 期刊:
- 影响因子:2.500
- 作者:
Qiqi Li;Michael Ludkovski - 通讯作者:
Michael Ludkovski
Extreme day-ahead renewables scenario selection in power grid operations
电网运营中日前可再生能源极端情景选择
- DOI:
10.1016/j.apenergy.2025.125747 - 发表时间:
2025-08-01 - 期刊:
- 影响因子:11.000
- 作者:
Guillermo Terrén-Serrano;Michael Ludkovski - 通讯作者:
Michael Ludkovski
Michael Ludkovski的其他文献
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{{ truncateString('Michael Ludkovski', 18)}}的其他基金
Collaborative Research: Pacific Alliance for Low-Income Inclusion in Statistics & Data Science
合作研究:太平洋低收入统计联盟
- 批准号:
2221421 - 财政年份:2022
- 资助金额:
$ 17万 - 项目类别:
Continuing Grant
Collaborative Research: Gaussian Process Frameworks for Modeling and Control of Stochastic Systems
合作研究:随机系统建模和控制的高斯过程框架
- 批准号:
1821240 - 财政年份:2018
- 资助金额:
$ 17万 - 项目类别:
Standard Grant
CDS&E-MSS/Collaborative Research: Sequential Design for Stochastic Control: Active Learning of Optimal Policies
CDS
- 批准号:
1521743 - 财政年份:2015
- 资助金额:
$ 17万 - 项目类别:
Standard Grant
Conference on Stochastic Asymptotics and Applications, September 25-27, 2014
随机渐近学及其应用会议,2014 年 9 月 25-27 日
- 批准号:
1413574 - 财政年份:2014
- 资助金额:
$ 17万 - 项目类别:
Standard Grant
Collaborative Research: ATD: Sequential Quickest Detection and Identification of Multiple Co-dependent Epidemic Outbreaks
合作研究:ATD:多种相互依赖的流行病爆发的顺序最快检测和识别
- 批准号:
1222262 - 财政年份:2012
- 资助金额:
$ 17万 - 项目类别:
Standard Grant
Workshop on Financial Engineering Methods for Insurance Mathematics
保险数学金融工程方法研讨会
- 批准号:
0649523 - 财政年份:2007
- 资助金额:
$ 17万 - 项目类别:
Standard Grant
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