AitF: Collaborative Research: Algorithms and Mechanisms for the Distribution Grid

AitF：协作研究：配电网算法和机制

• 批准号: 1733832
• 负责人: Evdokia Nikolova
• 金额: $ 48万
• 依托单位: University of Texas at Austin
• 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: 2017-10-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1733832&HistoricalAwards=false
• 关键词: AitF; Collaborative; Research; Algorithms; Mechanisms

The electricity distribution grid --the low-voltage line networks that distribute power to end consumers--is about to undergo a major transformation. More and more consumers are becoming "prosumers", namely consumers and producers of power at the same time, by installing solar panels (PVs) on their home roofs and by purchasing electric vehicles, which may be used for energy storage. Traditionally, power in distribution grids has flown one way: from the substation to the end consumer. In the new world of prosumers, distribution grids need to accommodate flow in both directions. This is challenging the existing wire and transformer abilities to serve load at acceptable quality levels. Moreover, the increasing number of prosumers is resulting in dramatically higher uncertainty in demand forecasting, which, with further prosumer increase, may prove unsustainable and ultimately threaten the utility companies' operation and business viability. This research advances the fields of computation and economics as well as the power systems domain, by contributing with novel algorithmic and mechanism design problem formulations and techniques, and with solutions that can enable improved distribution grid planning and operation. In terms of broader impact, this research has the potential to improve aspects of the grid such as planning for increased integration of renewable energy resources, mitigation of risks associated with variability of renewables, better management of congestion in the face of strategic prosumers and ultimately provide for more reliable, cost effective and efficient operation of the grid. The goal of this project is to help the distribution grid and its participants transition from its current functionality of serving mostly traditional consumers, to the future grid that needs to sustainably integrate prosumers, renewables and distributed energy resources, via: (1) Developing simplified mathematical models to solve combinatorial and incentive problems that will enable the future power grid to sustain massive growth in renewables and distributed energy resources; (2) Designing new algorithmic and mechanism design approaches that reduce congestion, and improve the investment and operational efficiency of the grid while further enhancing its reliability; (3) Working with Distribution Utilities for real-world models and operational advice, while facilitating the transfer of research findings to practice. The scope of the project includes (i) distribution network reconfiguration, (ii) distribution system upgrades and (iii) market mechanisms for supply-demand balancing. The research relies on methods from approximation algorithms and mechanism design, such as submodular optimization, stochastic combinatorial optimization, and price of anarchy analysis.

配电网--向终端用户输送电力的低压线路网络--即将经历一场重大变革。越来越多的消费者通过在自家屋顶安装太阳能电池板(PV)和购买可用于储能的电动汽车，正在成为“消费者”，即同时成为电力的消费者和生产者。传统上，配电网中的电力只有一个方向：从变电站到最终用户。在消费者的新世界里，配电网需要容纳双向流动。这对现有的电线和变压器以可接受的质量水平服务负载的能力构成了挑战。此外，消费者数量的增加导致需求预测的不确定性大大增加，随着消费者数量的进一步增加，这可能被证明是不可持续的，并最终威胁到公用事业公司的运营和业务生存能力。这项研究通过提供新的算法和机制设计问题的公式和技术，以及能够改进配电网规划和运行的解决方案，推动了计算和经济领域以及电力系统领域的发展。就更广泛的影响而言，这项研究有可能改进电网的各个方面，如规划加强可再生能源资源的整合、缓解与可再生能源变化性相关的风险、在面对战略消费者时更好地管理拥堵，并最终提供更可靠、更具成本效益和更高效率的电网运营。该项目的目标是帮助配电网及其参与者从目前主要服务于传统用户的功能过渡到需要可持续地整合消费者、可再生能源和分布式能源的未来电网，方法是：(1)开发简化的数学模型来解决组合和激励问题，使未来电网能够保持可再生能源和分布式能源的巨大增长；(2)设计新的算法和机制设计方法，以减少阻塞，提高电网的投资和运营效率，同时进一步增强其可靠性；(3)与分销公用事业公司合作，提供真实世界的模型和操作建议，同时促进将研究成果转化为实践。该项目的范围包括(1)重新配置配电网络，(2)配电系统升级和(3)供需平衡的市场机制。本研究依赖于近似算法和机制设计的方法，如子模块优化、随机组合优化、无政府状态价格分析等。

项目成果

Electrical flows over spanning trees

跨树上的电流

• DOI: 10.1007/s10107-020-01614-x
• 发表时间: 2021
• 期刊: Mathematical Programming
• 影响因子: 2.7
• 作者: Gupta, Swati;Khodabakhsh, Ali;Mortagy, Hassan;Nikolova, Evdokia
• 通讯作者: Nikolova, Evdokia

A digraph fourier transform with spread frequency components

具有扩展频率分量的有向图傅里叶变换

• DOI: 10.1109/globalsip.2017.8309026
• 发表时间: 2017
• 期刊: Proceedings of IEEE Global Conference on Signal and Information Processing (GlobalSIP 2017
• 作者: Shafipour, Rasoul;Khodabakhsh, Ali;Mateos, Gonzalo;Nikolova, Evdokia
• 通讯作者: Nikolova, Evdokia

Risk-Averse Selfish Routing

规避风险的自私路由

• DOI: 10.1287/moor.2017.0913
• 发表时间: 2018
• 期刊: Mathematics of Operations Research
• 影响因子: 1.7
• 作者: Lianeas, Thanasis;Nikolova, Evdokia;Stier-Moses, Nicolas E.
• 通讯作者: Stier-Moses, Nicolas E.

Optimal Mechanism Design with Risk-loving Agents

具有风险偏好主体的最优机制设计

• DOI: 10.1007/978-3-030-04612-5_25
• 发表时间: 2018
• 期刊: Proceedings of the 14th Conference on Web and Internet Economics
• 作者: Nikolova, Evdokia;Yang, Ger;Pountourakis, Emmanouil
• 通讯作者: Pountourakis, Emmanouil

A Submodular Approach for Electricity Distribution Network Reconfiguration

配电网重构的子模块方法

• 发表时间: 2018
• 期刊: Proceedings of the 51st Hawaii International Conference on System Sciences (HICSS
• 作者: Khodabakhsh, A;Yang, G;Basu, S;Nikolova, E;Caramanis, M;Lianeas, T;Pountourakis, E.
• 通讯作者: Pountourakis, E.