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.

电力分配网格（低压线网络将电力分配给最终消费者）将要进行重大转换。越来越多的消费者正在成为“生产商”，即同时通过在自己的家庭屋顶上安装太阳能电池板（PVS），并购买电动汽车，该电动机可以同时成为消费者和电力生产商，并购买了电动汽车，该电动汽车可用于储能。传统上，分销网格的力量已经以一种方式飞行：从变电站到最终消费者。在新的生产者世界中，分销网格需要在两个方向上适应流动。这挑战了现有的电线和变压器能力，以便在可接受的质量水平下为负载提供负载。此外，越来越多的生产商导致需求预测的不确定性极高，随着进一步的生产，这可能证明是不可持续的，并最终威胁到公用事业公司的运营和业务可行性。这项研究通过新颖的算法和机制设计问题的表述和技术来促进计算和经济学以及电力系统领域的领域，以及可以改善分布网格计划和操作的解决方案。在更广泛的影响方面，这项研究具有改善网格的各个方面的潜力，例如计划增加可再生能源资源的整合，减轻与可再生能源可变性相关的风险，更好地管理战略伪造者，并最终提供更可靠的，更可靠的，成本有效的电网操作。该项目的目的是帮助分销网格及其参与者从目前的主要为传统消费者服务的功能过渡到未来的网格，需要可持续地整合生产商，可再生能源和分配能源资源，通过以下方式： （2）设计新的算法和机制设计方法，以减少拥堵并提高电网的投资和运营效率，同时进一步提高其可靠性； （3）与分销公用事业合作以实现现实世界模型和运营建议，同时促进研究结果转移到实践。 该项目的范围包括（i）分销网络重新配置，（ii）分配系统升级和（iii）供求需求平衡的市场机制。 该研究依赖于近似算​​法和机制设计的方法，例如次试验优化，随机组合优化和无政府状态分析的价格。

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

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.

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

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.

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