EPCN: Enabling a Transactive Energy System from a Stochastic Geometry Framework

EPCN：从随机几何框架启用交互能源系统

• 批准号: 1855216
• 负责人: Bala Natarajan
• 金额: $ 48.18万
• 依托单位: Kansas State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1855216&HistoricalAwards=false
• 关键词: EPCN; Enabling; Transactive; Energy; System

The ability of active consumers and end devices to buy/sell energy and related services in a dynamic and interactive manner is expected to create a transactive energy (TE) market presenting new opportunities and challenges for distribution system operations. The implications of a market-based approach to operational management need to be better understood at both the consumer and utility levels. Researchers have typically attempted to address important and open operational questions using a simulation-based scenario analysis approach. The spatial and temporal randomness associated with energy generation/consumption as well as the stochastic behavior of consumers in response to pricing, significantly complicates the scale and number of Monte-Carlo simulations required to make meaningful and statistically valid inferences. Any changes to the network can force a re-computation that is cumbersome. While simulations provide useful insights on system operations for a specific set up, the dynamic nature of the TE market with multiple sources of uncertainty begs for the design of new planning tools. In this project, a suite of novel stochastic geometry based analytical approximations and bounds are derived in order to develop a unique operational planning tool that can be used in a sustaining mode (i.e., in conjunction with simulation tools) or as a disruptive standalone alternative depending on the needs of distribution system operator (DSO).This proposal introduces a new paradigm for operational planning incorporating analytical approximations and stochastic bounds in lieu of cumbersome simulations. By bringing together techniques from stochastic geometry, graph theory, information theory and power systems analysis, the PIs will derive new probabilistic voltage and loss sensitivity metrics that can be computed quickly and scale well with the size of the network. The probabilistic sensitivity analysis relies on both consumer level and network level stochastic abstractions that help quantify the average impact of varying penetration levels of active consumers on grid performance. The results from the probabilistic sensitivity analysis are used to develop the unique concept of a dominant influencer. Using the dominant influencer models, a network vulnerability rank can be determined and used to (1) quantify the susceptibility of the network to various points of cyber/physical attack, and (2) develop a hybrid control framework for DSOs to deploy and manage control assets within a TE system. The stochastic geometry framework also enables fast identification of inactive voltage constraints that can expedite power flow computations In summary, this project provides tools that will enable distribution systems operators to efficiently plan and operate distribution systems with large penetration of distributed renewable energy resources, electric vehicles, and engaged consumers. These tools will allow true techno-economic analysis of the system while incorporating consumer preferences. Results from this research will be: (1) integrated into several undergraduate and graduate courses, and (2) disseminated via publications in academic conferences and journals. The PIs will educate the public through Open House displays and field trips for K-12 students to encourage students from under-represented groups to pursue STEM careers.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

活跃的消费者和终端设备以动态和交互的方式购买/出售能源和相关服务的能力有望创造一个交易能源（TE）市场，为配电系统运营带来新的机遇和挑战。需要在消费者和公用事业两级更好地理解以市场为基础的业务管理办法的影响。研究人员通常试图使用基于模拟的情景分析方法来解决重要和开放的操作问题。与能量产生/消耗相关的空间和时间随机性以及消费者响应于定价的随机行为显著地使进行有意义的和统计上有效的推断所需的蒙特-卡罗模拟的规模和数量复杂化。网络的任何变化都可能迫使重新计算，这是很麻烦的。虽然模拟为特定设置的系统运营提供了有用的见解，但TE市场的动态性质具有多种不确定性来源，需要设计新的规划工具。在这个项目中，一套新的随机几何基础上的分析近似和边界推导，以开发一个独特的业务规划工具，可用于维持模式（即，结合仿真工具）或作为一个破坏性的独立的替代方案，这取决于配电系统运营商（DSO）的需求。该建议介绍了一种新的模式，结合分析近似和随机界，而不是繁琐的模拟操作规划。通过将随机几何学、图论、信息论和电力系统分析的技术结合在一起，PI将得出新的概率电压和损耗敏感性指标，这些指标可以快速计算，并随着网络的规模而扩展。概率敏感性分析依赖于消费者级别和网络级别的随机抽象，有助于量化不同的渗透水平的活跃消费者对电网性能的平均影响。概率敏感性分析的结果被用来开发一个独特的概念，一个主导的影响。使用主要影响者模型，可以确定网络脆弱性等级，并用于（1）量化网络对各种网络/物理攻击点的敏感性，以及（2）为DSO开发混合控制框架，以部署和管理TE系统内的控制资产。随机几何框架还能够快速识别可以加速潮流计算的无效电压约束。总之，该项目提供了工具，使配电系统运营商能够有效地规划和运营分布式可再生能源资源、电动汽车和消费者大量渗透的配电系统。这些工具将允许对系统进行真正的技术经济分析，同时考虑消费者的偏好。本研究的结果将：（1）整合到几个本科生和研究生课程中，（2）通过学术会议和期刊上的出版物传播。PI将通过开放日展示和K-12学生实地考察来教育公众，鼓励来自代表性不足群体的学生追求STEM职业。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

A novel framework for hosting capacity analysis with spatio-temporal probabilistic voltage sensitivity analysis

一种基于时空概率电压灵敏度分析的托管容量分析新框架

• 发表时间: 2022
• 期刊: International journal of electrical power energy systems
• 作者: Sai Munikoti, Mohammad Abujubbeh

Voltage Violation Prediction in Unobservable Distribution Systems

不可观测配电系统中的电压违规预测

• DOI: 10.1109/pesgm48719.2022.9916805
• 发表时间: 2022
• 期刊: 2022 IEEE Power & Energy Society General Meeting (PESGM
• 作者: Abujubbeh, Mohammad;Dahale, Shweta;Natarajan, Balasubramaniam
• 通讯作者: Natarajan, Balasubramaniam

Overview of Loss Sensitivity Analysis in Modern Distribution Systems

• DOI: 10.1109/access.2022.3149481
• 发表时间: 2022
• 期刊: IEEE Access
• 影响因子: 3.9
• 作者: Mohammad Abujubbeh;B. Natarajan

An Information Theoretic approach to identify Dominant Voltage Influencers for Unbalanced Distribution Systems

识别不平衡配电系统主要电压影响因素的信息论方法

• DOI: 10.1109/tpwrs.2022.3149144
• 发表时间: 2022
• 期刊: IEEE Transactions on Power Systems
• 影响因子: 6.6
• 作者: Munikoti, Sai;Abujubbeh, Mohammad;Jhala, Kumar;Natarajan, Bala
• 通讯作者: Natarajan, Bala

Analytical Power Loss Sensitivity Analysis in Distribution Systems

配电系统中的分析型功率损耗敏感性分析

• DOI: 10.1109/pesgm46819.2021.9637980
• 发表时间: 2021
• 期刊: 2021 IEEE Power & Energy Society General Meeting (PESGM
• 作者: Abujubbeh, Mohammad;Munikoti, Sai;Natarajan, Balasubramaniam
• 通讯作者: Natarajan, Balasubramaniam