EAGER: Fundamentals of Modeling and Control for the Evolving Electric Power System Architectures

EAGER：不断发展的电力系统架构的建模和控制基础知识

基本信息

批准号：
2002570
负责人：
Marija Ilic
金额：
$ 25万
依托单位：
Massachusetts Institute of Technology
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-02-01 至 2023-05-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2002570&HistoricalAwards=false
关键词：
EAGER Fundamentals Modeling Control Evolving

项目摘要

The main objective of this project is to formalize ground-breaking general principles in support of investment planning and operating protocols for the changing electric energy systems. Having this is crucial for assessing effects of candidate hardware and software technologies and for creating an environment in which flexible technologies are utilized by complementing each other’s performance and by jointly meeting the societal needs. Since the performance of many technologies of interest greatly depends on how well they are integrated over time and stakeholders (system modules), an effective framework needs to support decisions that are data-enabled and interactive over time and among different system decision makers. In this project a complex dynamical systems point of view is taken which recognizes such distributed nature of decisions and introduces novel modeling, control and protocol principles in support of system integration in time and space. In sharp contrast with the lack of theoretically-provable performance in the evolving electric power system architectures, this project explores fundamentals and takes major steps toward solving this long-overdue problem. The most important impact will be on the way electric power industry architectures evolve. In particular, the project will catalyze the adoption of data-enabled decision making and automation. Notably, this approach will help educate students to think about emerging electric energy systems as complex dynamical systems for which much innovation is needed and possible. Results of this research will be disseminated through a workshop on design and control of complex energy systems. The next generation Supervisory Control and Data Acquisition (SCADA) can evolve based on protocols defined according to a dynamic monitoring, and decision system (DyMonDS) framework envisioned in this project. Such framework is crucial for assessing effects of candidate hardware and software technologies and for creating an environment in which technologies are integrated and utilized by complementing each other’s performance and by jointly meeting the societal needs. In this project a complex dynamical systems point of view is taken which recognizes such distributed nature of decisions and introduces novel modeling, control and protocol principles in support of temporal and spatial system integration. The main question is how to ensure stability and efficiency of these systems without increasing complexity of information management and consequent implications on cyber-security. Once principles for answering this complex question are formalized, it becomes possible to support selection of “right” technologies and for utilizing them based on data obtained through sensing, communications and control. To establish such principles and not radically change the industry, this project introduces a generalization of today’s Automatic Generation Control by the Balancing Authorities (BAs) which is fundamentally cooperative in nature. The interactions between BAs are managed by each area compensating its own Area Control Error (ACE) which is the net power imbalance contributed by both internal power deviations from schedules and by the tie-line flow deviations into the BA. This is a great example of distributed control through cooperation based on simple protocols of balancing ACE. In this project the ACE is generalized into a notion of an interaction variable (intVar) associated with each intelligent Balancing Authority (iBA). Notably, an intVar has a physical interpretation in terms of power and rate of change of power, but it is not restricted to the assumptions made by the industry today, and it allows for different unconventional architectures, such as small iBAs nested within the existing BAs. iBAs can be components or subsystems of diverse spatial and temporal granularity, and are technology agnostic; their specifications, modeling and interactive multi-layered control are in terms of an intVar common to all. This project targets specifically principles for protocols and enhanced standards for a general DyMonDS framework so that following this framework one can catalyze performance enhancements based on the PI’s recent finding that the intVar dynamics can be interpreted in terms of rates of exergy (potential to perform useful work) and anergy (wasted work).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.

该项目的主要目的是正式化开创性的一般原则，以支持不断变化的电能系统的投资计划和运营协议。拥有此功能对于评估候选硬件和软件技术的影响以及创建一个环境至关重要，在该环境中，通过完成彼此的绩效并共同满足社会需求来利用灵活的技术。由于许多有趣的技术的性能取决于它们随着时间的流逝和利益相关者（系统模块）的整合程度，因此有效的框架需要支持随着时间的推移和不同系统决策者之间的数据支持和互动的决策。在该项目中，采用了复杂的动态系统观点，该观点认识到决策的这种分布性质，并引入了新颖的建模，控制和协议原理，以支持时空集成。与在不断发展的电力系统体系结构中缺乏理论支持的性能形成鲜明对比的是，该项目探索了基本原理，并采取了解决这一长期逾期问题的重要步骤。最重要的影响将是电力行业体系结构的发展方式。特别是，该项目将催化采用支持数据的决策和自动化。值得注意的是，这种方法将有助于教育学生将新兴的电能系统作为复杂的动态系统，以便为其进行大量创新和可能。这项研究的结果将通过有关复杂能源系统的设计和控制的研讨会来传播。下一代监督控制和数据采集（SCADA）可以根据根据动态监控和决策系统（Dymonds）框架定义的协议来发展。此类框架对于评估候选硬件和软件技术的影响以及创建一个通过彼此的绩效并共同满足社会需求来整合和利用技术的环境至关重要。在该项目中，采用了复杂的动态系统观点，该观点认识到决策的这种分布性质，并引入了新颖的建模，控制和协议原理，以支持临时和空间系统集成。主要问题是如何确保这些系统的稳定性和效率，而不会增加信息管理的复杂性以及对网络安全的影响。一旦将回答这个复杂问题的原则正式化，就有可能支持选择“正确”技术的选择，并根据通过感应，通信和控制获得的数据来利用它们。为了建立这样的原则而不是从根本上改变行业，该项目引入了平衡当局（BAS）对当今自动生成控制的概括，这本质上是合作的。 BAS之间的相互作用是通过补偿其自身区域控制错误（ACE）的每个区域来管理的，该错误是由内部权力偏离时间表以及双线流动流入BA所造成的净功率不平衡。这是通过基于平衡ACE的简单协议的合作进行分布式控制的一个很好的例子。在这个项目中，ACE通常被认为是与每个智能平衡权威（IBA）相关的相互作用变量（INTVAR）的概念。值得注意的是，INTVAR在权力和权力变化率方面具有物理解释，但它不仅限于当今行业的假设，并且允许使用不同的非常规架构，例如在现有BAS中嵌套的小IBA。 IBA可以是潜水员空间和临时粒度的组成部分或子系统，并且是技术不可知的。它们的规格，建模和交互式多层控制是所有人共有的INTVAR。 This project targets specifically principles for protocols and enhanced standards for a general DyMonDS framework so that following this framework one can catalyze performance enhancements based on the PI’s recent finding that the intVar dynamics can be interpreted in terms of rates of exercise (potential to perform useful work) and anergy (wasted work).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and更广泛的影响审查标准。