Collaborative Research: CRISP Type 2: Revolution through Evolution: A Controls Approach to Improve How Society Interacts with Electricity

合作研究：CRISP 类型 2：通过进化进行革命：改善社会与电力互动方式的控制方法

• 批准号: 1541148
• 负责人: Francesco Sorrentino
• 金额: $ 140.99万
• 依托单位: University of New Mexico
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-15 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1541148&HistoricalAwards=false
• 关键词: Collaborative; Research; CRISP; Type; Revolution

This CRISP project addresses the challenges associated with the rapid evolution of the electricity grid to a highly distributed infrastructure. The keystone of this research is the transformation of power distribution feeders, from relatively passive channels for delivering electricity to customers, to distribution microgrids, entities that actively manage local production, storage and use of electricity, with participation from individual customers. Distribution microgrids combine the advantages of the traditional electricity grid with the advantages of emerging distributed technologies, including the ability to produce and use power locally in the event of grid outages. The project will result in a unified model that incorporates key aspects of power generation and delivery, information flow, market design and human behavior. The model predictions can be used by policymakers to guide a transition to clean energy via distribution microgrids. The expectation is to enable at least 50% of electric power to come from renewable resources. This cannot be done with either the traditional grid, due to its limited capacity to accommodate intermittent renewable power sources, or with fully decentralized approaches, which would not be affordable for most utility customers.This project addresses many socio-technological gaps necessary to translate from research discovery to commercial applications. To date, there is no theoretical framework to ensure system stability as renewable energy routed through power electronics replaces traditional rotating machinery. To achieve an optimal mix of storage performance and information bandwidth and to design nonlinear controllers, we will use Hamiltonian Surface Shaping Power Flow Control theory. We will study methods to detect malicious tampering with information flows. The complex interaction of intermittent resources, human behavior and market structures will be modeled in an agent-based simulation. System inputs will be provided by utility and meteorological data, and by behavioral models that incorporate information obtained by surveys, interviews and metering data. Emergent system dynamics will be abstracted and studied using dynamical complex network theory, to explore stability limits as a function of human behavior and market design. Finally, the effect of enhanced controllability of distribution systems on the robustness of large energy-information-social networks will be analyzed using interdependent Markov-chain models. Graduate students involved in this program will be exposed to a unique combination of skills from engineering, data analysis and social sciences; such cross-disciplinary training will prepare them for leadership roles in the emerging energy economy of tomorrow.

这个清晰的项目解决了与电网快速演变为高度分布式基础设施相关的挑战。这项研究的重点是将配电馈线从相对被动的向客户输送电力的渠道转变为配电微电网，即在个人客户的参与下积极管理当地电力生产、储存和使用的实体。配电微网结合了传统电网的优势和新兴分布式技术的优势，包括在电网中断时在当地生产和使用电力的能力。该项目将产生一个统一的模型，其中包括发电和交付、信息流、市场设计和人类行为等关键方面。模型预测可以被政策制定者用来通过配电微电网来指导向清洁能源的过渡。他们的期望是使至少50%的电力来自可再生资源。由于传统电网容纳间歇性可再生能源的能力有限，传统电网无法做到这一点，而完全分散的方法对大多数公用事业客户来说是负担不起的。该项目解决了从研究发现转化为商业应用所需的许多社会技术差距。到目前为止，还没有确保系统稳定性的理论框架，因为通过电力电子设备传输的可再生能源取代了传统的旋转机械。为了实现存储性能和信息带宽的最佳组合，并设计非线性控制器，我们将使用哈密顿曲面成形潮流控制理论。我们将研究检测对信息流进行恶意篡改的方法。间歇性资源、人类行为和市场结构的复杂相互作用将在基于代理的模拟中建模。系统输入将由公用事业和气象数据以及纳入调查、访谈和计量数据获得的信息的行为模型提供。我们将利用动态复杂网络理论对紧急系统动力学进行抽象和研究，以探索作为人类行为和市场设计函数的稳定性极限。最后，利用相互依赖的马尔可夫链模型分析了配电系统的可控性增强对大型能量-信息-社会网络的稳健性的影响。参与该项目的研究生将接触到来自工程、数据分析和社会科学的独特技能组合；这种跨学科培训将为他们在未来新兴能源经济中担任领导角色做好准备。