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

CRISP项目解决了电网向高度分布式基础设施快速发展所带来的挑战。这项研究的重点是配电馈线的转型，从相对被动的向客户输送电力的渠道，到配电微电网，即积极管理当地生产、储存和使用电力的实体，并有个人客户的参与。分布式微电网将传统电网的优势与新兴分布式技术的优势结合起来，包括在电网中断的情况下在当地生产和使用电力的能力。该项目将形成一个统一的模型，将发电和输送、信息流、市场设计和人类行为的关键方面结合起来。该模型的预测可以被决策者用来指导通过分配微电网向清洁能源的过渡。目标是使至少50%的电力来自可再生资源。传统电网无法做到这一点，因为它容纳间歇性可再生能源的能力有限，或者完全分散的方法，这对大多数公用事业客户来说都是负担不起的。该项目解决了从研究发现转化为商业应用所必需的许多社会技术差距。到目前为止，还没有理论框架来确保系统的稳定性，因为通过电力电子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整形功率流控制理论。我们将研究检测恶意篡改信息流的方法。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行为模型提供，其中包括通过调查、面谈和计量数据获得的信息。紧急系统动力学将抽象和研究使用动态复杂网络理论，以探索稳定性极限作为人类行为和市场设计的功能。最后，利用相互依存的马尔可夫链模型分析配电系统可控性增强对大型能源-信息-社会网络鲁棒性的影响。参与该计划的研究生将接触到工程，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。

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.