CAREER: Hierarchical Robust Stochastic Control for a Flexible and Sustainable Power Supply

这个NSF CAREER项目旨在解决与电力系统灵活性相关的挑战，这是向无碳和弹性电网过渡的关键要求。一个可控的可重构电力系统可以潜在地减少自然灾害的影响和广泛使用的可再生能源（如太阳能和风能）固有的随机性。这一点很重要，因为可再生能源的波动性和极端天气的增加使系统对变化更加敏感，因此更难管理。该项目将为考虑间歇性可再生能源的多层电力系统建模提供一个总体框架，并提供一个强大的调度方案，帮助系统运营商采取适当的行动向客户提供电力，从而带来革命性的变化。这将首先通过引入一种新的协调方法来实现从现有电网向更灵活的电网的过渡，其次通过开发基于模型的监督算法来实现。该项目的智力优势包括为现代化电网的能源管理提供了一个基本框架，该框架灵活、可重构、清洁且具有弹性。该项目的更广泛影响包括综合努力吸引下一代工程师进入电力和能源领域，并提高当地服务不足社区对可再生能源的影响和利用的认识。在提出的研究中，将开发一系列新的控制策略，不仅为电网提供操作灵活性，而且允许管理和稳定电源。微电网是这一框架的基石。多级控制算法是基于一个包含网络约束的多层随机模型。所提出的控制策略具有以下关键属性：i)在微电网将根据需要与微电网网络连接和断开的意义上是分层的；Ii)它是稳健的，因为它将稳定性优先于最优性，iii)它是随机的，以解决可再生能源的间歇性特征。网络约束将通过基于线性矩阵不等式的设计来解决。结果将在循环中的实时硬件中进行验证。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This NSF CAREER project aims to address challenges associated with power system flexibility which is a key requirement for transitioning to a carbon free and resilient electric grid. A controllable reconfigurable power system can potentially reduce the impact of natural disasters and inherent randomness of widely used renewable energy sources such as solar and wind. This is important because volatility of renewable energies and increase occurrence of extreme weather makes the system significantly more sensitive to changes and therefore, harder to manage. The project will bring transformative change by providing a general framework to model a multi-layer power system that takes into account intermittent renewable energy sources and a robust scheduling scheme that will help system operators to take the appropriate action for delivering power to customers. This will be achieved first by introducing a new coordinated approach for transitioning from the existing grid to a more agile one, and second by developing a model based supervisory algorithm. The intellectual merits of the project include a fundamental framework for the energy management of a modernized electric grid that is agile, reconfigurable, clean and resilient. The broader impacts of the project include an integrated effort attracting the next generation of engineers to the field of power and energy and increase awareness to the local underserved communities on the impact and utilization of renewable energies. During the proposed research, a series of novel control strategies will be developed that not only provide operational flexibility to the grid but also allow management and stabilization of the power supply. Microgrids are the building blocks of this framework. The multi-level control algorithm is based on a multi-layer stochastic model that incorporates network constraints. The proposed control strategies have the following key attributes: i) it is hierarchical in a sense that microgrids will connect and disconnect from a network of microgrids as needed; ii) it is robust since it will prioritize stability over optimality and, iii) it is stochastic to address the intermittent character of renewable energies. The network constraints will be addressed by using linear matrix inequalities based design. The results will be validated in real-time hardware in the loop.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.