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

职业：用于灵活和可持续电源的分层鲁棒随机控制

• 批准号: 2236843
• 负责人: Maryam Khanbaghi
• 金额: $ 51.7万
• 依托单位: Santa Clara University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2028-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2236843&HistoricalAwards=false
• 关键词: CAREER; Hierarchical; Robust; Stochastic; Control

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.

这个NSF职业项目旨在解决与电力系统灵活性相关的挑战，这是过渡到无碳且弹性的电网的关键要求。可控的可控功率系统可以潜在地减少自然灾害的影响，并可以降低广泛使用的可再生能源（例如太阳能和风能）的固有随机性。这很重要，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。该项目将通过提供一个通用框架来建模多层电力系统，从而考虑到间歇性可再生能源和强大的调度方案，从而帮助系统操作员采取适当的措施，从而为客户采取适当的措施。这将首先通过引入一种新的协调方法来从现有网格过渡到更敏捷的方法，其次是通过开发基于模型的监督算法来实现的。该项目的智力优点包括一个基本框架，用于敏捷，可重构，清洁和弹性的现代电网的能源管理。该项目的更广泛的影响包括一项综合努力，吸引下一代工程师进入权力和能源领域，并提高对当地服务不足社区对可再生能源的影响和利用的认识。在拟议的研究中，将开发一系列新颖的控制策略，不仅为电网提供了操作灵活性，还可以管理和稳定电源。微电网是该框架的基础。多层控制算法基于包含网络约束的多层随机模型。提出的控制策略具有以下关键属性：i）在某种意义上，微电网将根据需要连接并与微电网网络连接； ii）它是鲁棒的，因为它将优先考虑稳定性而不是最优性，iii）随机解决可再生能量的间歇性。网络约束将通过使用基于线性矩阵不等式的设计来解决。 该奖项将在循环中的实时硬件中进行验证。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的智力优点和更广泛影响的评论标准来评估值得支持的。