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

Santa Clara University, Santa Clara CA

Investigators

Abstract

This NSF CAREER project aims to address challenges associated with power system flexibility which is a key requirement for transitioning to a 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, 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 communities on the impact and utilization of energy technologies. 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.