Data-centric Real-time Power System Modelling, Monitoring, and Control

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This research program will develop and integrate a comprehensive suite of data-centric applications aimed at achieving real-time modelling, monitoring, and control of the future power system. Traditionally, the bulk transmission system ensures power availability and quality via repeated offline what-if scenario-based simulation studies and hierarchical online operational practices. This model-centric and hierarchical status quo performs well in the traditional power system with high predictability and low uncertainty. However, the future power system is expected to reliably supply electricity in the face of (i) more uncertainty arising from renewable electric power generation, and (ii) added system stress due to growing electricity demand, both of which lead to uncertain and unpredictable behaviour, potentially causing widespread blackouts. Confronted with these circumstances that may render an a priori model (obtained based on historical data, maintenance records, and telemetry) grossly inaccurate, traditional model-centric tools may no longer be sufficient to maintain system-wide reliability and efficiency. Thus, there exists an impetus to develop transformative power system monitoring, operation, and control practices that are adaptive to (potentially rapid) changes in operating point and network topology, resilient against model error, and computationally tractable. A compelling strategy to address this goal is to develop a data-centric framework that is enabled by real-time measurements obtained from the system. To this end, the proposed program realizes its long-term vision in three cohesive themes: (i) estimating reduced-order network and dynamic models, (ii) developing transient stability monitoring tools, and (iii) unifying network optimization with real-time control. The proposed research program will generate tools that are absolutely essential, in Canada and beyond, to enable widespread integration of renewable resources, accommodate much higher electricity demand, and simultaneously prevent severe system-wide failures. Furthermore, through this program, graduate and undergraduate students will be equipped with (i) the knowledge and skills required to conduct first-class research in power systems, and (ii) the ability to implement functional and efficient algorithms for large-scale power systems.