Impacts of High Renewable Power Grids on System Planning and Monitoring

To achieve the goal of a carbon pollution-free electricity sector by 2035 proposed by Biden’s Administration, the U.S. power grids are expecting a dramatic transformation in the resource mix of electricity generation. This dissertation will present related research in several different aspects that will be largely affected by the clean energy transition.

The increasing size and complexity of the bulk power systems have made it more computationally burdensome to simulate the power system in full-size. As an alternative to traditional model-based methods, Chapter 2 proposes a measurement-based model reduction approach using system identification techniques. Chapter 3 presents a parameter fine-tuning procedure based on particle swarm optimization that could improve the accuracy of the coherency-based dynamic equivalents.

As the resource mix evolves, there are growing concerns about the impacts of inverter-based resources (IBRs) on grid reliability and resilience. A projected scenario of Eastern Interconnection (EI) of the year 2025 is developed in Chapter 4 by integrating generation additions and planned retirements. Using the developed model, grid strength assessments are conducted for the Dominion Energy area as a study case in Chapter 5. Grid strength trends are identified and its impacts on system voltages are evaluated from different perspectives. To mitigate the identified weak grid issues, Chapter 6 compares different options of dynamic voltage support and investigates strategic placement of the compensation equipment.

Another challenge brought by the integration of IBRs is the lower inertia in the power system. It is vital to monitor real-time inertia changes in the grid for situational awareness. In Chapter 7, a probing-based inertia estimation approach is proposed and validated in the Kauai island system under different operating conditions. A hardware-in-loop test and a field demonstration will be implemented to validate the proposed approach. For monitoring system transient stability, Chapter 8 proposes a transient stability prediction method using high-order angle dynamics. Conclusions of this dissertation and future work are given in Chapter 9.