Date of Award
Doctor of Philosophy (PhD)
Electrical and Computer Engineering
The grid is evolving rapidly to meet the requirements of the clean energy transition. This evolution involves an increasing penetration of renewable energy resources and new complexities with a larger number of devices and controls spread across transmission and distribution networks. The boundary between transmission and distribution becomes blur. Consequently, we face significant challenges in managing the fundamental shift in power system physics. The ubiquitous use of Inverter Based Resources (IBRs) throughout the transmission and distribution systems has made it more difficult for the grid to maintain grid stability under dynamic conditions. Therefore, there is a strong need to explore how IBRs will change the dynamic behavior of the grid and examine how IBRs could be utilized to enhance the operation and control of power systems under various operating conditions and system events.
To fulfill this pressing need to investigate the influence of IBRs on grid dynamics, the objective of this dissertation is to develop a flexible, scalable transmission and distribution (T&D) co-simulation platform, using open-source tools for assessing the impact of grid-following (GFL) and grid-forming (GFM) IBRs on dynamic stability at various renewable penetration levels (up to 100%). This platform enables researchers to explore different contingencies, faults at transmission, distribution, or both, providing a comprehensive evaluation of grid status. A series of case studies, including both small and large T&D systems with varying GFL/GFM configurations and contingencies, have been conducted. The results not only robustly validate our co-simulation platform, but also provide invaluable insights for effective IBR management in the power grid.
The dissertation starts with addressing the trends of the power system with the goal of clean energy and decarbonization, along with discussing the challenges introduced by IBR to the dynamics and stability of the power system in Chapter 1. Chapter 2 describes the literature review on T&D co-simulation, summarizes their limitations, and identifies the opportunities for the enhancement of T&D co-simulation. Chapter 3 introduces the foundational elements of this platform, comprising three open source tools, GridPACK, GridLAB-D, and HELICS, and dynamic models of GFL and GFM. A series of comprehensive case studies on an approximately 100-bus small-scale system are then presented in Chapter 4, including various GFL/GFM ratios within both T&D systems, a range of IBR penetration levels, and contingencies occurring on either T or D sides. The validation of co-simulation is shown at the beginning of Chapter 4 to layout a foundation for this research. Chapter 5 further demonstrates the capability of this platform with a large T&D system involving more than 10,000 IBRs, serve to validate the developed co-simulation platform and provide insightful observations for effective IBR management. The parallelization capabilities of this co-simulation platform is illustrated in Chapter 6 as an enhanced and crucial feature for improving computational efficiency. The dissertation concludes in Chapter 7 with a summary of the research undertaken, the discussion on the findings, and suggestions and recommendations for future research in this domain.
Chen, Yousu, "A Scalable Transmission and Distribution Co-simulation Platform for IBR-Heavy Power Systems" (2023). All Dissertations. 3528.