Title: Black-start and Load Restoration Planning Framework for Inverter Dominated Distribution Grids
Abstract: With the broad deployment of distributed energy resources (DERs), it is imperative to enhance distribution system resilience with effective black-start strategies during extended outages of the transmission grid. Although utilities have been employing diesel generators as black-start units, our research is centered on harnessing the potential of inverter-based black-start resources (e.g., grid-forming battery energy storage units) and non-black-start resources (e.g., grid-following PV resources) to facilitate black-start operations and l
oad restoration more efficiently.
We propose a bottom-up black-start and load restoration framework for the distribution grid, where the black-start is initiated by grid-forming inverters deployed across multiple locations, effectively creating numerous isolated microgrids. The framework provides optimal switching sequences to build a cranking path for each microgrid, energizing non-black-start resources and prioritizing the pickup of critical loads. Notably, the distribution network structure evolves at each switching step of the black-start process. Consequently, our framework’s unbalanced power flow is designed to adapt to changes in network structure while maintaining radiality. A significant challenge we address is the limited energy and power capacity inherent in storage-based grid-forming resources. To tackle this, we incorporate synchronizing decisions among microgrids and coordinate with the transmission grid as it becomes available. To validate our approach, we conducted tests using the IEEE 123-node test system, comparing a rule-based synchronizing setting with an optimal synchronizing setting. Our findings demonstrate that the latter approach outperforms the former, particularly when deploying multiple grid-forming inverters.
Bio: Salish Maharjan (Member, IEEE) received a Ph.D. in electrical and computer engineering from the
National University of Singapore in 2020. He is currently a Postdoctoral Research Associate with the
Department of Electrical and Computer Engineering at Iowa State University. He was a visiting student at the Massachusetts Institute of Technology, Cambridge in 2014. He received the Best Paper Award at the 2023 IEEE Power & Energy General Meeting. His interests include distribution system modeling, stability analysis, and optimization and control for techno-economic operation and resilience enhancement.