Enabling Electric Distribution System Resiliency through Metrics-driven Black Start Restoration

• Published in: 2021 IEEE Industry Applications Society Annual Meeting (IAS) pp. 1 - 8
• Main Authors: Kandaperumal, Gowtham, Pandey, Shikhar, Srivastava, Anurag K.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 10.10.2021
• Subjects: Black start restoration; Clustering algorithms; Cranking path; Distribution system resiliency; Islanded operation; Measurement; Microgrids; Power distribution; Prediction algorithms; Resilience metrics; Robustness; Switches
• ISSN: 2576-702X
• DOI: 10.1109/IAS48185.2021.9677074

The high impact and low probability (HILP) events on the electric distribution system have obligated utility planners to focus on resiliency enabling propositions. Recent trends show that large-scale outages due to damage and impacts to the distribution system resulting from HILP events are rising. When the distribution system sees large-scale blackouts, generation units with black start capability are required to restore out-of-service generation units and subsequently energize the system. However, during the event's progression, the black start process needs to be hardened to ensure the successful restoration of the system and maximize resiliency. This work introduces a resilience metrics-based black start restoration algorithm that determines the most resilient cranking path with the consideration of distribution network topological robustness, event progression, energy resource information, expected damage and impact, cold load pickup, and load priority. We present a framework for the planning and operational decision support in selecting the resultant cranking path and the complete energization of the active electric distribution system. Resiliency metrics consider multiple factors impacting the ability to supply critical loads. The algorithm is validated using the IEEE 123 node system to show the practicality of the proposed approach in enabling system resilience.