Self-Organizing Map-Based Resilience Quantification and Resilient Control of Distribution Systems Under Extreme Events
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
Due to climate change, extreme weather events are occurring more frequently and with increasing impact. This trend poses a significant challenge for distribution system operators (DSO) to ensure that there is uninterrupted power supply to critical loads in their networks. To embed resilience into DSO's decision-making, resilience needs to be first quantified and then integrated into the system-level optimization. Therefore, this paper first develops a novel self-organizing map (SOM) based method (called SomRes) to quantify the time-varying resilience index of a system that can leverage the powerful classification property of SOMs and removes some of the disadvantages of subjective weight assignment methods. Using SomRes, a resilient resource allocation and operational dispatch algorithm is further developed to enhance system resilience against extreme events by considering the SomRes resilience index directly as the feedback. Here, the proposed resilience quantification approach is benchmarked with a state-of-the-art approach and the efficacy of the proposed resilient dispatch algorithm is demonstrated through several deterministic and statistical case studies on the IEEE 123-bus distribution system. Simulation studies show that the proposed SomRes quantification method is an appropriate indicator of system resilience, and the resilient resource allocation and dispatch strategy can significantly reduce critical load shedding under varying event propagation scenarios.
- Research Organization:
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Sponsoring Organization:
- USDOE; National Renewable Energy Laboratory (NREL), Laboratory Directed Research and Development (LDRD) Program
- Grant/Contract Number:
- AC36-08GO28308
- OSTI ID:
- 1847254
- Report Number(s):
- NREL/JA-5D00-82074; MainId:82847; UUID:4d291aab-b5fb-42a7-b68e-ffd0df9de10b; MainAdminID:63893
- Journal Information:
- IEEE Transactions on Smart Grid, Vol. 13, Issue 3; ISSN 1949-3053
- Publisher:
- IEEECopyright Statement
- Country of Publication:
- United States
- Language:
- English
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