@inproceedings{70e9a5813b5441f9a8a8ed44d5dd2aa2,
title = "An Extended Model for Ecological Robustness to Capture Power System Resilience",
abstract = "The long-term resilient property of ecosystems has been quantified as ecological robustness (RECO) in terms of the energy transfer over food webs. The RECO of resilient ecosystems favors a balance of food webs' network efficiency and redundancy. By integrating RECO with power system constraints, the authors are able to optimize power systems' inherent resilience as ecosystems through network design and system operation. A previous model used on real power flows and aggregated redundant components for a rigorous mapping between ecosystems and power systems. However, the reactive power flows also determine power systems resilience; and the power components' redundancy is part of the global network redundancy. These characteristics should be considered for RECO-oriented evaluation and optimization for power systems. Thus, this paper extends the model for quantifying RECO in power systems using real, reactive, and apparent power flows with the consideration of redundant placement of generators. Recalling the performance of RECO-oriented optimal power flows under N-x contingencies, the analyses suggest reactive power flows and redundant components should be included for RECO to capture power systems' inherent resilience.",
keywords = "Biological System Modeling, Ecosystems, Power System Resilience, Resilience",
author = "Hao Huang and Davis, {Katherine R.} and Poor, {H. Vincent}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE Power and Energy Society General Meeting, PESGM 2023 ; Conference date: 16-07-2023 Through 20-07-2023",
year = "2023",
doi = "10.1109/PESGM52003.2023.10253322",
language = "English (US)",
series = "IEEE Power and Energy Society General Meeting",
publisher = "IEEE Computer Society",
booktitle = "2023 IEEE Power and Energy Society General Meeting, PESGM 2023",
address = "United States",
}