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Adaptive Day-Ahead Prediction of Resilient Power Distribution Network Partitions

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posted on 07.01.2021, 05:00 by Chinmay Shah, Richard Wies
The conventional power distribution network is being transformed drastically due to high penetration of renewable energy sources (RES) and energy storage. The optimal scheduling and dispatch is important to better harness the energy from intermittent RES. Traditional centralized optimization techniques limit the size of the problem and hence distributed techniques are adopted. The distributed optimization technique partitions the power distribution network into sub-networks which solves the local sub problem and exchanges information with the neighboring sub-networks for the global update. This paper presents an adaptive spectral graph partitioning algorithm based on vertex migration while maintaining computational load balanced for synchronization, active power balance and sub-network resiliency. The parameters that define the resiliency metrics of power distribution networks are discussed and leveraged for better operation of sub-networks in grid connected mode as well as islanded mode. The adaptive partition of the IEEE 123-bus network into resilient sub-networks is demonstrated in this paper.

Funding

This work was supported in part by the U.S. Department of Energy with the Battelle Memorial Institute under Contract DEAC05-76RL01830 and under a subcontract Contract No. 474633 from Pacific Northwest National Laboratories to the University of Alaska Fairbanks.

History

Email Address of Submitting Author

cshah@alaska.edu

ORCID of Submitting Author

https://orcid.org/0000-0001-7697-6681

Submitting Author's Institution

University of Alaska Fairbanks

Submitting Author's Country

United States of America