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DOI:10.35833/MPCE.2022.000436
Decentralized Bilateral Risk-based Self-healing Strategy for Power Distribution Network with Potentials from Central Energy Stations
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Author: Chaoxian Lv1, Rui Liang1, Yuanyuan Chai2

Author Affiliation: 1.School of Electrical Engineering, China University of Mining and Technology, Xuzhou, China
2.School of Electrical Engineering, Hebei University of Technology, Tianjin, China

Foundation:
This work was financially supported by the Fundamental Research Funds for the Central Universities (No. 2021QN1066).
Abstract: Owing to potential regulation capacities from flexible resources in energy coupling, storage, and consumption links, central energy stations (CESs) can provide additional support to power distribution network (PDN) in case of power disruption. However, existing research has not explicitly revealed the emergency response of PDN with leveraging multiple CESs. This paper proposes a decentralized self-healing strategy of PDN to minimize the entire load loss, in which multi-area CESs’ potentials including thermal storage and building thermal inertia, as well as the flexible topology of PDN, are reasonably exploited for service recovery. For sake of privacy preservation, the co-optimization of PDN and CESs is realized in a decentralized manner using adaptive alternating direction method of multipliers (ADMM). Furtherly, bilateral risk management with conditional value-at-risk (CVaR) for PDN and risk constraints for CESs is integrated to deal with uncertainties from outage duration. Case studies are conducted on a modified IEEE 33-bus PDN with multiple CESs. Numerical results illustrate that the proposed strategy can fully utilize the potentials of multi-area CESs for coordinated load restoration. The effectiveness of the performance and behaviors’ adaptation against random risks is also validated.

Keywords:
Power distribution network (PDN) ; central energy station (CES) ; bilateral risk management ; self-healing ; alternating direction method of multipliers (ADMM).
Received:July 21, 2022               Online Time:2023/01/28
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