A Novel Scalable Reconfiguration Model for the Postdisaster Network Connectivity of Resilient Power Distribution Systems

Imteaj, Ahmed; Akbari, Vahid; Amini, Mohammad Hadi

Abstract

The resilient operation of power distribution networks requires efficient optimization models to enable situational awareness. One of the pivotal tools to enhance resilience is a network reconfiguration to ensure secure and reliable energy delivery while minimizing the number of disconnected loads in outage conditions. Power outages are caused by natural hazards, e.g., hurricanes, or system malfunction, e.g., line failure due to aging. In this paper, we first propose a distribution-network optimal power flow formulation (DOPF) and define a new resilience evaluation indicator, the demand satisfaction rate (DSR). DSR is the rate of satisfied load demand in the reconfigured network over the load demand satisfied in the DOPF. Then, we propose a novel model to efficiently find the optimal network reconfiguration by deploying sectionalizing switches during line outages that maximize resilience indicators. Moreover, we analyze a multiobjective scenario to maximize the DSR and minimize the number of utilized sectionalizing switches, which provides an efficient reconfiguration model preventing additional costs associated with closing unutilized sectionalizing switches. We tested our model on a virtually generated 33-bus distribution network and a real 234-bus power distribution network, demonstrating how using the sectionalizing switches can increase power accessibility in outage conditions.

Citation

Imteaj, A., Akbari, V., & Amini, M. H. (2023). A Novel Scalable Reconfiguration Model for the Postdisaster Network Connectivity of Resilient Power Distribution Systems. Sensors, 23(3), Article 1200. https://doi.org/10.3390/s23031200

• Journal Article Type: Article
• Acceptance Date: Jan 17, 2023
• Online Publication Date: Jan 20, 2023
• Publication Date: Jan 20, 2023
• Deposit Date: Feb 20, 2023
• Publicly Available Date: Feb 20, 2023
• Journal: Sensors
• Electronic ISSN: 1424-8220
• Publisher: MDPI AG
• Peer Reviewed: Peer Reviewed
• Volume: 23
• Issue: 3
• Article Number: 1200
• DOI: https://doi.org/10.3390/s23031200
• Keywords: Resilience; Optimal power flow; Power distribution network; Network reconfiguration; Electrical and Electronic Engineering; Biochemistry; Instrumentation; Atomic and Molecular Physics, and Optics; Analytical Chemistry
• Public URL: https://nottingham-repository.worktribe.com/output/17637461
• Publisher URL: https://www.mdpi.com/1424-8220/23/3/1200