A Multi-Agent-Based Rolling Optimization Method for Restoration Scheduling of Electrical Distribution Systems with Distributed Generation

TL;DR

This paper introduces a multi-agent rolling optimization approach for electrical distribution system restoration that enhances resilience and adaptability during blackouts, especially under communication failures.

Contribution

It presents a decentralized, multi-time interval optimization model with a rolling process for EDS restoration, addressing communication failures and cyber-attacks.

Findings

Effective restoration scheduling demonstrated on IEEE 123-bus system.

Decentralized decision-making improves resilience and adaptability.

Rolling optimization updates schedules automatically during restoration.

Abstract

Resilience against major disasters is the most essential characteristic of future electrical distribution systems (EDS). A multi-agent-based rolling optimization method for EDS restoration scheduling is proposed in this paper. When a blackout occurs, considering the risk of losing the centralized authority due to the failure of the common core communication network, the agents available after disasters or cyber-attacks identify the communication-connected parts (CCPs) in the EDS with distributed communication. A multi-time interval optimization model is formulated and solved by the agents for the restoration scheduling of a CCP. A rolling optimization process for the entire EDS restoration is proposed. During the scheduling/rescheduling in the rolling process, the CCPs in the EDS are reidentified and the restoration schedules for the CCPs are updated. Through decentralized decision-making and rolling optimization, EDS restoration scheduling can automatically start and periodically update itself, providing effective solutions for EDS restoration scheduling in a blackout event. A modified IEEE 123-bus EDS is utilized to demonstrate the effectiveness of the proposed method.