Repair and Resource Scheduling in Unbalanced Distribution Systems using Neighborhood Search

TL;DR

This paper introduces a mixed-integer linear programming model and a neighborhood search algorithm to optimize repair and resource scheduling in unbalanced distribution systems during outages, enhancing restoration efficiency.

Contribution

It develops a comprehensive MILP model integrating damage isolation, network reconfiguration, and resource logistics, along with a neighborhood search algorithm for improved solution quality.

Findings

Validated on IEEE test systems showing effective restoration strategies.

Demonstrated improved solution quality with the neighborhood search method.

Integrated PV systems into the restoration process.

Abstract

This paper proposes an optimization strategy to assist utility operators to recover power distribution systems after large outages. Specifically, a mixed-integer linear programming (MILP) model is developed for co-optimizing crews, resources, and network operations. The MILP model coordinates damage isolation, network reconfiguration, distributed generator re-dispatch, and crew/resource logistics. In addition, a framework for integrating different types of photovoltaic (PV) systems in the restoration process is developed.} We consider two different types of crews, namely, line crews for damage repair and tree crews for obstacle removal. We also model the repair resource logistic constraints. Furthermore, a new algorithm is developed for solving the distribution system repair and restoration problem (DSRRP). The algorithm starts by solving DSRRP using an assignment-based method, then a neighborhood search method is designed to iteratively improve the solution. The proposed method is validated on modified IEEE 123- and 8500-bus distribution test systems.