Repair and Resource Scheduling in Unbalanced Distribution Systems using Neighborhood Search
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.
Keywords
Cite
@article{arxiv.1808.10548,
title = {Repair and Resource Scheduling in Unbalanced Distribution Systems using Neighborhood Search},
author = {Anmar Arif and Zhaoyu Wang and Jianhui Wang and Chen Chen},
journal= {arXiv preprint arXiv:1808.10548},
year = {2019}
}
Comments
Under review in IEEE Transactions on Smart Grid