An MILP Model for Optimal Placement of Sectionalizing Switches and Tie Lines in Distribution Networks with Complex Topologies

25Citations
Citations of this article
13Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Sectionalizing switches (SSs) and tie lines play essential roles in reducing the duration of customer interruptions in electricity distribution networks. The effectiveness of such assets is strongly influenced by their placement in the grid. Operation of SSs and tie lines is also inherently interdependent. Due to the structural complexities regarding the mathematical modeling of such dependencies, optimization of the planning and operation of switches and tie lines has typically required either leveraging heuristic and metaheuristic approaches or oversimplifying the network topology. To tackle such issues, this paper presents a computationally-efficient model for reliability-oriented concurrent switch and tie line placement in distribution networks with complex topologies. The proposed model can be applied to grids with several tie lines and laterals per feeder, and yields the optimal location of tie lines, type of tie switches, namely manual or remote-controlled, and the location and type of SSs. Being cast as a mixed integer linear programming (MILP) problem, the model can be efficiently solved with guaranteed convergence to global optimality using off-the-shelf optimization software. The efficiency and scalability of the proposed model are demonstrated through implementation on five networks and the outcomes are thoroughly discussed.

Cite

CITATION STYLE

APA

Jooshaki, M., Karimi-Arpanahi, S., Lehtonen, M., John Millar, R., & Fotuhi-Firuzabad, M. (2021). An MILP Model for Optimal Placement of Sectionalizing Switches and Tie Lines in Distribution Networks with Complex Topologies. IEEE Transactions on Smart Grid, 12(6), 4740–4751. https://doi.org/10.1109/TSG.2021.3092405

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free