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Article . 2024 . Peer-reviewed
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IEEE Transactions on Power Systems
Article . 2024 . Peer-reviewed
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Optimal Switch and Tie Line Planning in Distribution Networks: Benchmarking a Practical MILP Model with a Fast Heuristic Approach

Authors: Mohammad Jooshaki; Sahand Karimi-Arpanahi; R. John Millar; Jaakko Anttila; Matti Lehtonen; Mahmud Fotuhi-Firuzabad;

Optimal Switch and Tie Line Planning in Distribution Networks: Benchmarking a Practical MILP Model with a Fast Heuristic Approach

Abstract

Publisher Copyright: © 1969-2012 IEEE. Optimal placement of switches and tie lines is an integral task in distribution system planning. Owing to the problem complexity and the presence of binary decision variables, using heuristic methods for obtaining a close to optimal switch and tie line plan is a common practice in industry. Efforts to employ mixed-integer linear programming (MILP) to guarantee the solution optimality also tend to sacrifice the modeling accuracy through oversimplifying assumptions to make the problem tractable. Aiming to tackle these challenges, we present an efficient, yet accurate, MILP model for optimal switch and tie line planning. The proposed model avoids common simplifying assumptions in the state-of-the-art MILP models while preserving the solving efficiency. In order to demonstrate the applicability and scalability of the proposed MILP approach, it is applied to multiple test networks, and the results are compared with those of a fast heuristic model. The outcomes not only represent the high efficiency and accuracy of the MILP model but also validate the close to optimality of the heuristic approach developed for practical applications as a module in a commercial distribution system planning toolbox. Peer reviewed

Country
Finland
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Keywords

switch planning, Electricity distribution system, mixed-integer linear programming, tie line, optimization

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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