Reconfiguration of distribution system using a binary programming model

Md Mashud Hyder; Kaushik Mahata; Md Mashud Hyder; Kaushik Mahata

doi:10.3934/energy.2016.3.461

AIMS Energy

2016, Volume 4, Issue 3: 461-480. doi: 10.3934/energy.2016.3.461

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Research article Topical Sections

Reconfiguration of distribution system using a binary programming model

Md Mashud Hyder ^,,
Kaushik Mahata

Department of Electrical Engineering, University of Newcastle, Callaghan, NSW-2308, Australia.

Received: 11 December 2015 Accepted: 23 March 2016 Published: 30 March 2016

Distribution system reconfiguration aims to choose a switching combination of branches of the system that optimize certain performance criteria of power supply while maintaining some specified constraints. The ability to automatically reconfigure the network quickly and reliably is a key requirement of self-healing networks which is an important part of the future Smart Grid system. We present a unified mathematical framework, which allows us to consider different objectives of distribution system reconfiguration problems in a flexible manner, and investigate its performance. The resulting optimization problem is in quadratic form which can be solved efficiently by using a quadratic mixed integer programming (QMIP) solver. The proposed method has been applied for reconfiguring different standard test distribution systems.
- Radial distribution networks,
- reconfiguration,
- integer programming
Citation: Md Mashud Hyder, Kaushik Mahata. Reconfiguration of distribution system using a binary programming model[J]. AIMS Energy, 2016, 4(3): 461-480. doi: 10.3934/energy.2016.3.461

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Abstract

Distribution system reconfiguration aims to choose a switching combination of branches of the system that optimize certain performance criteria of power supply while maintaining some specified constraints. The ability to automatically reconfigure the network quickly and reliably is a key requirement of self-healing networks which is an important part of the future Smart Grid system. We present a unified mathematical framework, which allows us to consider different objectives of distribution system reconfiguration problems in a flexible manner, and investigate its performance. The resulting optimization problem is in quadratic form which can be solved efficiently by using a quadratic mixed integer programming (QMIP) solver. The proposed method has been applied for reconfiguring different standard test distribution systems.

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