# distribution system reconfiguration using a modified tabu search algorithm

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Electric Power Systems Research 80 (2010) 943953

Contents lists available at ScienceDirect

Electric Power Systems Research

journa l homepage: www.e lsev ier .co

Distrib od

A.Y. Abde rElectrical Powe Street

a r t i c l

Article history:Received 31 MReceived in reAccepted 3 JanAvailable onlin

Keywords:Distribution syPower loss redModied Tabu

a-heuis u

urning a td in tod isn quverifynd coned rein th

1. Introdu

The subgained a great deal of attention due to the high cost of electri-cal energy and therefore, much of current research on distributionautomation has focused on the minimum-loss conguration prob-lem. There are many alternatives available for reducing losses atthe distribution level: reconguration, capacitor installation, loadbalancing, afocuses on t

Networkogy of distof switchesbinations ina complicatmization pdistributionalizing swittwo types oguration machieved bysuch a way

The recomethods thand optimi

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(A.Y. Abdelaziz

ose uherschni

the problem to retain a certain degree of accuracy, while assuringconvergence and an acceptable solution time.

In Ref. [1], a branch exchangemethod that considered the onoffconditions of the sectionalizing switches in discrete numbers wasdeveloped [1]. Since themethod is based on heuristics, it is not easy

0378-7796/$ doi:10.1016/j.nd introduction of higher voltage levels. This researchhe reconguration alternative.reconguration is the process of changing the topol-

ribution systems by altering the open/closed status. Because there are many candidate-switching com-the distribution system, network reconguration is

ed combinatorial, non-differentiable constrained opti-roblem. Two types of switches are used in primarysystems. There are normally closed switches (section-ches) and normally open switches (tie switches). Thosef switches are designed for both protection and con-anagement. The change in network conguration isopening or closing of these two types of switches in

that the radiality of the network is maintained.nguration algorithms can be classied by the solutionat they employ: those based upon a blend of heuristicszation methods, those making use of heuristics alone,

ding author. Tel.: +20 101372930.dresses: almoatazabdelaziz@hotmail.com, ayabdelaziz@gawab.com).

to take a systematic way to evaluate an optimal solution.Two different methods with varying degree of accuracy to

approximate power ow in systems were proposed in Ref. [2]. Thesearchmethod has an acceptable convergence characteristic. How-ever, it can get stuck in local minimum. The method is very timeconsuming due to the complicated combinations in large-scale sys-tems.

An expert system for feeder reconguration, based upon exten-sions of the rules of Ref. [1] was presented in Ref. [3], with thepotential of handling realistic operating constrains. The approachtaken is set up a decision tree to represent the various switch-ing operations available. This strategy is efcient for trees that arenot too large. However, as a search tree becomes larger, a greatamount of time can be spent searching for the optimal solution. Toguarantee an optimal solution an exhaustive tree search should beused.

A linear programming method using transportation techniquesand a new heuristic searchmethod for comparisonwith previouslydeveloped heuristic techniques which are based on an optimalload ow analysis were presented in Ref. [4]. This study indicatesthat linear programming, in the form of transportation algorithms,is not suitable for application to feeder reconguration since the

see front matter 2010 Elsevier B.V. All rights reserved.epsr.2010.01.001ution system reconguration using a m

laziz , F.M. Mohamed, S.F. Mekhamer, M.A.L. Badr and Machines Department, Faculty of Engineering, Ain Shams University, 1 Elsarayat

e i n f o

arch 2008vised form 30 October 2009uary 2010e 20 January 2010

stem recongurationuctionSearch

a b s t r a c t

This article presents an efcient metmodied Tabu Search (MTS) algorithmlosses are globally minimized with twith some modications such as usina random multiplicative move is useregions. The Kirchhoff algebraic methfeature of the MTS method is that it canetwork reconguration problem. Tovariation is taken into consideration arather encouraging results. The obtaithat obtained using other approaches

ction

ject of minimizing distribution systems losses has

and thresearction tem/locate /epsr

ied Tabu Search algorithm

, Abdo Basha Square Abbassia, Cairo, Egypt

ristic method for reconguration of distribution systems. Ased to recongure distribution systems so that active powerg on/off sectionalizing switches. TS algorithm is introducedabu list with variable size according to the system size. Also,he search process to diversify the search toward unexploredadopted to check the radial topology of the system. A salientickly provide a global optimal or near-optimal solution to thethe effectiveness of the proposed approach, the effect of loadmparative studies are conducted on three test systems withsults, using the proposed MTS approach, are compared withe previous work.

2010 Elsevier B.V. All rights reserved.

sing some from of articial intelligence (AI). Numerousadvocate the use of a blend of heuristics and optimiza-

ques. The blend of the two types of technique permits

944 A.Y. Abdelaziz et al. / Electric Power Systems Research 80 (2010) 943953

power loss function is not linear whilst heuristic approaches,although not optimal, can provide substantial saving if properlyformulated.

Based on partitioning the distribution network into groups ofload buses,minimizedbusses, theovercome, w

In recensolving commal solutioinclude SimTabu Search

A two-slated anneaof distributied SA tecin distribution schemstarting temproposed. Tusing the mgives a neawell in the

A GA basRef. [8]. Strconsistingage drop liresults demobtained, so

An artiuration waencounterincreased ccertain objeclass of solu

A paralleuration hasschemes. Oallel procesmultiplicityPTS algorithallel Simula(PGA). InRerecongurative line losA method fexpression,restorativeefcienthybration to imwas proposalgorithm foposed. Thesuch as usinto escape frmovewas utoward une

Zhang ealgorithm ftribution syoperator usdependencethe candidaswitch exchdesigned to

Fig. 1. 16-Node distribution system.

t of computing time. The ITS algorithm in Ref. [14] wasto the 119-node system and gave an optimal solution.

his article, an enlarged version of Ref. [13] is introduced tohe reconguration problem. The proposedmethod is appliede-scale networks to show the effectiveness of the modiedearch algorithm. In comparison with Ref. [14] in which theon operation of GA is used to weaken the dependence ofsearch ability on tabu length, on the other side, we use aic tabu list with variable size according to the system sizeultiplicativemove is applied to diversify the search processprove the local search efciency of Tabu Search to reach thesolution. Also, the effect of variation of load is taken into con-ion to show the capability of the proposed algorithm (MTS)k at different load levels.verify the effectiveness of the proposed method, compar-tudies are conducted on three test systems with ratheraging results. The proposed method is applied to a 16-node, a 69-node system, and a 119-node system. The results,ed using the proposed MTS approach, are compared with

Fig. 2. Flow chart of Tabu Search algorithm.the line section losses between the groups of nodes are[5]. By dividing the distribution network into groups ofcombinatorial nature of the reconguration problem ishile simultaneously minimizing losses.

t years, meta-heuristic methods have been studied forbinatorial optimization problems to obtain an opti-

n of global minimum. Typical meta-heuristic methodsulated Annealing (SA), Genetic Algorithm (GA), and(TS).

tage solution methodology based on a modied simu-ling technique for solving the reconguration problemion systems was proposed in Ref. [6]. In Ref. [7], a mod-hnique for network reconguration for loss reductiontion systems was presented. An efcient perturba-e and an initialization procedure determining a betterperature for the simulated annealing approach werehis method can get a solution better than that obtainedethod presented in Ref. [5]. This solution algorithm

r-optimal solution but this method does not work socase of load variation.ed method for feeder reconguration was proposed inings which represent switch status, a tness functionof total system losses, and penalty values of volt-mit and current capacity limit were formed. Sampleonstrate that, although theminimal loss solutionswerelution time was prohibitive.cial neural network based method for feeder recong-s presented in Ref. [9]. However, such technique candifculties, such as getting trapped in local minima,omputational complexity, and not being applicable toctive functions. This led to theneedof developing anewtion methods that can overcome these shortcomings.l Tabu Search (PTS) based method for feeder recong-been proposed in Ref. [10]. PTS introduces two parallelne is the decomposition of the neighborhood with par-sors to reduce computational efforts. The other is theof the tabu length to improve the solution accuracy.m gives results better than results obtained by SA, par-tedAnnealing (PSA), GA, andparallel Genetic Algorithmf. [11], aTSalgorithmfor solving theproblemofnetworktion in distribution systems in order to reduce the resis-ses under normal operating conditions was presented.or checking system radiality based on an upward-nodewhich has been developed in solving the problem ofplanning of power systemwas proposed. In Ref. [12], anrid algor

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