Electrical Power and Energy Systems 42 (2012) 575–582

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Electrical Power and Energy Systems

journal homepage: www.elsevier .com/locate / i jepes

Fuse cutout allocation in radial distribution system considering the effectof hidden failures

Mojtaba Gilvanejad a,b, Hossein Askarian Abyaneh a,⇑, Kazem Mazlumi c

a Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iranb Substation & Transmission Department, Niroo Research Institute, Tehran, Iranc Department of Electrical Engineering, University of Zanjan, Zanjan, Iran

a r t i c l e i n f o

Article history:Received 23 May 2010Received in revised form 5 April 2012Accepted 20 April 2012

Keywords:Fuse cutoutHidden failureMarkov model

0142-0615/$ - see front matter � 2012 Elsevier Ltd. Ahttp://dx.doi.org/10.1016/j.ijepes.2012.04.029

⇑ Corresponding author. Address: DepartmentAmirkabir University of Technology, Hafez Street,64543300; fax: +98 21 66406469.

E-mail address: askarian@aut.ac.ir (H.A. Abyaneh).

a b s t r a c t

Among the several components of distribution systems, protection devices present a fundamental impor-tance, since they aim at keeping the physical integrity not only of the system equipment, but also of theelectricians team and the population in general. One of the protective devices playing a vital role in over-head distribution lines is fused cutout. At the era of privatized utilities, the protection devices should beallocated and coordinated optimally to reduce capital investments and the system outage costs. Amid thissituation, the mentioned type of the protection device (fuse cutout) has not been studied for economicalallocation up to now. In this paper, responding to this need, an accurate reliability model of fuse cutoutcontaining hidden failures is figured out in the shape of a new Markov model. This model is used for eco-nomical allocation of the fuse cutouts. On the basis of the proposed model, a methodology for economicallocation of fuse cutouts is presented. This methodology involves the worth of energy not supplied (ENS)of the network and makes a balance between the cost of fuse cutout installation and the benefit of ENSdecrease because of the minimizing the faulty zone by using more fuse cutouts. The methodology istested on a sample distribution network as well as on IEEE 6-bus distribution test system (RBTS). More-over, its capability on decision making about the fuse cutout placement and its simplicity for implement-ing on MV overhead lines are displayed.

� 2012 Elsevier Ltd. All rights reserved.

1. Introduction

Protective systems are designed to recognize certain types ofpower system disturbances and to isolate those parts of the systemon which the disturbances occur [1]. These systems play a vital rolein maintaining the high degree of service reliability required inpresent day power systems [2]. In reality, however, protection sys-tems may be exposed to two main failure modes, since they can faileither by not responding when they should or by operating whenthey should not. The reliability of protection relay can be improvedby carrying out routine maintenance or by including built-in mon-itoring and self-checking facilities during the design stages.

In recent years, considerable efforts have been devoted to eval-uate the extent up which these failure modes can affect the powersystem reliability [1–7]. In [2], a Markov model which is used toexamine the effect of routine tests and self-checking intervals onsystem reliability is described. The proposed method has been

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of Electrical Engineering,Tehran, Iran. Tel.: +98 21

further improved in [3] by dividing the Markov model into twomain parts which are devoted to express different situations ofpower component and protective devices. In [4], the effect of relaycoordination methods on reliability indices of an interconnectedpower system has been studied. The authors evaluated the effectof protection failures on the reliability indices using two separateMarkov models, one of them was dedicated to power system com-ponents and the other was considered for protective devices. In [1],a Markov model has been proposed which is capable to considerredundant protection systems.

Most of the aforementioned papers have been based of twomain assumptions. First, the power system has been assumed tobe interconnected. Furthermore, protective relays have been con-sidered as the main protection device to protect such systems[8,9]. However, the mentioned assumptions are of limited rele-vance in case of distribution systems which have usually radial con-figuration with fuse cutouts as the main protective devices. Thisdevice is more economical and, therefore, is favored on a distribu-tion level. The fuse cutouts have some different features comparingto the protection relays which made it special in reliability model-ing. For example, the rate of hidden failures of the fuses is lowerthan the rate of hidden failures of relays. The reason is the differ-ence between the nature of relays and fuses. The relay protection

Fig. 1. Types of fuse cutout usages: (a) at joint point and (b) primary side oftransformer.

576 M. Gilvanejad et al. / Electrical Power and Energy Systems 42 (2012) 575–582

system contains several parts such as transducers (CT1, VT2), circuitbreaker, relay, etc. Each of them has its own failure rate and makesthe total failure rate noticeable [10]. However, the fuse only operatesas a single element which is in series with the other components ofthe circuit. Therefore, only its own failure rate is taking into account[11]. Therefore, there is a knowledge gap to find an appropriate Mar-kov model applicable for these devices.

This paper tries to focus on this topic by bringing two main con-tributions into the existing literature. First, a Markov model is pro-posed which is capable to consider the distinct reliability featuresof fuse cutouts. Then, the proposed Markov model is used to allo-cate fuse cutouts in MV overhead lines by using the well-knownreliability index of energy not supplied (ENS). Finally, an economicanalysis is presented to investigate cost-saving benefits of the pro-posed model in protection device allocation procedure.

2. Problem statement

The ultimate purpose of protection is to provide power systemreliability. It might seem that protection of equipments is the pur-pose of protection systems, but this misses the global picture. It isthe integrity of the system which is being protected [5]. To designprotection scheme of a specific system, various devices becomeavailable and may have significant cost. Thus, the evaluation ofthe impact of applying new device as well as its cost effectiveness,is required.

Overcurrent relays (OCRs) and directional overcurrent relays(DOCRs) are widely used for the protection of radial and ringsub-transmission and distribution systems [12]. In some cases, dif-ferential protection scheme is also used in distribution feeder pro-tection system due to its fast operation [13]. In distributionsystems, these relays have relatively considerable cost comparingto other devices and mainly are used in the beginning of the feed-ers at the primary substations [14]. They have been studied in lit-erature in several areas of research such as optimum coordinationand advanced coordination methods, optimum routine test andself checking intervals, coordination of instantaneous trip func-tions with other protective devices like current-limiting fuses,etc. [2,15–18].

Reclosers and sectionalizers, which are other distribution pro-tective devices, also have relatively high expense and are usuallyinstalled on the beginning of distribution branches which servesensitive loads. They are also used for improving the reliability ofthe system especially in the DG-enhanced distribution networkswith preserving the protection system coordination [19]. But, thereis a protective device in distribution system which is inexpensiveand widely used along the distribution feeders and branches andalso for protecting the pole-mounted transformers. This device isfuse cutout and as mentioned above, has two different usages;one for protecting the pole-mounted transformers. Therefore, it islocated at the primary side of each aforementioned transformer.The other is in feeder protection where the fuse cutout is placedat the joint points and protects the main feeder from outages initi-ated at the feeder taps. These two usages are shown in Fig. 1.

The location of fuse cutouts which are used for transformer pro-tection is completely definite. They are installed at the primaryside of MV3/LV4 transformers. The rating of these fuses is chosenbased on the standard list according to its protected MV/LV trans-former capacity [20]. Such fuses should be coordinated with the up-stream fuses and overcurrent relay exists at the beginning of the MVfeeder. But, here questions raise as: ‘‘Where is the proper and cost

1 Current transformer.2 Voltage transformer.3 Medium voltage.4 Low voltage.

effective place for the joint point fuse cutouts?’’, ‘‘Should they be in-stalled at the beginning of every joint point along the distributionfeeders?’’ For example, if a branch has a few meters length and onlyone or two small transformers are being installed along this branch,does it need an individual fuse cutout for protecting itself or an up-stream protection device could provide the required protection?

In an increasingly competitive market environment where com-panies emphasize cost control, correct modeling and allocation offuse cutouts which can lead to a cost-saving approach becomeimportant. To answer the aforementioned questions, it is necessaryto evaluate the reduction of frequency and duration of outageshappening in a specific period of time and for a specific set of cus-tomers. Placing the fuse cutout at the joint points leads to decreasethe faulty zone; therefore, the resultant benefit should be com-pared to the investments that need to be expended for the requirednumber of fuse cutouts. Achieving this aim, the reliability model-ing of fuse cutouts should be studied and the performance of fusefor providing an economical reliable distribution network shouldbe assessed. Markov model of a fuse is a suitable approach forreliability modeling in Monte-Carlo simulations which will beexpressed in the following section.

3. Fuse Markov model

The first step in determining the reliability model for any sys-tem is to understand its function, the constraints under which itoperates, and the root cause of the failure [2]. Here, to betterunderstand the reliability modeling of the fuse cutout, the distinc-tive features of the fuse in comparison with the protective relaysare discussed.

There have been a number of models established to facilitatethe reliability evaluation including protective relay failures. Themodels of current-carrying component paired with its associatedrelay protection system are proposed in literature [1–3,6]. Also, amodel that separates the component Markov model from the pro-tection Markov model has been suggested in [4]. In that paper [4],the model is capable of analyzing the different reactions of over-current relays that have been installed on the both sides of a line,when a fault occurs in an interconnected system.

If the fuse is placed as the protective device in an electrical sys-tem, there is a reason that makes the Markov modeling of the fusediffer. The important point is that the fuse has not an inspectionstate when the current-carrying component is up. This is an intrin-sic feature of the fuse which is placed in series with the line whilethe network operator is not able to test this device during the oper-ation period of the network. The reason is the need for load de-energizing during the test process and detrimental effects of fusetests leading to fuse burning and fuse-link removal after the testcompletion. Thus, the inspection state will never exist in the

M. Gilvanejad et al. / Electrical Power and Energy Systems 42 (2012) 575–582 577

reliability model of the fuse. It leads to the fact that the probabilityof true or false operating of the fuse cutout can only be consideredwhen the component fails. In other words, it is possible to con-struct a Markov model of the fuse cutout only involved when thecurrent carrying component fails.

The Markov model of fuse cutout having five states is shown inFig. 2. As mentioned above, all of these states, except state 1, areprobable to occur only when the current carrying component isdown. The states in Fig. 2 are as follows:

� State 1: the fuse cutout is carrying the current.� State 2: the fuse link of fuse cutout starts to melt.� State 3: the fuse cutout trips.� State 4: the fuse cutout has experienced ‘‘failure to operate’’.� State 5: backup protection trips.

The notations in Fig. 2 are:

lI1

sum of repair rates relevant to component and fusecutout in normal (main) protection zone;

lI2

sum of repair rates relevant to component and fusecutout in backup protection zone;

wN

normal tripping rate to isolate component; wB backup tripping rate to isolate component; k failure rate of component; kp1 failure rate of fuse cutout to expose to ‘‘undesired trip’’; kp2 failure rate of fuse cutout to state of ‘‘failure to operate’’. kMC rate of mis-coordination of protection

The reason of selecting two different coefficients for main andbackup tripping and repair rates of protection system is the differ-ences that exist between the operation speed and fault locatingtime in these two protection zones in reality. The backup protec-tion (relay/fuse) should act with delay when the main protection(fuse) has no action. After tripping the backup protection, faultlocating process takes longer time because the zone of backup pro-tection is more extensive than the main protection zone. The hid-den failure is not considered for the backup protection because theoccurring of hidden failures in the set of main and backup protec-tions is rare.

In the model depicted in Fig. 2, the mode of influencing the mis-coordination of protection system on the reliability model has beenshown. As shown in this figure, the mis-coordination makes thebackup protection operate before the main protection. The rateof mis-coordination events greatly depends on the skill of protec-tion staff. In this paper, we want to locate the proper place for

Fig. 2. Markov model of fuse cutout.

the fuse cutouts in a distribution system considering the econom-ical and technical features. Human errors are not included in thestudy hence, the mis-coordination factor is neglected. The mis-coordination effect can be studied in each utility by applying therelated kMC in the model of fig. 2. The remaining parts will be thesame as the approach presented in the following sections of thepaper.

In general, in normal operating condition, load currents are nor-mally distributed in the network branches and fuse cutouts con-duct the current in a normal manner. In this situation, fusecutout is in state 1 (Fig. 2) where constitutes most time of opera-tion period. When a fault occurs in the distribution system, hugeamount of current passes through the fuses and makes it startmelting (state 2). If the fuse cutout trips correctly, the fault willbe isolated and fuse will be placed in state 3. Otherwise, if the fusefails to operate in a rational time (state 4) then backup protectionhas to trip immediately (state 5). After isolating the fault, either innormal zone or backup zone, the repair action starts and returnsthe system to a good state (state 1). In some instances, the fusetrips erroneous and makes the system to be de-energized unrea-sonably. In such situations, system goes directly from state 1 tostate 3.

In this way, the proposed model in Fig. 2 could model the differ-ent states which could happen in the fuse cutout protected distri-bution network. This model will be used in reliability analysis forthe fuse allocating methodology.

4. Fuse cutout allocation

4.1. Fuse cutout allocation methodology

Regardless the overcurrent relays which exist in sub-transmis-sion substations and being installed at the beginning of the med-ium voltage feeders, the MV overhead lines are also protected byfuse cutouts. These fuses are mainly placed at the joint points alongthe feeders. As mentioned before, determining the number of fusesthat should be installed along a feeder is a problem. This problem issolved through the cost and benefit balancing. Costs contain capitalexpenses to be invested for fuse cutouts and benefits contain rev-enues obtained from the outage and maintenance cost reduction.

In order to estimate the outage costs of a distribution system,the reliability analysis is required. This estimation could be doneby Monte Carlo iterative approach. The Markov Model of a fuse cut-out which is offered in Fig. 2 has been used in this Monte Carlosimulation.

It is necessary to mention that the reliability analysis should bedone for each fuse cutout removal on candidate places of the re-lated MV network. In this way, the analysis provides the amountof energy not supplied that fuse could decrease. Then, the worthof this additional sold energy is compared with the investmentsthat are required for the fuse cutout installation. If the fuse cutoutinstallation has the economical justification, the benefit of outagereduction during the life time of the network will compensatethe investments for fuse cutouts at installation time and will ob-tain some financial benefits for utility owners. Otherwise, the re-lated place is not proper for the fuse cutout placement.

Since in real networks, multiple faults may concurrently occurin different parts of the network, the reliability analysis should en-able to model this type of failures. However, the reliability calcula-tions should only consider one failure whenever the multiple failedcomponents devote to a unique protective device.

Furthermore, the magnitude of the energy not supplied (ENS),that occurs in a feeder because of the feeder failures, depends ontwo main factors: (a) the feeder load, and (b) the feeder length.The manner of affecting the load amplitude is that, whatever the

578 M. Gilvanejad et al. / Electrical Power and Energy Systems 42 (2012) 575–582

feeder load increases, the occurrence of any outage makes morecustomers be de-energized and the amount of energy not suppliedincreases. The other factor, ‘‘the feeder length’’, causes that what-ever the length increases, the probability of fault and outage occur-rence increases which will lead to energy not supplied increment.These two factors obviously show that making decision about plac-ing or not placing a fuse cutout along a feeder strongly depends onthe feeder and load configuration.

Based on the above discussions, it is proposed a method for thefuse cutout allocation as the following steps:

a. Fuse cutouts are placed at every beginning and middlepoints of medium voltage overhead lines.

b. For each fuse removal, the reliability analysis is performedand the rate of ENS changes is calculated.

c. If the cost of ENS increment due to fuse cutout removal wasless than the investment that is required for the fuse instal-lation therefore, the fuse cutout should not be installed.Otherwise, fuse cutout must be installed.

The middle point of the feeders is considered as a typical placefor sectionalizing type of fuse cutouts. This type of fuse can be in-stalled anywhere between start and ending points of the feeder.

4.2. Formulation of fuse Markov model in Monte Carlo simulation

The probability of residing in each state of Markov modelshown in Fig. 2 in an analytical way can be obtained via the theoryof Continuous Markov Processes [1]. The steady state probabilitiesof the proposed Markov model can be calculated by solving the fol-lowing equation:

P � a ¼ P ð1Þ

where a is the state transitional probability matrix:

a ¼

0 k kp1 0 00 0 wN kp2 kMC

lI1 0 0 0 00 0 0 0 wB

lI2 0 0 0 0

26666664

37777775

ð2Þ

And P is the row vector of state probabilities:

P ¼ ½Pstate1Pstate2Pstate3Pstate4Pstate5� ð3Þ

Using Eqs. (1)–(3), it is possible to obtain the average values ofthe probabilities devoted to reside in each state. In our approach,however, for closing the results to reality (real values, not averagevalues), the non-sequential Monte Carlo simulation is used toachieve the more accurate results. Since the failure rates of the net-work devices and protection systems are supposed to be constant,their failure probability corresponds to the exponential probabilitydensity function. The failure probability of a network componentaccording to exponential density function is as follows:

pðtÞ ¼ ke�kt ; t P 0 ð4Þ

where t is the age of the network component in year. The probabil-ity of multiple faults for a single component during a year is fulfilledby the Poisson process as follows:

pðkÞ ¼ kke�k

k!; k ¼ 0;1; . . . ð5Þ

where k is the number of component failures in a year.In Monte Carlo method, a random number generator that pro-

duces random numbers between 0 and 1 is used for assigning arandom failure probability to each network component. Wheneverthe random assigned number was smaller than the calculated

failure probability based on Eqs. (4) and (5), the related componentis considered as a failed component. This procedure is also accom-plished in this paper for modeling the component repair process aswell as the protection system malfunctioning in Monte Carlo sim-ulation; through replacing k in Eqs. (4) and (5) with related failureor repair rates (e.g. lI1, lI2, kp1, etc.).

4.3. Formulation of allocation criteria

If annual failure rate of an overhead line is shown with k then,the average cost of annual energy not supplied CENS-a can be calcu-lated through the following equation:

CENS-a ¼ kLPaveToutageCENS ð6Þ

where L is the length of feeder, Pave is the average active power ofloads which have experienced the outages, Toutage is the averageoutage time and CENS is the worth of energy not supplied unit (i.e.$/KW h). As mentioned before, Eq. (6) is an average value and onlytakes into account the failure rate of the feeder. In order to involvethe failure rates of protection system in each state of Markov modelshown in Fig. 2, a Monte Carlo simulation which utilizes randomnumber generators to model stochastic failure occurrences in com-ponent and protection areas is employed and the related outagetime and energy not supplied are calculated simultaneously. There-fore, the annual cost of ENS is calculated as follows:

CENS-a-tot ¼ ENS� CENS ð7Þ

where ENS is total energy not supplied which consists of energy notsupplied because of occurring faults in overhead lines and energynot supplied because of failures in protection system and CENS-a-tot

is its related costs. Since CENS-a-tot is a cost that happens every yearduring the network lifetime so, it should be converted to the pres-ent value. With the aid of this conversion, it makes possible com-pare ENS cost with the investment cost which is being spent atthe present time. To achieve this aim, the following equation is used[21]:

P:W: of CENS ¼ð1þ RORÞn � 1

ROR� ð1þ RORÞn� CENS-a-tot ð8Þ

where P.W._of_CENS is the present worth of the whole energy notsupplied during the lifetime of the network, ROR is the rate ofinvestment return that the utility owner expects (rate of interest)and n is the lifetime of the network in years. Proper installation offuse cutouts along the feeders could reduce CENS-a-tot and makesome benefit for the utilities. In general, if the following equationhas a positive value, the fuse installation at the relevant point isnot required. Otherwise, if it has a negative value, the fuse cutoutis required.

NB ¼ Ccap � ½P:W: of CENSð2Þ � P:W: of CENSð1Þ� ð9Þ

where NB is the net benefit of fuse removal and Ccap is the capitalcosts required for fuse cutout placement. Also (1) and (2) indicesrepresent the total worth of feeder ENS before and after fuse re-moval, respectively.

In the next section, the proposed methodology is implementedin sample networks and the results are discussed in detail.

5. Study results

5.1. Simple test case

The allocation methodology is demonstrated in a constitutedsystem of seven branches and seven transformers which is alsoused in [22]. In this system, each transformer is defined with theload power of 150 KW, 1-km branch length, 13.8 kV of operation

Fig. 3. System example.

Table 3Network ENS results.

Branch no. ofremoved fuse

No fuseremoval

1–2 3–4 3–5 1–6 6–7

ENS (kW h) (MonteCarlo)

2815 3630 3230 3230 3490 2960

Priority of removal – 4 2 2 3 1

Fig. 4. First candidate of fuse cutout removal.

M. Gilvanejad et al. / Electrical Power and Energy Systems 42 (2012) 575–582 579

and a failure rate equal to one fault a year (k = 1). The re-establish-ment time (Toutage) is 55 min. Fig. 3 shows the described system. InFig. 3, triangles contain electrical loads and circles are fuse cutouts.

The failure and repair probability distribution functions of thenetwork devices are formed according to their related failure andrepair rates and then are used in Monte Carlo simulation. Forexample, the probability distribution functions related to eachbranch failure will be equal to:

pðtÞ ¼ e�t ; t P 0 ð10Þ

And,

pðkÞ ¼ e�1

k!; k ¼ 0;1; . . . ð11Þ

In [22], the aforementioned distribution system is used forimplementing the protection coordination algorithm and the aver-age energy not supplied of the system is calculated as a criterionfor priority of fuse removal. The calculated ENS has not consideredthe hidden failures of the fuses. In that paper, since the goal is thecoordination of protection devices, an estimate of average values ofENS is useful for prioritizing of fuse removal; and fuse allocation isnot the subject of the study. In our study, however, in order to eco-nomically evaluate the fuse cutout allocation, the real values ofENS are needed to be taken into account. Thus, it is required thatmore real parameters affecting the operation of real network beconsidered in reliability studies such as undesired trip and failureto operate of protection systems, re-establishment time of mainand backup protection, etc. In this study, the re-establishment timeof the network in backup zone of the protection system is consid-ered as twice (110 min) of outage time in the main protection sys-tem (55 min). The value of other parameters for the cutout fuseMarkov model which is used in simulations is presented in Table 1.

In Table 2, to compare the results of analytical (Ref. [22]) anditerative Monte Carlo approaches, the quantities of ENS for differ-ent fuse removals of sample network are presented.

Table 1Fuse cutout reliability data [9].

kp1 (failure/year) kp2 (failure/year) WN (operation/h) WB (operation/h)

0.00374 0.00876 36,000 18,000

Table 2Comparison of ENS results.

Branch no. ofremoved fuse

No fuseremoval

1–2 3–4 3–5 1–6 6–7

ENSa (kW h/year)(analytical)

2755.5 3580.2 3169.6 3169.6 3444.2 2893.1

ENS (kW h/year)(Monte Carlo)

2730 3555 3160 3160 3400 2880

Priority ofremoval

– 4 2 2 3 1

a The values of this row is obtained from [18].

In Table 2, in order to keep similarity with assumptions in [22],the protection failure rates are not considered for the Monte Carlosimulations; therefore, no backup protection exists. As can be seen,the results are close to each other. But there are some differencesbetween the quantities which despite low magnitude, is importantwhen the size of the network extends and the number of cutoutfuses increases. Monte Carlo estimates the reliability indices basedon the stochastic approach which corresponds to the networkbehavior essence. Therefore, its results are more useful for techni-cal–economical evaluations.

The ENS values resulting from the proposed Markov model(Fig. 2) in Monte Carlo simulations which include all of the param-eters shown in Fig. 2, are presented in Table 3. According to the ta-ble, the first priority of fuse cutout removal is fuse No. 6 (Fig. 4).

The quantities that have been inserted in Table 3 are annual val-ues and to implement the proposed methodology for the fuse allo-cation, the present worth of ENS cost during the life time of thesystem should be calculated before and after fuse cutout removal.So

PW of CENSð1Þ ¼1:120 � 1

0:1� 1:120 � 2815� 0:1

PW of CENSð1Þ ¼ 2396:6$

PW of CENSð2Þ ¼1:120 � 1

0:1� 1:120 � 2960� 0:1

PW of CENSð2Þ ¼ 2520:0$

ð12Þ

Eq. (12) is computed according to (8), where ROR and n are assumed0.1 and 20. CENS is also assumed 0.1 $/kW h.

The capital cost of the installation a series of three phase fusecutouts is supposed 170 $. Now, it is possible to calculate the intro-duced criteria (Eq. (9)) to judge about preserving or removing thefuse cutout which can be placed on branch (6–7):

NB ¼ 170� ½2520:0� 2396:6� ¼ 46:6$ ð13Þ

Therefore, Eq. (13) declares that the fuse cutout is not requiredin branch (6–7) and should be removed. After removing this fusecutout, the process should be repeated and the removal prioritiesshould be determined again. Results of this stage are presentedin Table 4.

Two points can be achieved from Table 4. The first one is thatthe next candidate for fuse removal is fuse No. (3–4) or (3–5).The second one which is more important is that the sequenceof fuse removal priorities has changed comparing to Table 3.

Table 4Network ENS results after the first fuse removal.

Branch no. of removed fuse No fuseremoval

1–2 3–4 3–5 1–6

ENS (kW h/year) (MonteCarlo)

2960 3770 3370 3370 4280

Priority of removal – 2 1 1 3

Table 5Network ENS results after taking new rates for fuse cutout undesired trip (kp1).

kp1 = 0.095(failure/year)

kp1 = 0.95(failure/year)

ENS (kW h/year)

Fuse cutout No. (3–4)preserved

3030 3980

Fuse cutout No. (3–4)removed

3410 4160

NB ($) �153.4 16.8

Table 6Network ENS results after taking new rates for fuse cutout failure to operate (kp2).

kp2 = 0.015 kp2 = 0.15(failure/year)

(failure/year)

ENS (kW h/year)

Fuse cutout No. (3–4)preserved

2950 3590

Fuse cutout No. (3–4)removed

3320 3780

NB ($) �144.9 8.3

580 M. Gilvanejad et al. / Electrical Power and Energy Systems 42 (2012) 575–582

In Table 3, fuse No. (1–6) has higher priority than fuse No. (1–2). InTable 4 fuse No. (1–2) has higher priority for removal. Therefore, itcan be concluded that the sequence of fuse removal should bere-evaluated after any fuse cutout elimination.

Fig. 5. Distribution syst

Now, in order to make decision about the second fuse removal,the worth of ENS increment duo to the eliminating of the fuse ofthe highest removal priority (fuse No. (3–4)) is again calculated:

PW of CENSð2Þ ¼1:120 � 1

0:1� 1:120 � 3370� 0:1

PW of CENSð2Þ ¼ 2869:1$

ð14Þ

Therefore, NB equals to:

NB ¼ 170� ½2869:1� 2520:0� ¼ �179:1$ ð15Þ

The fuse removal has not any justification this time and fusecutout No. (3–4) (or (3–5)) should be preserved. Since this fusewas the first priority for fuse removal in the network, the othercandidates certainly will not have justification for the removal.

In order to more clarifying the influence of a factor which affectsthe removal or preserving the fuse cutouts during the allocationprocedure, some complementary studies are performed here. Thisimportant factor is the magnitude of hidden failure rates. Theundesired trip or failure to operate of fuse cutouts will result inENS augmentation in distribution systems. Bigger values of hiddenfailure rates will result in bigger values of total network ENS.Therefore, the hidden failure rate increment in fuse cutouts mayresult in more fuse cutout removal action to achieve less ENS valueof the network in optimum placement procedure. For example, thesecond fuse cutout removal action for the test system has not eco-nomic justification (Eq. (15)) when its hidden failure rate wasaccording to Table 1. However, its removal will have economic jus-tification if the fuse cutout hidden failure rate has large enough va-lue to make the answer of Eq. (15) positive.

In order of evaluation the effect of hidden failure rate magni-tude on the economic justification which is investigated in fusecutout allocation process, some complementary simulations wereperformed to assess this issue and their results have been reportedin Tables 5 and 6.

Tables 5 consists the ENS results for changing the undesired tripvalue of fuse cutouts in the system of Fig. 3 and Table 6 consists the

em for RBTS bus 5.

Fig. 6. Joint point configuration.

Table 7Overhead lines reliability data.

Failure rate (failure/year km) Repair time (h) Switching time (h)

0.065 5 1.0

M. Gilvanejad et al. / Electrical Power and Energy Systems 42 (2012) 575–582 581

ENS results for changing the failure to operate value of fuse cutoutsin the system of Fig. 3. The first row of ENS results in Tables 5 and 6devotes to the energy not supplied values of the network which arecalculated with new values of kp1 and kp2 before removing the fusecutout No. (3–4). As can be seen in these two tables, removal offuse cutout No. (3–4) will have economical justification wheneverkp1 and kp2 take large enough values and causes the NB takes a po-sitive value. Furthermore, it is seen that the influence of kp2 (failureto operate) variation on the energy not supplied value of the sys-tem is much more than kp1 (undesired trip). In other words, thefuse cutout allocation procedure is more sensitive to kp2 ratherthan kp1.

The ENS is also influenced by two other factors such as loadmagnitude and feeder length. Changing each of them could changethe final decision about the fuse. Hence, in order to show the gen-erality of the proposed methodology, IEEE distribution reliabilitytest system will be studied in the next section.

5.2. IEEE 6-bus test system (RBTS)

The IEEE test system for reliability assessment is a 6 bus testsystem with five load buses (bus 2–bus 6). The distribution net-work at bus 5 represents a typical urban type network consistingof residential, government and institutional, office and buildings,and commercial customers. The peak load of the distribution sys-tem at bus 5 is 20 MW. The distribution network at bus 5 is labeledin detail in Fig. 5 [23].

In this network, a fuse cutout is placed at any join point. Fur-thermore, a disconnector has been installed after each join point.

Table 8Network ENS results and removal priorities.

Branch No. of removed fuse No fuse removal 2 3

ENS (kW h/year) 2750 3680 3680Priority of removal – 6 6

Fig. 6 illustrates the configuration of the fuse cutout and the dis-connector at the joint points [24].

In [23,24], the fuses and disconnectors are assumed to be 100%reliable. But, here in our study, the fuses are not 100% reliable andhave failure rates corresponding to the mentioned quantities in Ta-ble 1. The reliability data for the 11 kV lines are shown in Table 7[23,24].

The failure and repair probability distribution function for thenetwork components and protection systems are formed and theyare used in Monte Carlo simulation. The failure probability func-tion of the network overhead lines will be equal to as follows:

pðtÞ ¼ ð0:065� lÞ � e�ð0:065�lÞ�t; t P 0 ð16Þ

And,

pðkÞ ¼ ð0:065� lÞke�ð0:065�lÞ

k!; k ¼ 0;1; . . . ð17Þ

where l is the length of overhead line in both aforementioned rela-tionships. Now, the fuse cutout allocation methodology is imple-mented on the feeder F1 of the system shown in Fig. 5.Comparing to the previous sample test, in this case, the disconnec-tors have been added to distribution system and are included in thereliability simulations. The feeder lengths and loading data areaccording to [23].

Similarly, the first step is the determination of the removal pri-orities. This data has been collected in Table 8.

The present worth of ENS before and after removing the firstcandidate cutout fuse (i.e. cutout fuse No. 11) equals to:

PW of CENSð1Þ ¼1:120 � 1

0:1� 1:120 � 2750� 0:1

PW of CENSð1Þ ¼ 2341:3$

PW of CENSð2Þ ¼1:120 � 1

0:1� 1:120 � 2920� 0:1

PW of CENSð2Þ ¼ 2486:0$

ð18Þ

For this state, the NB factor for cutout fuse removal is calculatedas:

NB ¼ 170� ½2486:0� 2341:3� ¼ 25:3$ ð19Þ

Therefore, cutout fuse 11 should be removed. Prioritizing thefuse cutouts at the next stage after removing the cutout fuse 11is demonstrated in Table 9.

In the case of evaluating the elimination of cutout fuse No. 9,the NB will be equal to �17.3$ therefore, it should be preserved.

As the results show, in every distribution system, the problemof placing or removing the fuse cutout on the beginning of thebranches should be evaluated case by case. In the two sampleswhich are studied in this paper, one fuse cutouts was been in-stalled improperly.

In this way, all of MV overhead lines can be evaluated for thefuse cutout allocation and only the fuse cutouts with technicaland economical justifications are installed. The procedure whichis described in this paper can help to better modeling of the fusecutout operation in distribution systems and the network opera-tors can better manage the network investments through optimalplacement of fused cutouts in distribution systems where, largenumbers of fused cutouts are usually installed.

5 6 8 9 11

3410 3140 3010 2960 29205 4 3 2 1

Table 9Network ENS results and removal priorities.

Branch No. of removed fuse No fuse removal 2 3 5 6 8 9

ENS (kW h/year) 2920 3790 3790 3540 3320 3220 3140Priority of removal – 5 5 4 3 2 1

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6. Conclusion

In this paper, a new Markov model for the reliability analysis ofthe fuse cutouts has been proposed which considers the hiddenfailures of the fuses. Also, a methodology has been suggested forthe fuse cutout allocation along the medium voltage overhead dis-tribution lines. This methodology gives a simple and useful crite-rion for decision making about fuse cutout placement. Theapproach has been tested on two different networks. One of thesewas a simple constituted network which the methodology isimplemented and its concepts were explained. Another one wasthe IEEE reliability test system and the methodology was discussedfor one of its feeders. This network had also disconnectors whoseeffects are included in the reliability simulations. Fuse cutout allo-cation results showed that in both sample networks, there was afuse cutout which was been installed improperly.

Therefore, using the proposed methodology in this paper, thereliability of MV overhead lines is maintained at a reasonable levelwhile preserving the protection system adequacy. The results ofthe implementing the proposed methodology in two sample net-works show its capability and simplicity to be applied in real MVoverhead distribution lines.

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