1

Abstract-- Distribution automation (DA) application for fault

management in the electricity distribution networks is one of the main potential remedial actions to reduce customers’ outage times and hence improve service reliability. As a result, various automation schemes have been developed and introduced in different countries and by different venders. The impacts of implementing a specific automation scheme on reliability indices of a given distribution system can be different from other available automation schemes. For this reason, when comparing the available automation schemes with each other or with the other reliability improvement measures, it is necessary to perform a course of reliability worth assessment activities in the related decision making process. This paper aims to quantitatively assess the reliability worth of employing an Automatic Loop Restoration Scheme (ALRS) for urban distribution networks. Distributed intelligence and peer-to-peer communication are the main features of this feeder automation scheme. An urban distribution reliability test system is utilized in this paper to perform the reliability worth assessment analyses.

Index Terms--Distribution Automation, Automatic Loop Restoration Scheme, Reliability Worth Assessment, Urban Distribution Network.

I. NOMENCLATURE ALRS Automatic Loop Restoration Scheme CB Circuit Breaker DA Distribution Automation LP Load Point MAIFI Momentary Average Interruption Frequency Index MST Manual Switching Time RMU Ring-Main Unit SAIDI System Average Interruption Duration Index SAIFI System Average Interruption Frequency Index SURTS Swedish Urban Reliability Test System SW Load-Break Switch Ci Component i Lj Load point j

S. Kazemi is with the Departments of Electrical Engineering at Sharif

University of Technology, Tehran, Iran and also at Aalto University School of Science and Technology, Espoo, Finland (e-mail: shahram.kazemi@tkk.fi).

M. Lehtonen is with the Department of Electrical Engineering, Aalto University School of Science and Technology, Espoo, Finland (e-mail: matti.lehtonen@tkk.fi).

M. Fotuhi-Firuzabad is with the Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran (e-mail: fotuhi@sharif.edu).

Per unit interruption cost of Lj due to an interruption with duration of t in EUR/kW

Contribution to expected interruption cost of Lj due to a fault on Ci

Average load connected to Lj Repair time of Ci

Contribution to the sustained annual outage time of Lj due to a fault on Ci

Rate of fault on Ci S

LC jiλ

Contribution to the sustained interruption frequency of Lj due to a fault on Ci

Contribution to the momentary interruption frequency of Lj due to a fault on Ci

II. INTRODUCTION

Analysis of customer failure statistics in the most electric utilities indicates that electric power distribution systems make the greatest individual contribution to the unavailability of supply to customers. Typical distribution system accounts for 25-40% of the cost to deliver power and 80-90% of customer reliability problems [1]-[3]. These statistics reinforce the need to be concerned with the reliability evaluation of distribution systems, to evaluate quantitatively the merits of various reinforcement schemes available to the planner and to ensure that the limited capital resources are used to achieve the greatest possible incremental reliability and improvement in the system. Distribution automation application for fault management in the electricity distribution networks is one of the main potential remedial actions to reduce customers’ outage times and hence improve service reliability. As a result, various automation schemes have been developed and introduced in different countries and by different venders [4]-[5]. The impacts of implementing a specific automation scheme on reliability indices of a given distribution system can be different from other available automation schemes. For this reason, when comparing the available automation schemes with each other or with the other reliability improvement measures, it is necessary to perform a course of reliability worth assessment activities in the related decision

Reliability Worth Assessment of an Automatic Loop Restoration Scheme for Urban

Distribution Networks Shahram Kazemi, Graduate Student Member, IEEE, Matti Lehtonen

Mahmud Fotuhi-Firuzabad, Senior Member, IEEE

2

making process. Reliability assessment of a manually operated distribution system is not a difficult task. However, the evaluation process will be complicated when some levels of automation are implemented in the system under study. Usually, in this situation, much detailed reliability modeling and analyses are needed to gain the desired results.

The basic concepts of reliability evaluation procedure and their application for several different automation schemes have already been discussed in the previous works of the authors [6]-[9]. However, the evaluated automation schemes were mainly designed for rural distribution networks. Rural distribution networks are almost overhead line design. The nature of such networks is such that the share of transient faults is dominant. For this reason, available automation schemes for these networks are almost based on using switching devices like reclosers and sectionalizers. These automation schemes can be implemented either based on the centralized intelligence or distributed intelligence. In [6]-[7], an automation scheme based on a centralized intelligence, and in [8]-[9], two automation schemes based on the distributed intelligence were discussed and evaluated. These automation schemes have been mainly designed for overhead line rural distribution networks.

The main characteristic of urban distribution networks is its underground cable open-loop design. Cable faults are permanent and of high fault currents. For this reason, automation schemes available for urban networks are not allowed to use fault re-ignition sequence in fault detection, isolation and service restoration stages, which is almost common in the case of overhead rural distribution networks. Therefore, generally, available (standalone) automation schemes for underground cable distribution networks follow a different operating logic. These automation schemes are usually designed based on a set of intelligent load-breaking switches along the feeder and a communication network. These switching devices are operated in a coordinated manner with the feeder circuit breaker either from a centralized control center or through a set of local distributed intelligence available in the switching devices.

This paper aims to quantitatively assess the reliability worth of employing an ALRS for urban distribution networks. This ALRS works based on the distributed intelligence and uses a peer-to-peer communication network. An urban distribution reliability test system is utilized in this paper for reliability worth assessment analyses. The proposed technique is based on the event tree method and the concepts of conditional probability approach. The evaluation procedure follows the basic concepts developed in the previous works of the authors [6-9]. In this paper, the main emphasis is on the application of the developed concepts to this specific automation scheme.

III. OPERATIONAL PROCEDURE OF THE ALRS Urban distribution networks are almost in the form of

underground cable open-loop design. Each feeder consists of a set of cable sections with load-breaking switches, normally in the RMU arrangement. Each feeder is connected to one or more feeder through normally-open RMUs. Any short circuit

on a cable section causes the feeder circuit breaker to operate. After the fault has been located, however, the faulted cable section can be isolated from the healthy part of the feeder using the relevant sectionalizing switches and the circuit breaker is reclosed. This procedure allows the restoration of as many disconnected load points as possible to the main supply or to another feeder through normally-open RMUs. Finally, after repairing the faulted cable section, repair crew reconfigures the status of distribution network to its normal operating status.

The above operations can be performed automatically when an ALRS is employed in the distribution network. In this case, the fault detection, isolation, and service restoration stages can be accomplished sequentially and automatically, using the automation units installed on the network so as to significantly reduce the customer outage time. The ALRS typically implemented by retrofitting the feeder circuit breakers and RMUs with automation units which contain suitable secondary devices (such as actuators, current and voltage measuring sensors, communication devices and processing units).

Figure 1 shows an underground cable open-loop circuit which has been designed to work as an ALRS. In this distribution network, eight automation units have been implemented (two units for feeder circuit breakers and six units for RMUs). These automation units are such designed and implemented that the developed ALRS can operate based on the distributed intelligence concept and use a peer-to-peer communication network. The ALRS is designed to follow predefined operating logics.

Fig. 1. Typical configuration of an ALRS for urban distribution networks

Depending on the characteristic of the distribution network, number, location and capabilities of automation units, different operating procedure can be implemented for fault detection, isolation and service restoration activities. Consider the schematic diagram of Fig. 1. As an example, an ALRS can be designed to work for the indicated fault as follows:

A. Fault Detection Stage The over-current element in the protection unit of circuit

breaker CB1 and also the over-current element in the automation unit of ring-main unit RMU1 both detect the fault current passing through their primary equipment.

CB1

CB2

SW1 SW2 SW1 SW2

SW1 SW2 SW1 SW2

RMU3

RMU4 RMU6

LP1 LP3

LP4 LP5

Fault

SW1 SW2

SW1 SW2

RMU5

LP2

LP6

RMU1 RMU2

3

B. Fault Isolation Stage The protection unit of CB1 issues an opening comment to

this circuit breaker for fault interruption and locks it open. As a result, the power service for all the customers supplied by RMU1, RMU2 and RMU3 (i.e., LP1, LP2 and LP3) is interrupted. At the same time, the loss of voltage elements in the automation units of RMU1, RMU2 and RMU3 detect the loss of voltage condition in both sides of these RMUs and the automation unit of RMU6 detect the loss of voltage condition at one side of RMU6. After a short time delay, the automation units of CB1, RMU1, RMU2, RMU3 and RMU6 start to communicate with each other over a peer-to-peer communication network. The automation unit of CB1 reports an over-current fault condition which has been cleared by CB1. The automation unit of RMU1 reports an over-current situation followed by a loss of voltage condition. However, the automation units of RMU2 and RMU3 only report the loss of voltage conditions at both sides of RMU2 and RMU3, and the automation unit of RMU6 also reports the loss of voltage condition at one side of RMU6. Based on these reported information and some other shared information (such as the status of distribution network), it is recognizes that the fault has been on a cable section between RMU1 and RMU2. Hence, the automation unit of RMU1 issues an opening comment to SW2 of RMU1 and the automation unit of RMU2 issues an opening comment to SW1 of RMU2. By opening these switches, the faulted section is completely isolated from the rest of feeder and, hence, fault isolation stage is accomplished.

C. Service Restoration Stage After completing the fault isolation stage, automation units

of RMU1 and RMU2 report their successful operation to the other involved automation units. After acknowledging of this situation by the other automation units, the service restoration stage starts. The automation unit of CB1 issues a closing comment to this circuit breaker. As a result, power service is restored for the customers supplied by RMU1 (i.e., LP1). Finally, the automation unit of RMU6 issues a closing comment to SW2 of RMU6 in order to restore the customers supplied by RMU2 and RMU3 (i.e., LP2 and LP3). Now, the power service has been restored for all the customers. Whole of this process can be accomplished within a short period of time (say 1 minute) which is much shorter than manual restoration time (say 60 minutes).

D. Repair and Return to Normal Configuration Stage After pinpointing the fault and repairing the faulted cable

section by repair crew, the network can be returned to its normal operating status. This activity can be started by issuing the return to normal configuration command to any one of the automation units involved in the faulted feeder. This command can be issued either by repair crew or from distribution control center, if there is a communication link available between automation unit of CB1 and the distribution control center. After receiving the return to normal configuration command, the automation units involved in the faulted feeder communicate which each other and recognize the status of each other. Next, they begin the transition process from the

current configuration to the normal configuration. As a result, automation units of RMU1 and RMU2 issue the closing comments to SW2 of RMU1 and SW1 of RMU2, respectively, which results in a closed loop configuration. Finally, the automation unit of RMU6 issues an opening comment to SW2 of RMU6 in order to open the loop and to return the network to its normal operating status.

IV. EVALUATION PROCEDURE At the moment, several venders are available in the power

distribution market which offering different types of ALRS. The procedure of fault detection, isolation and service restoration may differ from one automation scheme to another one. In addition, the operational failure of automation units of ALRS may have crucial effects on this procedure. Therefore, these issues should be modeled in the analyses, when performing the reliability worth assessment of the intended ALRS. Reliability assessment of a manually operated distribution system is not a difficult task. However, the evaluation process will be complicated when some levels of automation are implemented in the system under study. Therefore, a modular approach should be used to evaluate the impacts of ALRS on the distribution system reliability. In this approach, different operational failure modes of protection and automation units of ALRS can be considered in the analyses. The basic concepts of the evaluation procedure can be found in the previous works of the authors [6-9]. The evaluation procedure developed in [6-9] can be applied to any ALRS designed for urban (cable) distribution networks using the following steps:

(1) Classification of Restoration Times: When a fault occurs, restoration times of different load points of a feeder are not the same due to the operating procedure of the implemented ALRS and availability of its protection and automation units. Therefore, for any fault condition, customers of a distribution system equipped with ALRS can be included in the following classes: - Class A: Load points that are not interrupted due to a fault. - Class B: Load points that are interrupted due to a fault, but they can be restored by automatic switching actions of ALRS. It is considered that ALRS accomplishes this activity successfully. Therefore, outage durations of these load points are equal to the time required to isolate the fault and to restore service through a main or an alternative supply using successful automatic switching actions. These load points experience just one momentary interruption. - Class C: Load points that are interrupted due to a fault, but they can just be restored by manual switching actions. This may be either due to operational failure of some protection and/or automation units of ALRS or due to the inherent characteristics of the automated distribution network. The later usually exists in those parts of a distribution network with only manually-operated switching devices. Therefore, outage durations of these load points are equal to the time required to isolate the fault and to restore service through a main or an alternative supply using manual switching actions. These load points experience sustained interruptions. - Class D: Load points that are interrupted due to a fault and their outage durations are equal to the time required to locate

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and repair the failed component. These load points experience sustained interruptions.

(2) Reliability Modeling of ALRS: The ALRS is divided into modules that can be analyzed independently. The reliability data associated with each module can be either derived by a separate reliability analysis or obtained from a data collection scheme. For illustration purposes, the ALRS of Fig. 1 can be divided into 8 modules, corresponding to two feeder circuit breakers and six RMUs. These modules have no shared components and are considered to be independent. Each module contains switchgear, power supply units, timers, relays, sensors, processing units and communication systems. The developed reliability models can have any degree of complexity, depending on available data and study targets. This model should be able to show the probabilities associated with success or failure operation of protection and/or automation units of ALRS. It should be noted that, probability of operational failure is the conditional probability that a protection or automation unit will not operate if it is required to operate. As an example, a simple two-state model shown in Fig. 2 can be used for representing the success or failure operation of protection or automation units of ALRS.

Fig. 2. A simple two-sate model for representing the operational failure of automation or protection units of ALRS

(3) Deducing the Event Trees: Based on the type of

implemented ALRS, the procedure of ALRS in performing its task, when a fault occurs on a component of distribution network, is identified. This procedure involves the sequential operation logic of a set of protection and automation units of ALRS. Therefore, the consequence of the availability and unavailability of each protection and automation units of the involved switching devices on the operating procedure of ALRS is analyzed using the event tree method. Using this approach, various possible classes of load points and their associated probabilities are identified. For illustration purposes, consider the schematic diagram of Fig. 1. Assume the protection units of circuit breakers are fully reliable. Then, using the simple two-state model of Fig. 2 for representing the automation units of ALRS, an event tree diagram can be deduced for the indicated fault as shown in Fig. 3.

Fig. 3. Event tree diagram for the indicated fault in the network of Fig. 1, when implementation of ALRS described in this paper

The paths leading to the required outcome are first

identified. The probability of occurrence of each relevant path is the product of the event probabilities in the path. The probabilities associated with different classes of a particular load point can then be obtained by summing up the probabilities of each path leading to the same class for that load point.

(4) Based on the results obtained from step 3, the contributions to the sustained and momentary interruption frequency of Lj due to a fault on Ci are determined using the concepts of expectations as follows:

)P(D)D|(λ

)P(C)C|(λ λ

jijii

jijiiji

LCLCC

LCLCCS

LC

×+

×=

(1)

)P(B)B|(λ λ

jijiiji LCLCCM

LC ×=

(2)

S S

F S

RMU6

Fault

RMU3 RMU2 RMU1 CB1

F S

F

S S

F

F S

F

S S

F

F S

F

S S

F

F S

F

S S

F

F S

F

S S

F

F S

F

F

S

F

S

F

S

F

S

F

Class of Load Points

LP1 LP2 LP3

B B B

B C C

B B B

B C C

B C B

B C C

B C C

B C C

C B B

C C C

C B B

C C C

C C B

C C C

C C C

C C C

C B B

C C C

C B B

C C C

C C B

C C C

C C C

C C C

S: Automation unit works successfully F: Automation unit fails to operate

UU: Automation or protection unit works successfully UD: Automation or protection unit fails to operate λF : Operational failure rate of automation or protection unit μF : Repair rate for fixing the operational failure of automation or protection unit

UU

UD

λU μU

5

In these equations, and are respectively the

event and its associated probability, so that load point Lj due to a fault on Ci is categorized as Class C. Similar notations are used for referring to other classes of load points.

(5) The contribution to the sustained annual outage time of Lj of a fault on Ci is determined based on the concepts of conditional probability theory. Using the results obtained in step 3, the following equation can be deduced:

))P(D)D|)λ((r

)P(C)C|)λ((MST U

jijiii

jijiiji

LCLCCC

LCLCCS

LC

××+

××= (3)

(6) The contribution to the expected interruption cost of Lj

by a fault on Ci can also be determined based on the concepts of conditional probability theory. Using the results obtained in step 3, the following equation can be deduced:

{

})P(D)D|)(r(CIC

)P(C)C|(MST)(CIC

)P(B)B|(ALRT)CIC( λLa ECOST

jijiij

jijij

jijijijji

LCLCCL

LCLCL

LCLCLCLLC

×+

×+

×××=

(4)

(7) The load-point and system reliability indices are

determined by analyzing the contributions associated with different failure events. These indices can be calculated from the same equations outlined in step 6 of the evaluation procedure proposed in [9].

V. STUDY RESULTS The Swedish Urban Reliability Test System (SURTS) [10]

is used for reliability worth assessment of the ALRS described in this paper. The required component reliability data is given in [10]. However, the interruption cost data is taken from the results of the Finnish reliability worth study [11]. These data are shown in Table 1. A computer program has been developed to perform the necessary computations. It is assumed that protection units of circuit breakers operate successfully when required to do so. Also, when employing the ALRS for the test system, it is assumed that the feeder circuit breakers and distribution (transformer) substations are equipped with suitable automation units in order to follow the operating logic of the ALRS described in this paper. The procedure of ALRS for fault detection, isolation and service restoration is assumed to be accomplished within 1 minute.

Various comparative case studies were conducted in order to assess the performance of the ALRS from distribution system reliability improvement point of view. An overall brief description of various comparative case studies is as follows: - Case 1: The ALRS is not implemented and the distribution network is operated manually. - Case 2: The ALRS is implemented in the distribution network and it is assumed that all of its automation units are fully reliable. - Case 3: The ALRS is implemented in the distribution network and it is assumed that all of its automation units have 5 percents operational failure probability.

Fig. 2. The Swedish Urban Reliability Test System (SURTS) [10]

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TABLE 1 CUSTOMER INTERRUPTION COST IN EUR/KW [11]

Interruption Duration

Customer Type

Residential Public Commercial Industry

1 Second 0.23 1.9 1.8 1.9

2 Minutes 0.84 2.6 3.0 2.5

1 hour 5.8 13.6 27.6 17.0

4 hours --- 52.1 67.8 ---

8 hours --- 70.6 117.2 104.4

12 hours 43.8 91.3 163.0 132.7

Table 2 shows the system reliability indices of the test system for the above described comparative case studies. It can be seen from the results presented in Table 2 that the reliability indices are improved when ALRS is implemented in the test system compared to those obtained in the absence of ALRS (Case 1). Comparing the results shown in Table 2 for Cases 1 and 2 indicates the relative improvements for different reliability indices range from 62 to 70 percents. These improvements are due to the fact that ALRS can perform the fault detection, isolation and service restoration activities in a short period of time (say 1 minute) compared to the same activities in the manually operated distribution networks which takes a much longer time (say 60 minutes). Therefore, the number and duration of sustained interruptions (corresponding to SAIFI and SAIDI) are reduced when ALRS is implemented in the test system. However, the total interruption frequency experienced by the customers (SAIFI+MAIFI) is the same before and after of employing the ALRS in the test system.

Table 2 also shows the effects of operational failure of the automation units of ALRS on the reliability indices of the test system (Case 3). By comparing the results obtained for Cases 1, 2 and 3, it can be found that the operational failure of automation units of ALRS has negative impacts on its performance from reliability improvement vantage. When conducting Case 3, it was assumed that the automation units of the feeder circuit breakers and RMUs have the same operational failure equal to 5 percents.

TABLE 2

SYSTEM RELIABILITY INDICES OF THE TEST SYSTEM FOR VARIOUS COMPARATIVE CASE STUDIES

Reliability Indices Case 1 Case 2 Case 3

SAIFI (int/cust.yr) 0.210 0.063 0.0735 MAIFI* (int/cust.yr) 0.000 0.147 0.1364 SAIDI (min/cust.yr) 13.920 5.1223 5.7334

EENS [kwhr/yr] 4677.02 1605.85 1819.50 ECOST [EUR/yr] 80406.11 30703.12 34165.39

ASUI (%) 0.002648 0.000975 0.001091 * Aggregation window is assumed to be 5 minutes.

In order to find the effect of each set of these automation units on the reliability performance of ALRS, it is important to perform a course of sensitivity analyses. This can be conducted by varying the operational failure probability of a set of automation units of ALRS and determining their effects on the distribution system reliability indices. In these analyses, when the operational failure probability of a given set of automation units is changed, the other remaining automation units are assumed to be fully reliable. Three case studies were performed. In these case studies, each sensitivity analysis was only concentrated on the following set of automation units: - Case 4: The automation units of feeder circuit breakers. - Case 5: The automation units of normally-closed RMUs. - Case 6: The automation units of normally-open RMUs.

Figure 3 shows the results of various sensitivity analysis case studies. In this figure the results of various comparative case studies are also included. It can be seen from the results that except for MAIFI, all the other system reliability indices are deteriorated when the operational failure probability of any set of automation units of ALRS increases. However, the index MAIFI shows the opposite trend. This behavior is due to the operating logic of the implemented ALRS. When this automation scheme is fully or partially available, it tries to isolate the healthy parts of the network from the damaged section and restore as many as possible of load points through the main or alternative supplies in a short period of time. As a result, the frequency and duration of sustained interruption events, which are counted by SAIFI, SAIDI, EENS and ASUI, decrease and the frequency of momentary interruption events, which counted by MAIFI, is increased. The less operational failure probability, the more improvement in indices like SAIFI, SAIDI, EENS and ASUI is anticipated and the worse condition for MAIFI is expected. Among the system reliability indices, by definition, ECOST is the only reliability index which considers the effects of both sustained and momentary interruption events. For this reason, the performance of the implemented ALRS would be more precise from the reliability point of view. By close examination of the results presented in Fig. 3, it can be found that the performance of the implemented ALRS is more sensitive to the operational failure of automation units of normally-closed RMUs compared to the same situation for feeder circuit breakers or normally-open RMUs. The main reason, that can justify such behavior, is again the operational logic of the implemented ALRS. As noted earlier, the role of automation units of normally-closed RMUs in all stages of fault detection, isolation and service restoration is more dominated compared to the automation units of feeder circuit breakers and normally-open RMUs. Actually, without their acknowledgments on completing the fault detection and isolation stages, restoration of interrupted load points may partially or completely altered, despite of availability or unavailability of the other automation units.

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Fig. 3. The System Reliability Indices of the Test System for Various Comparative and Sensitivity Analysis Case Studies

0.00

0.03

0.06

0.09

0.12

0.15

0.18

0.21

0.24

0% 30% 60% 100% Case 3 Case2 Case1

SAIF

I [in

t/cu

st.y

r]]

Operational Failure Probability

Case 4 Case 5 Case 6

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0% 30% 60% 100% Case 3 Case2 Case1

MA

IFI [

int/

cust

.yr]

Operational Failure Probability

Case 4 Case 5 Case 6

0

2

4

6

8

10

12

14

16

0% 30% 60% 100% Case 3 Case2 Case1

SAID

I [m

inut

es/c

ust.

yr]

Operational Failure Probability

Case 4 Case 5 Case 6

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

0% 30% 60% 100% Case 3 Case2 Case1

EEN

S [k

whr

/yr]

Operational Failure Probability

Case 4 Case 5 Case 6

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

0% 30% 60% 100% Case 3 Case2 Case1

ECO

ST [E

UR/

yr]

Operational Failure Probability

Case 4 Case 5 Case 6

0.0000

0.0004

0.0007

0.0011

0.0014

0.0018

0.0021

0.0025

0.0028

0% 30% 60% 100% Case 3 Case2 Case1

ASU

I [%

]

Operational Failure Probability

Case 4 Case 5 Case 6

8

VI. CONCLUSION Electric utilities can improve distribution system reliability

through various methods. Distribution automation application for fault management in the electricity distribution networks is one of the main potential remedial actions to reduce customers’ outage times and hence improve service reliability. For this purpose, various automation schemes have been developed and introduced in different countries and by different venders. This paper was concentrated on reliability worth assessment of an automatic loop restoration scheme which is mainly designed for reliability improvement of urban distribution networks. The basic concepts of reliability worth evaluation procedure for automated distribution network have been already developed in the previous works of the authors. For this reason, in this paper the main emphasis was on the application of this evaluation method for this specific automation scheme.

Various analyses were performed in this paper using the Swedish Urban Reliability Test System. Comparative case studies were conducted to illustrate how the automation scheme described in this paper could affect the reliability indices of the test system. Sensitivity analyses were performed to illustrate the impacts on reliability indices of operational failure of the automation units of the implemented automation scheme. The results presented indicate the benefits of employing the automatic loop restoration scheme for reliability improvement of urban distribution feeders.

VII. ACKNOWLEDGMENT The first author gratefully acknowledges the financial

support received from the Fortum Foundation.

VIII. REFERENCES [1] R. Bilinton, and R. N. Allan, Reliability Evaluation of Power Systems,

Plenum Press, 1996, 2nd Ed. [2] R. E. Brown, Electric Power Distribution Reliability, CRC Press, 2009,

2nd Ed. [3] R. E. Brown, A. P. Hanson, H. L. Willis, F. A. Luedtke, and M. F. Born,

"Assessing the reliability of distribution systems," IEEE Computer Applications in Power, vol. 14, pp. 44-49, January 2001.

[4] D. G. Hart, D. Uy, J. Northcote-Green, C. LaPlace, and D. Novose, "Automated solutions for distribution feeders," IEEE Computer Applications in Power, vol. 13, pp. 25-30, October 2000.

[5] J. Northcote-Green, and R. Wilson, Control and Automation of Electric Power Distribution Systems, CRC Press, 2007, 1st Ed.

[6] S. Kazemi, M. Fotuhi–Firuzabad, and R. Billinton, "Reliability assessment of an automated distribution system," IET Generation, Transmission and Distribution, vol. 1, pp. 223-233, March 2007.

[7] S. Kazemi, M. Fotuhi–Firuzabad, and M. Lehtonen, "Reliability worth assessment of an advanced centralized feeder automation scheme," In Proceedings of the IEEE 8th Annual Electrical Power Conference 2008, EPEC2008, Vancouver, Canada, 6-7 October 2008, pp. 1-8.

[8] S. Kazemi, M. Fotuhi–Firuzabad, M. Sanaye-Pasand, and M, Lehtonen, "Impacts of loop restoration strategy on distribution system reliability," In Proceedings of the 2009 IEEE Bucharest PowerTech Conference, Bucharest, Romania, 28 June - 2 July 2009, pp. 1-8.

[9] S. Kazemi, M. Fotuhi–Firuzabad, M. Sanaye-Pasand, and M. Lehtonen, "Impacts of automatic control systems of loop restoration scheme on the distribution system reliability," IET Generation, Transmission and Distribution, vol. 3, pp. 891-902, October 2009.

[10] M. Jakobsson Ueda, O. Engblom, and K. Alvehag, "Representative test systems for Swedish distribution networks," In Proceedings of the 20th IEEE International Conference and Exhibition on Electricity Distribution (CIRED 2009), Prague, 8-11 June 2009, Paper No. 0837 pp. 1-4.

[11] K. Kivikko, P. Järventausta, A. Mäkinen, A. Silvast, P. Heine, and M. Lehtonen, "Research and analysis method comparison in Finnish reliability worth study," In Proceedings of the 19th IEEE International Conference and Exhibition on Electricity Distribution (CIRED 2007), Vienna, May 2007, Paper No. 0542, pp. 1-4

IX. BIOGRAPHIES Shahram Kazemi (GSM’09) received the B.Sc. Degree (Honors) in Electrical Engineering from University of Hormozgan, Bandar-Abbas, Iran in 2002, and the M.Sc. Degree (Honors) in Electrical Engineering from Sharif University of Technology, Tehran, Iran in 2004. From 2003 to 2006, he has been with Niroo Consulting Engineers Co., Tehran, Iran, as a senior researcher. He is currently working toward the Ph.D. and D.Sc. Degrees in Electrical Engineering respectively at Sharif University of Technology, Tehran, Iran and Aalto University

School of Science and Technology, Espoo, Finland. His research interests include Power System Reliability and Power System Protection, Control and Automation.

Matti Lehtonen received the M.S. and Licentiate Degrees in electrical engineering from Aalto University School of Science and Technology (formerly Helsinki University of Technology), Espoo, Finland, in 1984 and 1989, respectively, and the D.Sc. Degree from the Tampere University of Technology, Tampere, Finland, in 1992. Since 1987, he has been with VTT Energy, Espoo, and since 1999, he has been with Aalto University School of Science and Technology, where he is a Professor of IT applications in power systems. His main activities

include earth fault problems, and harmonic related issues and applications of information technology in distribution automation and distribution energy management.

Mahmud Fotuhi-Firuzabad (SM’99) obtained the B.Sc. and M.Sc. Degrees in Electrical Engineering from Sharif University of Technology and Tehran University in 1986 and 1989 respectively and M.Sc. and Ph.D. Degrees in Electrical Engineering from the University of Saskatchewan, Canada, in 1993 and 1997 respectively. Dr. Fotuhi-Firuzabad worked as a postdoctoral fellow in the Department of Electrical Engineering, University of Saskatchewan from Jan. 1998 to Sept. 2000. where he conducted research in the area of power system reliability. He

worked as an assistant professor in the same department from Sept. 2000 to Sept. 2001. Presently he is a professor and Head of the Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran. He is a member of center of excellence in power system management and control.