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IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 22, NO. 2, MAY 2007 597
Selective Maintenance Schedule of DistributionNetworks Based on Risk Management Approach
Aleksandar D. Janjic , Member, IEEE , and Dragan S. Popovic , Member, IEEE
Abstract—This paper presents a methodology for optimal long-term maintenance schedule of distribution networks. The method-ology is based on risk management approach and the new model of decoupled risk factors and state transition based on decision treediagram. Risk approach provides more realistic modeling of com-ponent failure and estimation of expected consequences, while de-coupled risk factors enable definition of selective plan for preven-tive actions. Theproposed methodology is testedon a real overheaddistribution network, but it can be used for other parts of distribu-tion system as well. Obtained results have shown that the expectedcosts of distribution network maintenance can be reduced and therisk of emerging of significant operation costs minimized, by de-
tailed and realistic modeling of risk factors. Index Terms—Distribution network, dynamic programming,
maintenance schedule, risk management.
I. INTRODUCTION
MAINTENANCE schedule of distribution system is
timely action plan with purpose to extend life cycle of
the system, in order to reduce overall operation costs. Mainte-
nance is closely related to reliability. If maintenance actions
are performed rarely, it can cause a large number of faults and
outages, while done too often, costs will be greatly increased.
Therefore, it is necessary to make an appropriate balance
between maintenance costs and outage duration costs. Two
main approaches in the maintenance strategy determination are
a) corrective, or “run to failure,” approach and b) preventive
maintenance. Preventive maintenance strategies may be further
divided into several different types: scheduled maintenance,
condition based and Reliability centered maintenance (RCM).
Risk based maintenance can also be considered as a special
case of RCM. Overview of status in application of various
maintenance strategies is provided in report of IEEE Task
Force [1].
According to mathematical model, or definition of objective
function, maintenance schedule problem is developed in four di-
imization; 3) overall costs minimization; and 4) overall risk
minimization.
In the first approach, the criteria function is defined as the
minimum of maintenance costs [2]. Reliability is defined as a
Manuscript received July 12, 2006; revised October 27, 2006. This work wassupported in part by theDMS Group,Ltd.,NoviSad, Serbia. Paperno. TPWRS-00419-2006.
A. Janjic is with the Electric Power Industry, Belgrade, Serbia. (e-mail:[email protected]).
D. Popovic is with DMS Group Ltd., Novi Sad, Serbia (e-mail:[email protected]).
Digital Object Identifier 10.1109/TPWRS.2007.894863
limit, or minimal requested level. In the second approach, an
optimal maintenance strategy is determined that achieves the
highest reliability of the system, or EENS indexes [3], [4].
In the third approach, in the criteria function, beside mainte-
nance costs, reliability costs are added as well (costs of outage
frequency and duration from the consumer’s side) [5]–[8]. More
flexible models, that enable the combination of minimizing cost
for a given reliability and maximizing reliability for a given cost
[9], or cost benefit analysis, are also developed [10]–[13].
Risk management based maintenance is the latest approach
based on evaluating risk of equipment failure and consequencessuch failure can produce of functioning of the system [14]. In-
troducing the risk approach provides more realistic modeling
of equipment failure and estimation of expected consequences.
More precisely, quantification of risk enables determining an
optimal levelof risk that provides the most efficient maintenance
strategy for distribution networks.
In all of the above mentioned approaches, usually only one
kind of maintenance action has been analyzed -replacement or
repair of a particular component [2]–[4], [7], or just one specific
activity (inspection, tree trimming [8], [9]. Long term planning
is performed either by determining fixed time intervals [4]–[7]
or from year to year by quasi-dynamic approach [8], [9]. On the
other hand, prioritizing of maintenance activities does not pro-
vide a global optimum of costs [10]–[13]. Finally, in [15] is pro-
posed the model of decoupling risk factors and related preven-
tive actions, but in this model simultaneous treatment of more
components and risk approach has not been used. In a method-
ology for determining optimal maintenance strategy, it is there-
fore necessary to define a model that would unite following de-
mands: 1) decoupling risk factors and related preventive actions,
2) determining strategy for long term period, and 3) simulta-
neous treatment of more components. This paper is dedicated
to these problems.
The proposed methodology in this paper determines an op-
timal plan of actions for multiyear maintenance schedule. It isbased on the risk approach and the model of decoupled failure
risk factors in distribution network. Risk approach enabled more
realistic modeling of component failure and estimation of ex-
pected consequences, while decoupling risk factors provided an
overview of quantitative influence of individual risk factors to
reliability and determining the optimal plan of selected actions
that have impact to individual risk factors. Within that method-
ology, the new model of state transition based on decision tree
diagram is also proposed. New state variables – number of years
since the last repair for each preventive maintenance action have
been introduced into this model. Introducing these new vari-
ables provides a simple modeling of state transition, as well as
604 IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 22, NO. 2, MAY 2007
price of used material necessary for fault
elimination;
number of working hours necessary for fault
elimination;
average duration of unplanned outage (fault);
cost per MVA of undelivered power for unplanned
outages;rate of average towards maximum power on the
line.
(A.6)
failure rate on feeder in year ;
failure rate depending on defects that could be
observed during inspection;
failure rate depending on branches grown in
feeder conductors;
failure rate depending on defects that could be
eliminated by overhaul.
(A.7)
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Aleksandar D. Janjic (M’00) was born in 1966. He received the B.Sc. degree
in 1989 and the M.Sc. degree in 1999, both from the University of Belgrade,Yugoslavia.
He is currently working in the electric power industry in Serbia. His researchinterests are distribution systems planning, automation, and distribution man-agement systems.
Mr. Janjic is chairman of the distribution planning session of the CIREDNational Committee.
Dragan S. Popovic (M’95) received the B.Sc. degree from the University of Novi Sad, Yugoslavia, in 1985, and the M.Sc. and Ph.D. degrees from the Uni-versity of Belgrade, Yugoslavia, in 1990 and 1995, respectively.
He is currently a Professor with the Faculty of Engineering, University of Novi Sad. He has worked for many years in researching fields of bulk powersystem analysis, control, and stability. Presently he is engaged in researching
and developing application software for distribution management systems. Hehas also been the Project Manager on several projects in the field of distributionautomation and distribution management system.