Decision support for maintenance managent of high voltage components

Decision Support for Maintenance Management of High Voltage Components

Quak*,

Delft University ofTechnology, The Netherlands *E-mail:

b.quakgewi.tudelft.nl

in the power network are capital intensive assets, which force the owners of these assets to utilise them inthe mostefficientway. Efficient utilisation demands athorough analysis of the relation between the assets performance and the stakeholders' expectations. To support electrical engineers in the interpretation of diagnostics onbehalf ofassessmentof the condition of high voltage components, and to aid the asset management in above mentioned analysis, linkage between different information domains has to be brought about to generate the required decision knowledge. Because of the large amount of components, the diversity of component types and measurement data, information systems areneeded for storage, correlation and comparison of measurement

data on specific components and specific component types. Nowadays, however, decisions will have to be based on more than this technical information alone. Amore integralapproach is required, paying attention to all stakeholders' expectations. Thispaper discusses research performed on modelling the asset management decision process to provide support during the decisionprocess.

INTRODUCTION

When pursuing optimal economical performance

decisions have to be made about which of all the possible maintenance or investment actions are the

correct ones. Simply put, this canbe seen as decision process, where decisions are made on technical, economical and societalinformation. However, this is

acontinuousprocess,asdecisions influence thesystem,

Technical Information .-- -Economical Information 1 (on assets) . Economical Information 2 (on business) Societal Information

Figure 1: Asset maintenance management decision processonthree levels

and therefore influences at least the technical and

economical information on which the decision is based.

Looking in more detail, this decision process can be seen as build of three separate levels, as illustrated in figure 1.

The first level deals with the technical information; the second level uses the results of the first level and the economical informationonassets,while the third level combines this with the economical information on

business and societal information.

A way to approach this separation is to think of the first level, which consists of technical information and is mainly focussed at components, as the component level.

The second level, which combines the economic information on assetswith the results of the first level, has more focus on the level of the network (the reliability and operational performance), while the third leveluses the economic information onbusiness combined with the societal information, to make decisions about risk which have mainly a corporate focus.

From atechnicalpoint ofview, multiple scenarios can be found to influence the performance ofassets. For example, scenarios could be in- or decreasing maintenance and inspection intervals, replacement or

refurbishment, but also about changing the maintenance strategy from corrective maintenance to

time basedorcondition based maintenance.

The scenarios are found by analysis and combination of the equipment inventory, the maintenance actions already performed onthe equipment, the current rules that exist for maintenance, and condition assessment, that results from diagnostics, in combination with statistical evaluation of practical failure cases, reliability evaluation andageing models result.

All these scenarios will have a different effect onthe technical performance (in terms of reliability and availability) of the asset. At this stage, scenarios should not be excluded based on their effect on

technical performance, because in the next levels, the scenarios will be combined with other relevant data,

whichevenmaycause ascenario withanegative effect

on technical performance to be the most economic while having the smallest risk. The stakeholders' expectations for example will be taken into account at

the third level.

Combination of the technical information of the scenarios with relevant economic data fromunderlying

economic systems will result in a quantification of benefits andcostsof each scenario. These benefits and costs are notexclusively expressedineconomicterms, but could also be expressed in other terms such as reliability orexpected lifetime. Forexample, enlarging aninspection intervalmay cause abenefitindecreased expenditures, but could have costs in terms of decreasedreliability.

Onthe otherhand, shortening the interval might have costs in increased expenditures, but could lead to benefitsinincreasedreliability.

Useful decision support tools should address all the categories information and different levels in the decision process. The tool should support the asset manager in his decision process, aiding the asset manager totake his decision supported by the tool. In the past decisions related to asset utilisation were mainly basedonthe technicalperformance of theasset. After some years the ratio between technical performance and expenses became a relevant parameter in the decision process. Currently it is also important to look at the effect the utilisation of the

asset has on its environment. However the above decision process shows that the technical information isatthe base of the decisionprocess and still ofmajor importance. Conditionassessmentinformation isone of themajor technicalaspects.

DATABASED CONDITION ASSESSMENT To support electrical engineers inthe interpretation of diagnostics onbehalf ofassessmentof the condition of high voltage components, linkage between the following information domains hastobebrought about

togeneratetherequired decision knowledge:

1. Componentdomain; consisting of specific insulation characteristics of theassetstructure;

2. Diagnostic domain; consisting oftypeofdiagnostics applied; e.g. general condition assessment, weak-spots assessment;

3.Measuring data domain; defining specificdiagnostic quantities used during conditionassessment.

Because of the large amount of components, the diversity ofcomponent types and measurement data, informationsystemsareneeded forstorage, correlation and comparison of measurement data on specific components and specific component types. To assess

the condition ofcomponents:

a) suitable parameters should be selected that give an

indication of thecomponentshealth,

b) inspections andmeasurements should be performed

toobtain data about theseparameters,

c) levels should be defined that trigger inspection, maintenanceorreplacement actions. [1,4]

Normally components are manufactured with optimal

condition. Ageing oforassembly faultsmayresult in a degradation of materials. Component and material specific parameters (e.g. partial discharge related parameters in case of insulation condition) may provide indication of such degradation. Inspections and measurements should be carriedout toobtain data about these parameters. To monitor the condition of components, suitable parameters should be selected. The selected parameters must give an indication of the componentshealth.

Besides the results from diagnostics, a reference is necessary to interpret the results. From this reference knowledge rules can be extracted with respect to the availability and remaining lifetime from components. Finally levels (Norms) should be defined that trigger inspection, maintenanceorreplacement actions. However, to determine discerning critical levels for this information, knowledge and (historic) information about components are necessary. Diagnostics applied

to medium voltage power cable in particular, these levelscanbe obtainedin two ways:

a) forensic evidence research,or

b) statistic analysis of historical andtyperelated data. Forensic evidence research obtains the levels from 'post-mortem' research on (possibly artificial) aged components. This kind ofinvestigation supplies results about one single failure eventper investigated sample

so theknowledgeonhowto estimate thetrigger levels increases slowly. In addition, it is not possible to investigate and predict all the possible failure mechanisms occurring in practice. However, this method also gives more knowledge about the physics behind failure mechanisms, gaining insightonhowto

increase quality of future products.

Statistical analysis of historic measurement and inspection data to establish the trigger levels give an alternative approach. In particular, by using statistical analysis overall behaviour is taken into account.

Interpretation by physics is important, but most assets are complexsystems inthatregard. This complexity is due to the variety inmaterials used, component ages, appliedstressesand installationworkmanship.

Database support in combination with data mining offers nowadays an easy opportunity for the second methodinobtaining relevant information for condition

assessment. Mostinformation will be already available in digital formats and by storage of diagnostic quantities in a database, not only analysis can be

components can be easily selected for inspection, maintenance or replacementactions.

DECISION SUPPORT

what extend the different advisable options match the at~

Nowadays, however, decisions will have to be based on more than technical information alone. A more integral approach is needed, paying attention to all stakeholders' expectations[ 1-8]. Research has been performed on modelling the asset management decisionprocess toprovidesupportduring the decision process. The model was developed to provide a structured approach in making decisions. This way it assures that all aspects and categories of importance will be taken into consideration every time a decision has to be made. Based on an interactive template, the model provides support in profiling the asset owners' demands, and in assessment oftechnical, economical and societalstatusof theassets. Furthermore the model helps out inthe selection of integrated analytical tools to model the effects on, and the interaction between: reliability and availability, spare part provision, maintenance activities and intervals, operational load, conditionassessment, remaining technical lifetime and benefits and costs. A practical implementation in the field of medium voltage power cable networks is discussedto illustrate theuseof the model.

Within the decision supportmodel three stages[7] can

bedefined (Fig. 2): 1. Input stage 2. Analysesstage 3. Decisionstage

During the inputstageall thenecessaryinformation for the different types of assessment is gathered. The model enables a thorough assessment in three categories:

* technical, * economical and * societal

In the following stage, the analyses stage, statistical analyses ofe.g. the availability and the reliability are

conducted. Finally, the decision stage provides the

assetmanager witha setofpossibleoptions to choose from in order to meet the stakeholders' demands. Initially the model was only applied on distribution powercableconnections, so asof thispoint theaspects and factors usedapplytothecaseof distributionpower cable.

Input stage

Profiling First step inthe decision supportmodel isto get aclear view of thetype of advise that is sought by theparty (e.g.: assetowner) whichoperates on behave behalf of the stakeholders. The advice generatedatthe end of the modelserves as a mean to anend, soduring the profiling stage the end is defined. The data obtained from the profiling is thus used to verify to

A

Figure 2: Flowchart

supportmodel of the asset management decision

assetowner'sgoals and objective.

Technical Assessment The technical performance of theassetis determinedby five key factors:

1. the condition(e.g.: insulation condition) 2. the loadprofile

3. theasset structure 4. theredundancy

5. the environmental factors

The assetis ratedonall thesefive factors. The adopted ratingsystemisasfollows:

* category 1:bad * category 6:moderate * category 9:good

Aside from therating of the factors, the factorsarealso givenaweight. Depending onthetype ofcompanythe weight of the factors can differ, there the model enables the user toapply weights which best supports the company'spolicy. The combination ofthe rating of the factors and the weights, results in a technical output diagram (Fig 3a). The diagram illustrates the technical performance of the asset based on the key factors and their weights. Again the three category ratingsystemisadopted.

Economical Assessment Several scenarios [8] concerning maintenance on components can be distinguished. The model uses a similar set of maintenance scenarios. The economical assessment is conducted by analysing the expenses related to these scenarios. The scenarios usedare:

* Runtill end

* Upgrade (partial replacement) * Immediate fullreplacement * Delayed full replacement

The scenariosare comparedtoeach otherby analysing theirnet present values (NPV). The scenario with the highestNPV is selected as being the most profitable.

As in the case of distribution power cable the benefits of all possible scenarios are not determined by the cable but by its environment, only the expenses are taken into account. In the presented model the following factors play a key role during the economicalassessmentstage:

* meantimetofailure (MTTF),

* expenses (failure, maintenance and decomposition expensesand investmentscostofa newasset),

* technicalremaining life time * time frame forNPVanalysis.

Technical -4)

AI

The economicalassessmentproduces adiagram of the categorized annual and cumulated discounted cash flow and eventually selects the scenario with highest NPV. Because only the expenses are being taken into consideration, the scenario with the least negativeNPV value will be selected. Fig. 3b illustrates aneconomical

assessment output diagrams for one of the four

scenarios. In case of scenarios with almost identical NPVs the categorized annual discounted cash flow becomes ofmore importance. Bytheinspection of the annual discountedcash-flow, and its categorized origin, acertain scenariocanbemorepreferredthan others.

Societal Assessment The societal assessment is conducted in thesameway asthe technicalassessment. Thekey factors for the societalassessmentare:

1. Number of connections 2. Type of connections

3. Humansafety (public andemployees) 4. Environmental hazards

The output diagram for the societal assessment is the same as the technical assessment output diagram and generatedinthesame manner.

Analysesstage

During this stage all the data attained from the input stageisanalysed by usingasetofanalytical equations. To be able to estimate the availability of the asset

based on its condition, Markov processes are

calculated. Also the failure probability and hence the reliabilityare calculated basedonthe condition data. A

part from availability and reliability analyses, spare

part provision can also be important in the decision making process concerning the asset. Based on the

current condition of the asset the model assesses the optimalamountofsparepartstohave instore.

Decision stage

To verify that the model can be used in the decision making process, the model was implemented for

distribution power cable connections. This exercise

showed that the results attained can assist the asset manager in the decision making process, but it also

showed some interesting relations.

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0 10 20 30 40 50

Socetal

-SEAs orecurye MtuaISEAv[de

Categoybor Ir

QalcOo7ryboFdcr

0 50 100 150

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Figure 3: Example of output of a decision support tool addressing the three categories of information technical,

economical and societal.

Influence of FactorsontheOutput

By applying the model on MV cable connection interesting relations between the factors and the outputs could be attained. Themostinterestingrelation from condition assessment point of view is the influence of the insulation conditiononthe economical

output. The data relatedtoacertain distributionpower

cable connection in first instance showed that when the insulation condition is bad the best economical scenario is to upgrade the asset. When the insulation condition is improved partially (from category badto

category moderate) the output of the economical

vTA scrcu

dua ITA NOlu

t

assessment is still scenario two (upgrade), but the differenceineconomicaltermsbetween upgradingand doing nothing has become less. The output of the economical assessment changes when the condition becomes good. Figures 3 and 5 illustrate the influence of the conditiononthe economicaloutput.

Figure 4: Intluence of the bad condition on the economical output

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.~~~~~~~~~W*_bw aw

Figure 5: Influence of the good condition on the economical output

CONCLUSIONS

-The informationaspects ofAM decisionprocess can be divided into the three categories: technical, economical and societal.

- The decision process itself can be regarded as

consisting of three separate levels: component,

network andcorporate.

-Whenanimplementation ofanAM decisionprocess (or the supporting decision support tools) does not coverthe allaspectcategories of information and all of the threelevels, the main goal of AM, finding the best balance between component performance and stakeholders' expectations, willnotbe reached, which probably will not lead to the highest efficiency possible.

- Database support, in combination with data mining, is an important element in obtaining relevant information for condition assessment of assets. By

storage of the relevant parameters in a database, analysis can be performed to extract additional information not shown by single measurementsonly. - Based on this information, decisions can be made about levels for updatingormaintenance.

- When these levels are applied on the database as norm levels, components are easily selected for inspection, maintenance or replacementactions. - The use of presented model makes the decision process more transparent for both the asset manager as wellashis environment. This allows theassetmanager to clarify his choices and to better explain why one typeof action ispreferred above another.

- The model can simulate the effects of for example increasing or decreasing maintenance intervals and what influence this choice will have on the overall performance (technical, economical and societal) of theasset.

-As anbenefit, the use of a model guarantees aunified decisionprocesstaking intoaccountall relevant factors and aspects every time a similar decision has to be made.

REFERENCES

[1] J.J. Smit "Decision making experience with maintenance diagnosis of high voltage equipment", 37thCigre session, Paris 1998, paper 15-105.

[2] E.Gulski, J.J. Smit, J. Maksymiuk, Asset Management of electrical power grids, Book 150 pages, Publishing House of the Warsaw University of Technology (2004,ISBN 83-7207-522-0

[3]Ph. Wester, B. Quak,E.R.S.Groot, E. Gulski& J. J. Smit, 'Impact of Condition Based Maintenance on Asset Management', Cigre SC23 Colloquium 2001, Venezuela,paper 1.6,2001.

[4 ] A. G. Starr, "A structured approach to the selection of condition based maintenance", Factory 2000 - The Technology Exploitation Process, Fifth

International Conference on, 2-4 April 1997, paper 435.

[5] D. Kopejtkova, H.P. Ott, H.Rossler, F.Salamanca, J.J. Smit, A. Strnad, Ph. Wester, "Strategy for condition-based maintenance and updating of substations", 36th Cigre, Paris 1996,paper 23-105. [6] J.McGrail,, E. Gulski,E. R. S.Groot,D.Allan,D. Birtwhistle, T.R. Blackburn, "Datamining techniques

to assessthe condition ofhigh voltage electricalplant" Cigre Paris,WG15.11 paper, 2002

[7] G.J. Frijmersum, B. Quak, E. Gulski, J.J. Smit, "Asset Management Decision Support Model for Distribution Power Cable", ISH 2005, Beijing, paper T06-100