Novel Decision Support System for Underground Power Network Asset Management Asawin Rajakrom CAMT, CMU August 29, 2009

Novel Decision Support System for Underground Power Network Asset Management

Asawin Rajakrom

CAMT, CMU

August 29, 2009

Problem and Justification

69/115 kV Customer

230/500 kV

Grid Station

Substation

Power Plant

12/24 kV Customer

12/24 kV

220/380 V Customer

69/115 kV

220/380 V

Problem and Justification Failure of distribution feeder directly impacts end users’

wellbeing Concerns on safety, health, environment and aesthetics

are increasingly high Network equipment is reaching its designed service age Overhead feeder facilities are vulnerable to external

environment Investment on feeder rehabilitation is extremely high Better decision making of utility asset management can

be obtained through a sort of DSS that can incorporate all impacted factors: technical, economical, societal, and environmental aspects.

Research Questions How shall the power distribution domain knowledge

be modeled? How can the risks of distribution network failure be

efficiently assessed? How can the costs involving network failure and

preventive action be quantified? How can the social and environmental consideration

be included in investment decision?

Key Assumptions Conversion of overhead distribution line into underground

feeder is of the prime concern. Risk assessment is solely based on the performance of

network components, not considering any other aspects such as network configuration, or operating process (e.g. switching philosophy).

Snap shot comparison, investment cost of network reinforcement at the time of network failure is of interest and compared with the cost of failure.

Available data are of sufficient quality to enable assessment modules to predict corresponding outputs/outcomes.

DSS tries to replicate the decision making of human experts so that the utility expert’s judgment are assumed sufficient to validate the models.

Publications1. “Improvement of Underground Cable Installation

Performance by Knowledge Management”, the 16th Conference of the Electric Power Supply Industry, Mumbai, India, 2006.

2. “Asset Categorization for Enhanced Asset Management Using Object Oriented Approach”, the 16th Conference of the Electric Power Supply Industry, Mumbai, India, 2006.

3. “Enhance Decision Making on Underground Power System Implementation Using MCDA”, the 16th Conference of the Electric Power Supply Industry, Mumbai, India, 2006.

4. “Underground Power Line Risk Assessment Using Heuristic Approach”, the 1st Software, Knowledge, Information Management and Applications, Chiang Mai, Thailand, 2006.

Publications5. “Fuzzy Risk Assessment for Distribution System Asset

Management”, Presented at the Conference of Asian Energy Week 2007, Bangkok, Thailand, 2007.

6. “Fuzzy Multicriteria Approach for Power Distribution System Risk Analysis” , Presented at Energy21C: The 10th International Transmission and Distribution Conference & Exhibition, Sydney, Australia, 2007.

7. “Determination of Power Distribution Network Risk Using Fuzzy Markov”, the 2nd Software, Knowledge, Information Management and Applications, Kathmandu, Nepal, 2008.

8. “Asset Modeling To Support Cost-Risk Evaluation In Distribution System Asset Management”, the 17th Conference of the Electric Power Supply Industry, Macau SAR, China, 2008.

Methodologies and Tools Asset categorization

CommonKADS Categorization and Assessment template

Ontology 101 UML CIM/RDF/XML

Risk assessment: Fuzzy logic Markov chain MS Excel

Methodologies and Tools Cost evaluation:

Interrupted energy rate (IER) Work breakdown structure (WBS)

Multicriteria Decision Analysis: Analytic Hierarchy Process (AHP)

Tools: Protégé 2000 MATLAB MS Excel

DSS FrameworkM

ark

ov

Chain

Distress indicators

FIS Present Asset Condition

Future Asset Condition

Deterioration Rate

Initial Asset Condition Operational

Environment

FIS

FIS

Present/Future Failure Likelihood

Expected Repair Time

Connected Load

IER

x

-

Customer

xPrice Cap

Repair CostUtility

Outage Cost

+

Upgrade

Replacement

Conversion

vResolution Cost

MC

DA

(AH

P)

Invest

ment

Opti

on

x Financial Index

Public Interest

Technical Matter

Asset Categorization

Risk Module Decision Module

Cost Module+

Age

Asset Categorization

AssetnamedescriptioncommissioningDate

ComponentmaterialCodematerialDetail

AssetContainer

ImplementationCostnamedescriptioncommissioningDate

ConditionGradenamegradeinspectionDaterelativeImportanceDegree

FeederampacityratedVoltagepredictedFailurePotentialexpectedFailureDuration

PointComponent

LocationnamecoordinateXcoordinateY

FailurefailureDescriptionfailureDatefailureTimefailureDuration

OutageCostcostOfOutage

InvestmentCriteriadegreedescription

CustomercustomerIDcustomerTypeIERkWpriceCap

Stressordegreedescription

has has

locateAt

supplyhas

operateIn hashas

isis

is

iscompose

compose

AssetnamedescriptioncommissioningDate

ComponentmaterialCodematerialDetail

AssetContainer

FeederampacityratedVoltagepredictedFailurePotentialexpectedFailureDuration

ComponentGroup

OverheadLine UndergroundLine

PoleAssembly CableComponentConductorAssembly

CableContainerLightningProtection

UndergroundSwitches

CircuitSwitches

LinearComponentlength

Conductor

OHConductor UGCable

DuctBank

PointComponent

Pole

Manhole

UGCable

Splice

Splice

Duct

Manhole

Rack

Pole

Guy

Crossarm

Fittings

Arrester

Groundwire

Switches

Recloser

FuseCutout

Splice

Insulator

Conductor

RMU

ATS

UnitSubstation

Simulation

Simulated Feeder

3 MW Industry

T1: 4,000 kVA

T4: 2,500 kVA

T6: 4,000 kVA

T2: 3,000 kVA

T3: 2,000 kVA

2 MW Commercial

T5: 2,500 kVA

Substation 24kV bus1 2 3 4 5 6 7 8 9 10 11 12 13

14

15

16

17

18

19

20

21

22

23

24

25

26LS3

T1 T2 T3

T4

T5

T6

Substation

SimulationFeeder Condition Grade:

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 10 20 30 40 50

Serviced Year

Con

ditio

n G

rade

SimulationFailure Rate Contributed by Feeder Condition:

0%

10%

20%

30%

40%

50%

60%

0 5 10 15 20 25 30 35 40

Serviced Year

Failu

re R

ate

SimulationFinancial Analysis of Alternative Options:

-

1.00

2.00

3.00

4.00

5.00

6.00

7.00

0 10 20 30 40 50

OutageByDeterioration(Benefit)

OutageByTree(Benefit)

Bare(Cost)

ASC(Cost)

UG(Cost)

SimulationInvestment Decision Hierarchy:

Select the Most Suitable Feeder Rehabilitation

Technical Financial Social

Reliability

Bare OH

ASC OH

UG

Construction Maintenance Aesthetics Safety

Bare OH

ASC OH

UG

Bare OH

ASC OH

UG

Bare OH

ASC OH

UG

Bare OH

ASC OH

UG

Bare OH

ASC OH

UG

SimulationRanking of Investment Options:

CriteriaSignificant

WeightBare OH ASC OH UG

Reliability 0.0901 0.0548 0.3583 0.5869

Construction 0.0110 0.4545 0.4545 0.0909

Maintenance 0.0274 0.4545 0.4545 0.0909

Finance 0.5949 0.4899 0.4507 0.0594

Safety 0.2075 0.0698 0.1659 0.7644

Aesthetics 0.0692 0.0909 0.0909 0.8182

Overall marks (%) 33.46 35.85 30.69

Feeder Condition Grade:

0

0.2

0.4

0.6

0.8

1

1.2

0 10 20 30 40 50

Year

Co

nd

itio

n G

rad

e

Case Studies: Feeder Rehabilitation in Industrial Estate

Feeder Failure Rate:

1.49

1.50

1.51

1.52

1.53

1.54

1.55

1.56

1.57

1.58

0 5 10 15 20 25 30 35 40

Year

Failu

re R

ate

(tim

es/y

ear)


Financial Analysis of Alternative Options:

-

2.00

4.00

6.00

8.00

10.00

12.00

14.00

0 5 10 15 20 25 30 35 40

Year

Mill

ion

Bah

t Outage

ASC OH

UG


Investment Decision Hierarchy:

Select the Most Suitable Feeder Rehabilitation

Technical Financial Social

Reliability

ASC OH

UG

Construction Maintenance Aesthetics Safety

ASC OH

UG

ASC OH

UG

ASC OH

UG

ASC OH

UG

ASC OH

UG



Ranking of Investment Options:

CriteriaSignificant

WeightASC OH UG

Reliability 0.4580 0.1429 0.8571

Construction 0.0557 0.8333 0.1677

Maintenance 0.1392 0.8333 0.1677

Finance 0.2510 0.9000 0.1000

Safety 0.0720 0.1429 0.8571

Aesthetics 0.0420 0.1000 0.9000

Overall marks (%) 46.65 53.35

Case Studies: Undergrounding Feeders in World Heritage Site

Particular Requirement:

Criteria Subcriteria DescriptionTechnical Reliability Well protection and well performance of network equipment

Installation Simplicity of construction and installation of duct, cable, switchgear and transformer including less adverse effect to public sector

Maintenance Convenience of underground network maintenance (inspection, repair, replacement) and operation

Extension Network expansion (new substation connected) and new customer connection can be achieved with ease

Conversion process Simplicity of conversion step from existing overhead to underground) as well as including less adverse effect to customers and public in vicinity.

Aesthetic The network shall be in harmony with the cityscape and existing construction

Safety Safety to employees and public communityCost Cost of implementation; this cost will eventually be borne by

every stakeholder


Investment Decision Hierarchy:

Select the Most Suitable Underground System

Technical Cost Aesthetics

Reliability

DR-CS

DR-US

DB-CS

Installation Maintenance

DB-US

Extension Conversion

DR-CS

DR-US

DB-CS

DB-US

DR-CS

DR-US

DB-CS

DB-US

DR-CS

DR-US

DB-CS

DB-US

DR-CS

DR-US

DB-CS

DB-US

DR-CS

DR-US

DB-CS

DB-US

DR-CS

DR-US

DB-CS

DB-US


Ranking of Investment Options:

CriteriaSignificant Weight

DR-CS DR-US DB-CS DB-US

Reliability .1183 .0477 .1080 .2588 .5854

Construction & installation

.0453 .0732 .1969 .1969 .5330

Maintenance .0534 .0569 .1219 .5579 .2633

Extension .0159 .3750 .1250 .3750 .1250

Conversion procedure .0275 .1250 .1250 .3750 .3750

Aesthetics .6333 .3750 .1250 .3750 .1250

Cost .1062 .5579 .2633 .1219 .0569

Overall marks (%) 31.81 14.08 33.61 20.50

Conclusion and Future Work Asset model of expressivity, interchangeability,

extensibility, reusability and integratability Human expert emulation of risk assessment Balancing of risk, cost and performance of asset

through MCDM mechanism Proposed approaches can be extended to cover other

area such as: Rehabilitation of transmission lines or substations Risk assessment of underground cable system

Thank you

Asset Categorization Purpose: To determine risks, costs and socials

factors associated with the implementation of power distribution network.

Domain: Encompass medium voltage distribution feeder including network components, network operation, and operational environment

Scope: Limited to information that aids determining risks, costs and socials factors involved with distribution feeder.

Asset CategorizationInformal description: Distribution feeder is used to carry electric current through

electrical wire. Distribution feeder runs along public road. Overhead feeder is an electrical wire laying or hanging on

insulator which in turn supported supporting structure. Failure occurs when feeder fails to perform an intended

function such as carrying electric current, withstanding presence voltage, threatening the living standard.

Power utility does not gain revenue due to unavailability of energy sale when feeder fails.

Burying distribution network improve city aesthetics. etc.

Asset CategorizationClasses and Attributes: Pole is a distribution network component Material cost of pole is 8,104.00 baht. Labor cost of pole installation is 8,376.80 baht. Condition grade of pole inspected on March 20, 2009 is 1.8. Feeder comprises of overhead cable and underground cable. Feeder PI417 supplies Imperial Hotel. etc.

Asset CategorizationClasses and Attributes:

FeederAssetContainer

name

Asset

name

Component

code

commissioningDate

unitPrice

Conductor Insulator Pole

is

is

is isis

contains

Risk AssessmentCondition Grade of Distribution Assets:

Grade Description Verbal Grade

1No noticeable deterioration. Some aging may be visible

good

2Some deterioration is evident, but the function of component is not significantly affected.

Adequate

3Moderate deterioration. Ability to function is adequate.

Fair

4Serious deterioration. Ability to function is significantly affected.

Poor

5Severe deterioration. General failure or a complete failure of component

Failed

Risk AssessmentFeeder Component Categories and Contributing Weight:

Category i Weight (Wi)

Component i,j Weight (Wi,j)

Pole structure 1 5 Pole 1,1 4Crossarm 1,2 3Guy 1,3 3Fittings 1,4 3

Conductor assembly 2 5 Conductor 2,1 5Insulator 2,2 5Splice 2,3 3

Lightning protection 3 2 Overhead ground wire 3,3 3Lightning arrester 3,2 5

Circuit protection 4 8 Fuse cutouts 4,1 3Switch 4,2 5Recloser 4,3 3

Risk AssessmentCategory and Overall Condition Grade:

Hj = [W1j …Wij … WNij]*[C1j… Cij… CNii]

Cij is condition grade fuzzy set of each distress indicator

Wij is scalar normalized weight given to each distress indicator Hj is condition grade fuzzy set of category

C = [W1 …Wi … WM]*[H1… Hj… HM]

Hj is condition grade fuzzy set of cateogory Wj is scalar normalized weight given to each categoryC is overall condition grade fuzzy set

Risk AssessmentFuzzy Rules for Deterioration Model:

Deterioration Rate (D’) Condition Grade (C)

Age (A) good adequate fair poor failed

new average fast fast very fast very fast

young average average fast fast very fast

Meddle-aged slow average average fast fast

Old very slow slow slow average fast

Very old very slow very slow slow average average

Risk AssessmentTime Based Condition Grade Evaluation Using Markov Transition Model:

10000

1000

0100

0010

0001

),...,(),...,(5,45,4

4,34,3

3,23,2

2,12,1

115151

tt

tt

tt

tt

Ct

Ct

Ct

Ct

DD

DD

DD

DD

Risk AssessmentFuzzy Inference System:

InferenceFuzzification Defuzzification

Knowledge

Base

Expert Knowledge Field Data

Sub

ject

ive

Obj

ect

ive

Inputs Output

• Degree of feeder overload Degree of feeder overvoltage Degree of exposure to

mechanical harmfulness Asset condition

Failure likelihood

Risk AssessmentStage Wise Fuzzy Reasoning Process:

RB1:Load currentAmbient temp.Ventilation

Thermal violation degree

RB2:Lght. exposureLght protectn.Pollution

Voltage violation degree

RB3:TreeAccidentAnimal

Mecha. contact degree

RB4:ThermalVoltageMechanical

Stressor degree

RB5:StressorCondition grd.

Failure possibility

Risk AssessmentFuzzy inference rules to deduce feeder failure possibility:

Feeder failure possibility

Stressor degreevery low low Medium High very high

Condition grade

good very low Low Medium High very highadequate very low Low Medium high very high

fair very low Low Medium high very highpoor very low Low Medium high very highfailed very high very high very high very high very high

Cost EvaluationSectoral Customer Damage Cost (Sectoral IER)

0

100

200

300

400

500

600

700

800

900

0 2 4 6 8 10

Interruption duration (hours)

Dam

age

cost

(Bah

t) Residential

Small general service

Medium general service

Large general service

Specific business

Government

Cost EvaluationAverage and Composite Damage Cost (IER)

Duration 2 s 1 m 30 m 1 hr. 2 hr. 4 hr. 8 hr.

MEA 3.033 1.944 19.020 65.996 136.717 245.184 458.956

PEA 8.533 13.131 37.661 62.794 105.610 208.010 374.720

All customers 6.452 8.905 30.587 63.881 117.097 221.618 405.735

IER (Bath/kWh)MEA 53.799PEA 60.165

60.348

Cost EvaluationPrice Cap

CustomerType

Size(kW)

Rate Price Cap

On peak Off peak On peak Off peak

Residential 3.6246 1.1914 1.5289 0.1011Small business < 30 3.6246 1.1914 1.5289 0.1011Medium business 30 – 99 2.6950 1.1914 0.5993 0.1011Large business > 999 2.6950 1.1914 0.5993 0.1011

Cost EvaluationWork Breakdown Structure (WBS)

WBSTask name: Pole installationScope: installing 12 m concrete pole on ordinary groundMaterial:

Code Description Quantity5625-668-12100 Concrete pole 12m 1

5620-643-00100 Cement 105610-641-00100 Rough sand 0.5Manpower:

Position Number

Worker 2

Technician 1

Crane Operator 1

Machine:

Machine & Tool Number

Mobile crane 1

Duration: 2 hrs.

Responsible person: Somsak

Cost EvaluationTypical Cost Figure for 1 Circuit-km UG Feeder:

Components Qty Unit Cost

Duct 1000 m 1,500,000.00

Manhole 4 set 200,000.00

Cable support 4 set 54,644.80

Underground cable 3,000 m 4,026,750.00

Splice 9 set 45,602.64

Terminator 3 set 30,588.00

Total cost 6,457,585.44

Cost EvaluationConcept of Loss of Fixed Asset by Prevention

Replacement

Analytical Hierarchy Process (AHP)Hierarchical Structure Decision Model:

Goal

Criterion1 Criterion2 Criterion3

Subcriterion11

Alternative1

Alternative2

Alternative3

Alternative4

Subcriterion12

Alternative1

Alternative2

Alternative3

Alternative4

Alternative1

Alternative2

Alternative3

Alternative4

Alternative1

Alternative2

Alternative3

Alternative4

Analytical Hierarchy Process (AHP)Numerical Rating and Verbal Preference:Numerical

ScaleVerbal Importance Explanation

1 Equal importance Two activities contribute equally to the object

3 Moderate importance Slightly favors one over another

5 Essential or strong importance

Strongly favors one over another

7 Demonstrated importance

Dominance of the demonstrated in practice

9 Extreme importance Evidence favoring one over another of highest possible order of affirmation

2,4,6,8 Intermediate values When compromise is needed

Analytical Hierarchy Process (AHP)Comparison Matrix:

Criteria Alternative 1 Alternative 2 Alternative 3 ….. Alternative n

Alternative 1 1 a12 a13 a1n

Alternative 2 a21 1 a23 … a2n

Alternative 3 a31 a31 1 … a3n

….. … … … 1 …

Alternative n an1 an2 an3 … 1

i, j = 1,…., naij = 1,….,9 aji = 1/ aij

Analytical Hierarchy Process (AHP)Consistency Check:

1. Determine the principal Eigen value: lmax 2. Compute the consistency index (CI)

3. Compute the consistency ration (CR)

1max

n

nCI

RI

CICR

SimulationResults Analysis and Discussion: Data modeling Data availability and sufficiency Accuracy:

Inclusion of impacted factors Expert knowledge

Applicability

Results Analysis and Discussion: Failure rate of assessed feeder estimated from DSS of 1.5 times/year

lower than actual events of 7. Result obtained looks alright when compared to other feeders operating in

neighboring area. Difference possibly due to:

Different deterioration behavior of components Some components may deteriorate faster than 2d0 under certain stressor Fuzzification and fuzzy rules design, workmanship, switching, overheat/overvoltage effect or particular

features inherent to assessed feeder. Undergrounding system cannot compete with overhead counterpart if

only financial aspects are considered. Cost figured already provided for each option.



Results Analysis and Discussion: Aesthetic and world heritage site harmony are prime

important for decision making. Information on feeder configuration and design are

offered by asset model. Cost figured already provided for each option. If there exist more criteria/requirements to examine,

they can be added into the decision hierarchy without any difficulty

Documents

Novel Decision Support System for Underground Power Network Asset Management Asawin Rajakrom CAMT, CMU August 29, 2009