Electricity Supply Interruption Costs

Assessment of electricity supply interruption costs

under restricted time and information resources

Peeter Raesaar, Eeli Tiigimägi, Juhan Valtin

Department of Electrical Power Engineering

Tallinn University of Technology


Contents

Introduction

Assessment approach

Customer survey

Analytical methods

Final results

Conclusions


Reliability consideration

An adequate balance between costs and reliability Traditional – establishing reliability standards

n-1 criteria normative level of LOLP or EENS permitted interruption frequency and duration per year,

etc.

Modern - consider the worth of reliability

Economically justified level of reliability

Measure of reliability worth – interruption costs

Objective – assessment of interruption cost characteristics for Estonian power system


revenue from unserved energy

cost of the supply restoration

direct costs indirect costs

- lost of industrial production- spoiled food or raw materials- lost personal leisure time- injury or loss of life, etc.

- crime during a blackout - business relocation, etc.

Utility costs Customer costs

Electricity supply interruption costs

Customer costs >> Utility costs


Interruption cost characteristics

Cost models: CDF, CENS and combined models For implementation - models characteristics are needed

CDF CENS CID

Characteristics assessment methods: customer surveys –

favorable, but most costly and time-taking

indirect analytical evaluations case studies of actual blackouts


Assessment approach

Short time frame - customer survey rather a pilot one

For more reliable results: customer survey + indirect analytical methods Case studies: no major breakdowns for conclusions

Final results: mean values of estimates by different methods

Interruptions cost characteristics: estimated for residential industrial commercial (+ public) agriculture sector

For whole country - weighted averages of sector estimates


Customer survey - questionnaires

Aim: compose CDF for different customer sectors

Design - the direct costing, indirect costing and contingent valuation approaches

Experience of UK, Canada, Denmark, Finland and Island

For residential and agricultural customers: similar, direct and indirect costing methods were used

For industrial and commercial customers: mainly the direct costing approach


The National Grid ordered the real implementation of the survey from a market information company

Residential survey - by CATI (Computer Assisted Telephone Interviewing) method

For other sectors - Internet survey

Responding rate in commercial and residential sector was low (correspondingly 26 and 46 %)

Survey principles were not realized properly

Customer survey


Short time frame and limited financial resources – not sufficiently bulk surveys for reliable results

Considerably simplified questionnaires to be suitable for telephone or Internet survey

Telephone interviewing with request to answer immediately

No special training of questioners - the competent explanations were not available

The answer “I can not say” in lists of possible answers turned very many answers useless (in commercial sector even 60-70 %)

However - substantial experience for more extensive surveys in future

Customer survey - blunders


020406080

100120140160180

0 1 2 3 4 5 6 7 8

Interruption duration, hours

Inte

rru

ptio

n c

ost

, €

/kW

Industrial, ACOC Industrial, EstoniaCommercial, ACOC Commercial, EstoniaAgriculture, ACOC Agriculture, EstoniaResidential, ACOC Residential, Estonia

Peak demand normalized CDF by surveys

Strongly overestimated costs in commercial and agricultural sectors

Realistic and relatively reliable results in industrial sector


Simple analytical macro methods

For industrial, commercial and agricultural sector:

CENS = GNP / A (€/kWh)

A – the annual electricity sales to customers of the sector

For domestic customers

CENS = HI / Ad (€/kWh)

HI – average annual household income

Ad – average annual domestic electricity consumption

Rough customer damage functions were derived


Deriving from values of other countries

Can be treated as a distinctive analytical method

CDF of Canada, UK, Finland, Denmark, Island, Greece, Tai, Nepal and India were analyzed

Easy and direct way - using prevailing exchange rates (ER)

Comparing on base of ER is misleading - ER do not reflect accurately the worth of electrical energy in countries

More meaningful quantitative comparison - use of purchasing power parities (PPP) estimates

Reflect the purchasing power of inhabitants of countries


Commercial sector CDF

0

20

40

60

80

100

120

140

160

180

2 s 1 min 20min

1h 2h 4 h 8 h 24 h

Interruption duration

Inte

rrup

tion

cost

est

imat

es,

€/k

W Canada 1991

IslandFinland

Canada 1987

Average

Denmark

Nepal

Thailand

Greece

UK

Canada 1980

India

Based on exchange rates

0

10

20

30

40

50

60

70

80

90

2 s 1 min 20min

1h 2h 4 h 8 h 24 h


Inte

rrup

tion

cost

est

imat

es,

€/k

W

Nepal

Canada 1991

Canada 1980

Canada 1987

AverageFinlandIsland

Denmark

Greece

India

Thailand

Based on PPP estimates

Curve shapes are similar, placement is not the same Dispersion of PPP estimates - considerably less and the average is

much lower than in the case of ER estimates Similar results for other sectors


Final results

From results obtained by aforesaid methods, estimates of annual peak demand normalized CDF annual energy consumption normalized CDF cost of energy not supplied CENS and cost of interrupted demand CID

were derived Surveys of commercial and agricultural customers were

not taken into account - they practically failed

Results of residential customers survey – overestimated

Nevertheless they were considered, but with lower weight (answers on willingness to pay for avoiding interruptions were taken account of)


Peak demand normalized CDF

Based on customer surveyAverage of other countries based on PPPBased on GNP/ household income Final for sector

0

5

10

15

20

25

30

Inte

rrup

tion

cost

s, €

/kW

Industry Commerce

0

5

10

15

20

25

30

Inte

rrup

tion

cost

s, €

/kW

2 s 1 m 20 m 1 h 2 h 4 h 8 h


Agriculture

2 s 1 m 20 m 1 h 2 h 4 h 8 h


Residential


Final peak demand normalized CDF

0

5

10

15

20

25

30

2 s 1min 20 min 1 h 2 h 4 h 8 h 24 h


Inte

rru

pti

on

co

sts,

€/k

W

Industry Commerce

Residential Agriculture

Whole country


Final estimates of CENS and CID

2,55

3,60

2,37 2,352,77

0,20 0,220,46

0,85

0,23

0

1

2

3

4

5

Industry Commerce Agriculture Residential Wholecountry

CENS, €/kWh CID, €/kW

n

i i

i

rLF

rCDF

nCENS

1

1 )()(0CDFCID

LF – load factor


Conclusions (1)

The evaluation of the worth of electric service reliability is still in its infancy in many countries, including Estonia

Growing recognition of the need to consider the link between the cost of a certain level of reliability and its value to customers

Use of any reliability worth evaluation model needs interruption cost characteristics such as CDF, CENS, CID

The outcome of the study - assessments of these characteristics for Estonian customer sectors

The results - relatively realistic and made available a set of generic data for reliability worth evaluation


Conclusions (2)

Due to a short time frame given for the study

small scale customers survey + indirect analytical methods + analysis of characteristics of other countries

Experience for comprehensive large-scale customer surveys in future

The approach can be recommended for assessment of electricity supply interruption cost characteristics under restricted time, financial and/or information resources


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Electricity Supply Interruption Costs

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