1M.Sc. Jukka Lassila FI Session 5 – Block 2
Barcelona 12-15 May 2003LAPPEENRANTAUNIVERSITY OF TECHNOLOGY
DATA ENVELOPMENT ANALYSIS IN THE BENCHMARKING OF ELECTRICITY
DISTRIBUTION COMPANIES
M.Sc. Jukka Lassila
M.Sc. Satu Viljainen
M.Sc. Samuli Honkapuro
Prof. Jarmo Partanen
2M.Sc. Jukka Lassila FI Session 5 – Block 2
Barcelona 12-15 May 2003LAPPEENRANTAUNIVERSITY OF TECHNOLOGY
Overview
Overview
Introduction
Evaluation of the present DEA-model
Developments of the present DEA-model
Interruption costs
Conclusions
3M.Sc. Jukka Lassila FI Session 5 – Block 2
Barcelona 12-15 May 2003LAPPEENRANTAUNIVERSITY OF TECHNOLOGY
0
10 000
20 000
30 000
40 000
50 000
Dis tribut ion companies (total num ber is 94)
Ne
twork
le
ng
th [
km
]
Finland – Electricity distribution companies
• The number of electricity distribution companies: ~ 100• Average length of the network: 3 700 km (123…49 000 km)
• Average number of customers: 31 000 (766…314 000)
• 3 years experience of efficiency benchmarking (1999, 2000, 2001)
4M.Sc. Jukka Lassila FI Session 5 – Block 2
Barcelona 12-15 May 2003LAPPEENRANTAUNIVERSITY OF TECHNOLOGY
The factors of the efficiency benchmarking by DEA-model
EFFICIENCYSCORE (0…1)
Operational costs
Power quality
(interruption time) Distributed
energy
Number of customers
Length of the network
5M.Sc. Jukka Lassila FI Session 5 – Block 2
Barcelona 12-15 May 2003LAPPEENRANTAUNIVERSITY OF TECHNOLOGY
The efficiency scores of the Finnish distribution companies
0,00
0,20
0,40
0,60
0,80
1,00
1,20
Distribution companies (total number is 94)
Eff
icie
ncy
scor
e
The average is 0.830
6M.Sc. Jukka Lassila FI Session 5 – Block 2
Barcelona 12-15 May 2003LAPPEENRANTAUNIVERSITY OF TECHNOLOGY
The effects of the efficiency benchmarking (1/2)
1) Directing effects companies tend to pay attention to factors that are used in the DEA-model
2) Efficiency score affect directly to the reasonable return on capital
7M.Sc. Jukka Lassila FI Session 5 – Block 2
Barcelona 12-15 May 2003LAPPEENRANTAUNIVERSITY OF TECHNOLOGY
The effects of the efficiency benchmarking (2/2)
Example:
Operational costs of a company are 200 M€/a.
A) Efficiency score is 1.0
Impact on allowed return = (1.0 - 0.9) * 200 M€ = 20 M€/a
B) Efficiency score is 0.72
Impact on allowed return = (0.72 - 0.9) * 200 M€ = -36 M€/a
8M.Sc. Jukka Lassila FI Session 5 – Block 2
Barcelona 12-15 May 2003LAPPEENRANTAUNIVERSITY OF TECHNOLOGY
Problems of efficiency benchmarking with DEA-model
• The directing effects of benchmarking are not equal for all the companies- There are large numbers of companies for which the
efficiency scores do not depend on power quality
- Power quality affects the efficiency scores randomly
• The changes in the directing effects differ from one year to another
• The present efficiency benchmarking method has to be developed
9M.Sc. Jukka Lassila FI Session 5 – Block 2
Barcelona 12-15 May 2003LAPPEENRANTAUNIVERSITY OF TECHNOLOGY
Problems of efficiency benchmarking with DEA-model
0
10
20
30
40
50
60
Operationalcosts
Power quality * Distributedenergy
Network length Customers
Dis
trib
utio
n c
om
pa
nie
s0
100
200
300
400
500
600
Pri
ce o
f ou
tage
[€/
cust
omer
,h]
Price of outage [€/customer,h]
The number of companies that have insignificant factors in the DEA-model
10M.Sc. Jukka Lassila FI Session 5 – Block 2
Barcelona 12-15 May 2003LAPPEENRANTAUNIVERSITY OF TECHNOLOGY
Developing the DEA-model (1/2)
costs lOperationa
c timeonInterruptiCustomersNetworkEnergy hMax
1
23210
v
vuuu
costs) onInterrupticosts lOperationa(
cCustomersNetworkEnergy hMax
1
3210
v
uuu
11M.Sc. Jukka Lassila FI Session 5 – Block 2
Barcelona 12-15 May 2003LAPPEENRANTAUNIVERSITY OF TECHNOLOGY
Developing the DEA-model (2/2)
• Principle changes in the model- power quality can be measured as a interruption costs
- power quality is not a separate factor in the model
- interruption costs are added to operational costs
Power quality becomes meaningful and almost equally important factor for each company
12M.Sc. Jukka Lassila FI Session 5 – Block 2
Barcelona 12-15 May 2003LAPPEENRANTAUNIVERSITY OF TECHNOLOGY
Number of companies having insignificant factors in efficiency benchmarking
0
10
20
30
40
50
60
Operational costs Power quality * Distributed energy Network length Customers
Dis
trib
utio
n c
ompa
nies
Present DEA-modelDeveloped DEA-model
13M.Sc. Jukka Lassila FI Session 5 – Block 2
Barcelona 12-15 May 2003LAPPEENRANTAUNIVERSITY OF TECHNOLOGY
Price of outages in developed DEA-model
0
2
4
6
8
10
12
14
Distribution companies (total number is 94)
Price o
f outa
ge [
€/c
usto
mer,
h]
• For most companies price of outages is between 4…6 €/customer,h
• Corresponding prices of outages in the present DEA-model are 0…500 €/customer,h
14M.Sc. Jukka Lassila FI Session 5 – Block 2
Barcelona 12-15 May 2003LAPPEENRANTAUNIVERSITY OF TECHNOLOGY
Conclusions
• The directing effects of benchmarking have to be predictable and equal for each company
• This presentation introduced a solution to a problem concerning equality - basic idea was change the way in which power quality is handled in the DEA-model
• Future research activities include improving the predictability and taking investment into account in the efficiency benchmarking
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