UM ESTUDO COMPARATIVO ENTRE USINAS TERMEL

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FEDERAL UNIVERSITY OF PERNAMBUCO UFPE
COMPANHIA HIDRO ELÉTRICA DO SÃO FRANCISCO CHESF
A COMPARATIVE STUDY OF THE EFFICIENCY OF THE
BRAZILIAN HYDROELECTRIC POWER PLANTS USING DATA
ENVELOPMENT ANALYSIS DEA
PRESENTER MSc. EDUARDO ARRUDA CÂMARA Co-author
Prof. Dr. Francisco de Sousa Ramos
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Electricity Installed Capacity, in Megawatts
  Country Total
1 United States 964,754
2 China 517,550
3 Japan 251,318
4 Russia 218,370
5 India 143,773
6 Canada 122,661
7 Germany 120,833
8 France 112,022
9 Brazil 93,158
10 United Kingdom 78,706
Source Energy Information Administration. International Energy Annual 2006. Table Posted December 8, 2008. Source Energy Information Administration. International Energy Annual 2006. Table Posted December 8, 2008. Source Energy Information Administration. International Energy Annual 2006. Table Posted December 8, 2008.

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Hydroelectric Installed Capacity, in Megawatts
  Country Total
1 China 117,388
2 United States 77,821
3 Canada 71,801
4 Brazil 70,858
5 Russia 45,835
6 India 32,326
7 Norway 26,410
8 Japan 22,133
9 France 20,806
10 Sweden 16,302
Source Energy Information Administration. International Energy Annual 2006. Source Energy Information Administration. International Energy Annual 2006. Source Energy Information Administration. International Energy Annual 2006.
Table Posted December 8, 2008. Next Update August 2009 Table Posted December 8, 2008. Next Update August 2009 Table Posted December 8, 2008. Next Update August 2009
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USAs Electricity Installed Capacity by Type,
January 1, 2006 (Megawatts)
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Brazils Electricity Installed Capacity by Type,
January 1, 2006 (Megawatts)
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Comparative of the Distribution of Electricity
Installed Capacity by Type
Country Thermal Hydroelectric Nuclear Others Total
United States (MW) 761,603 77,821 100,334 24,996 964,754
Distribution () 78.94 8.07 10.40 2.59 100.00
Brazil (MW) 14,205 70,858 2,007 6,088 93,158
Distribution () 15.25 76.06 2.15 6.54 100.00
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GENERAL OBJECT

• This study will identify and compare the
  efficiency of 87 Brazilian hydroelectric
  generating plants with installed capacity above
  50 MW, based on the inputs and output used as
  variables of the analysis.

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METHODOLOGY

• For the data analysis, the DEA methodology was
  used, under the input orientation, in the
  traditional models that allow constant returns of
  scale (CRS), also known as CCR model, and
  variable returns of scale (VRS) or BCC model.

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DATA ENTRY

• ? Sample
• Due to the availability of data, related to the
  variables used in the study, 87 Brazilian
  hydroelectric generating units, from 29 different
  companies were chosen for analysis.

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DATA ENTRY
? Output and Inputs

• In the selection of variables were used and
  combined three criteria the availability of
  data the research of related literature and the
  professional opinion of relevant individuals,
  concerned with the issue that the research is
  proposed.

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STUDIES ON EFFICIENCY IN POWER GENERATION
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STUDIES ON EFFICIENCY IN POWER GENERATION
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DATA ENTRY
? Output and Inputs

• Output
• Generated Energy in medium MW .
• Inputs
• Installed Power in MW
• Height of falls in meters
• Age of the Generation Plant in months and
• Assured Energy in medium MW.

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OBSERVED RESULTS
The indices of efficiency of the 87 HPPs in
question were obtained using the EMS program,
version 1.3.0, Scheel (2000), which employs the
DEA methodology and its traditional DEA-CCR and
DEA-BCC models.
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OBSERVED RESULTS
Number of efficient HPPs with 5 variables
selected (1 OUTPUT e 4 INPUTS) in both
models DEA-CCR 8 efficient HPPs
(100) DEA-BCC 27 efficient HPPs (100). From
the results obtained it is possible to observe
that all 8 HPPs considered efficient by the
DEA-CCR model were also efficient in the DEA-BCC
model.
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OBSERVED RESULTS
The Top 5 Efficient HPPs and the Number of Times
they were Considered as Benchmark
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OBSERVED RESULTS
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OBSERVED RESULTS
Histogram of the Distribution of Indices of
Efficiency (DEA-CCR e DEA-BCC)
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OBSERVED RESULTS
Statistical Summary of Indices of Efficiency in
the DEA-CCR and DEA-BCC Models
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OBSERVED RESULTS
Indices of Efficiency Analysis by the Time of
Operation of the HPP
Arithmetic average between the efficiency
averages from the models by category.
- Recent HPPs ? 81.30
- Intermediary HPPs ? 84
- Old HPPs ? 75.44
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OBSERVED RESULTS
Indices of Efficiency for Installed Power
Analysis
- Small HPPs ? 77.46 - Medium HPPs ? 74.71
Arithmetic average between the efficiency
averages from the models by category.
- Large HPPs ? 87.76
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OBSERVED RESULTS
Indices of Efficiency Analysis by the Height of
Falls of the HPP
- Low HF HPPs ? 83.01
Arithmetic average between the efficiency
averages from the models by category.
- Medium HF HPPs ? 74.38 - High HF HPPs ? 80.80
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OBSERVED RESULTS
Indices of Efficiency Analysis by the HPP Owner
Company
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Indices of Efficiency Analysis by the
Geographical Location of the HPP
OBSERVED RESULTS
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OBSERVED RESULTS
(Indices of Efficiency by the Geographical Region)
84
71
82
80
88
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CONCLUSION
- The DEA-CCR model, which admits constant
returns of scale, is more restrictive in the
efficiency of the units than the DEA-BCC
model - The efficient units in the DEA-CCR
model will also be efficient in the DEA-BCC
model - The efficiency indices obtained for
the units in the DEA-CCR model will always be
equal to or lower than the indices for the
DEA-BCC model.
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CONCLUSION
- This study suffers a great influence of the 87
HPPs included in the sample, of the variables
used as inputs and output and of the scope period
covered. - And yet, as a suggestion to carry out
further work would be to measure the efficiency
of national HPPs that were privatized, showing
the situation of them before and after
privatization.
e-mail ecamara_at_chesf.gov.br Phone
55-81-3229.3477/9234.9398