1 In this annex we review the load forecasts produced by the Thai Load
Forecasting Subcommittee (TLFS). The objective is to ascertain whether the forecasts are a sound basis on which to base investment plans.
2 In the annex we:
3
(a) describe the process and methodology used. We give a more detailed description of the methodology in Attachment 1;
(b) review the accuracy of previous TLFS forecasts;
(c) review the GDP forecasts used, which are the key driver of the local forecasts;
(d) summarise the latest load forecasts. The forecasts are reproduced in detail in Attachment 2;
(e) compare recent electricity demand against latest forecasts; and
(f) summarise our key conclusions.
We also present a summary of trends in demand in Attachment 3.
Forecasting process
4 The TLFS assumes overall responsibility for load forecasting in Thailand.
The subcommittee includes representatives from NEPO, EGAT, the PEA and MEA.
MEA and PEA estimate demand from their respective customers, and EGAT estimate demand for their direct customers. These forecasts are then subject to review by the
TLFS.
5 Load forecasts are made annually by the TLFS every September. A halfyearly review is conducted so that the annual forecast can be amended if necessary.
The most recent version of the TLFS load forecast was issued in September 1998.
Forecasting methodology
6 The current forecasting methodology is based upon the recommendations of a
Canadian International Development Agency funded study. We discuss the approach briefly here and set out the approach in more detail in Attachment 1 to this Annex.
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7 MEA and PEA forecast energy take for each of their seven customer classes.
Typical load profiles for each customer class are applied to energy take forecasts to calculate peak demand. PEA forecast energy take and demand separately in each of their regions. EGAT then forecast their generation requirement.
8 MEA and PEA use a mixture of econometric equations and energy intensity ratios to forecast energy take. The key driver is Gross Domestic Product (GDP), which determines household income and industrial output and hence electricity demand.
9 The GDP forecasts used are long term forecasts prepared by the Thailand
Development Research Institute (TDRI) specially for load forecasting purposes. The aggregate GDP forecasts are disaggregated by region into Gross Regional Product
(GRP) and by industrial sector, in order to calculate energy take by customer class and by region. There are no comparable forecasts by alternative organisations.
10 Because the outlook for the Thai economy is currently uncertain, the
September 1998 load forecasts are based upon three different predictions for load growth, with different projected rates of economic recovery: the Rapid Economic
Recovery case (RER); the Moderate Economic Recovery case (MER); and the Low
Economic Recovery case (LER).
11 Generally we think that the methodology is sound, but we note that:
(a) the EGAT forecasts of the generation requirement, upon which generation investment plans are based, incorporate EGAT’s own losses /internal consumption, which depends upon the future plant portfolio.
It would be more accurate for planning purposes to prepare the load forecast on a net ‘sent out’ basis and not gross generated values;
(b) the load profiles used are from a 1996 study, but we understand that new research is being undertaken to update this data;
1
(c) the survey data on ownership of household appliances by household income group dates from the early 1990s.
We understand that action is being taken to update it.
1 Using methodology from a recent World Bank funded consultant’s report, MEA will install electronic metering equipment at a sample 1 200 customers (comprising all customer types) to undertake a new
‘end use’ survey of electricity consumption. These meters will be installed by September 1999 and data logging will commence thereafter. We have been told by the TLFS that PEA will carry out a similar ‘end use’ survey in the near future; this survey, however, will be on a very much smaller scale than that of MEA due to limited resources.
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2

12 We understand that load forecasts made before 1995 consistently underestimated actual demand and energy consumption and, as a result, too little new capacity was planned for the system. Since 1995, however, as illustrated in Figure
A.1, ‘Base Case’ forecasts have been higher than actual demand.
In 1996, before the economic downturn, actual demand was consistent with the ‘Low Case’ forecast.
In 1997, the actual demand was consistent with the ‘Very Low Case’ forecast.
Figure A.1 - Comparison of previous load forecasts with actual demand growth
17 000
16 000
15 000
14 000
13 000
12 000
11 000
Actual system maximum demand
1994 'Base case' forecast
1995 'Base case' forecast
1996 'Low case' forecast
1997 'Very low case' forecast
10 000
1994 1995 1996
Year
1997 1998
13 Figure A.2 illustrates the TDRI’s current GDP forecasts, on which the
September 1998 load forecasts are based. Growth is positive in 1999 in all but the
LER, and exceeds 2.0% in 2000 in all scenarios.
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Figure A.2 - GDP forecast prepared by TDRI for different rates of economic recovery
8.00%
6.00%
4.00%
2.00%
0.00%
-2.00%
-4.00%
Rapid Economic Recovery
Moderate Economic Recovery
Low Economic Recovery
-6.00%
Year
14 In Table A.1, we have compared the TDRI forecasts with other available forecasts, which are all short term.
Table A.1 - Comparison of GDP forecasts
Source of GDP forecast
TDRI (RER)
TDRI (Medium Economic Recovery)
TDRI (LER)
Bank of Thailand (prepared by Economics Research Department)
National Economic and Social Development Board (NESDB)
Bangkok Bank plc
Asian Development Bank
Goldman Sachs
ABN-AMRO
Merrill Lynch Phartra
Thai Farmer Bank plc
15 We note that:
Annual GDP growth (%)
1998 1999 2000
-5.0%
-5.0%
2.4%
0.6%
5.4%
3.7%
-5.0%
-8.0%
-7.8%
-0.5%
1.0%
0.9%
2.7%
2.5%
2.5%
-7.8%
0.5%
-1.0%
-2.0%
-2.4%
0.5%
(a) the TDRI forecast of GDP growth of –5% for 1998 is significantly more optimistic than that predicted by the Bank of Thailand and
NESDB, which predict growth of about -8%;
(b) for 1999, the MER GDP assumption is consistent with the forecasts by the public agencies, but significantly higher than forecasts by the private sector international banks.
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16 The following tables, Tables A.2, A.3 and A.4, summarise the result of the
September 1998 forecasts.
Table A.2 - Summary of TLFS forecast for EGAT generation
Period
1997-2001
2002-2006
2007-2011
Average energy growth rate
(% per annum)
RER
5.34
7.68
7.16
MER
3.83
6.39
6.65
LER
2.69
4.58
6.01
Period
1997-2001
2002-2006
2007-2011
Average peak demand growth rate
(% per annum)
RER
5.37
7.62
7.13
MER
4.02
6.46
6.65
LER
2.96
4.80
5.92
Table A.3 - Summary of TLFS load forecast for MEA
Period
1997-2001
2002-2006
2007-2011
Average energy growth rate
(% per annum)
RER MER LER
3.59
6.12
5.30
2.18
4.68
4.36
1.35
3.47
3.49
Period
1997-2001
2002-2006
2007-2011
Average peak demand growth rate
(% per annum)
RER MER LER
3.46
6.07
5.31
2.01
4.58
4.34
1.17
3.37
3.48
Table A.4 - Summary of TLFS load forecast for PEA
Period
1997-2001
2002-2006
2007-2011
Average energy growth rate
(% per annum)
RER
7.11
8.82
8.50
MER
5.49
7.57
8.20
LER
4.18
5.37
7.76
Period
1997-2001
2002-2006
2007-2011
Average peak demand growth rate
(% per annum)
RER
6.45
8.73
8.24
MER
5.20
7.74
7.99
LER
4.00
5.80
7.38
17 The MER load forecast (on which all investment plans are based) for total
EGAT generation is illustrated in Figure A.3.
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Figure A.3 - Forecast of EGAT generation
35 000
30 000
25 000
20 000
15 000
10 000
5 000
Maximum demand (MW)
Energy (GWh)
350 000
300 000
250 000
200 000
150 000
100 000
50 000
0
1985 1990 1995 2000
Year
2005 2010 2015
0
18
The TLFS forecasts that PEA’s generation requirement will continue to grow at a faster rate than that of MEA due to decentralisation of industry away from
Bangkok. This is clearly illustrated in Figure A.4, which shows a predicted
7% increase in PEA’s share of total EGAT generation between the years 2001 and
2011.
Figure A.4 -Breakdown of forecast for EGAT generation
2001 2011
MEA
35%
Direct sales
2%
MEA
29%
Direct sales
1%
Ow n use
/Lossses
6%
Ow n use
/Lossses
6%
PEA
57%
PEA
64%
19 A summary of the annual MER load forecast for EGAT, MEA and PEA for
1999-2011 is given in Attachment 2.
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20 We have been told by MEA and the TLFS that demand for the first three months of this fiscal year was lower than had originally been forecast. This may have been due, in part, to the unusually cool weather experienced during this time but MEA told us that they were seeing patterns of demand more similar to the LER forecast than to the MER forecast. However, insufficient data is yet available to make a reasonable comparison.
21 The key conclusions from our review of the September 1998 load forecast are that:
(a) the forecasting methodology is generally sound; and
(b) the Medium Economic Recovery forecast which underlies the present investment plans provides:
(i) a sensible basis for long term planning, in the absence of evidence to the contrary; but
(ii)
– may constitute an optimistic view of short term demand since outturn demands for the first six months of FY1999 are lower than forecast, although this may be explained, at least in part, by unusually cool weather;
– TDRI GDP forecasts for 1998 were more optimistic than those produced by the Bank of Thailand and
NESDB; and
–
TDRI GDP forecasts for 1999 exceed those of the private sector international banks.
22 However, we believe the current demand forecast represents a reasonable basis on which to undertake the current tariff review.
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23 The methodologies employed by MEA and PEA to forecast load are largely based upon the results of a Canadian International Development Agency funded consortium. The methodology recommended by that study is published in a volume entitled “Load Forecast Methodology, Basic Data, and Load Forecast Results by sector by Utility”, printed in 1993. The methodologies used are described below.
Residential
24
MEA adopt an ‘end use’ model to forecast residential loads. This model considers the level of market saturation and diversity of use for eight different household appliances (accounting for about 85 % of all domestic electricity consumption) in certain stocks of dwelling by income and by dwelling type. We were told by the TLFS that PEA has, from 1998, adopted a similar approach to forecasting residential loads. The structure of the ‘Residential End Use Model’ is illustrated in
Figure A.5.
Figure A.5 - Residential End Use Model
Model Structure
Number of
Dwellings
Source of Data
Household Registration,
Population, Population per
Household
Dwelling by
Income
Surveys,
GRP
Appliance, Saturation
Dwelling by
Types
Social Economic
Survey
Appliance Stock by Dwelling by Income by Dwelling Types
Capacity, Hours of Use
Efficiency Factors
Survey
DSM
Energy
MEA, PEA
Residential Rate Class
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Commercial
25 MEA and PEA adopt different methodologies for short term and long term forecasting of commercial loads:

For short term load forecasting, MEA use a regression model based on the stock of commercial floor space by type of building and energy-use per floor area to derive a forecast of total energy consumption.

Both MEA and PEA disaggregate total commercial load by business type, and use econometric equations, or energy intensity ratios, to develop medium to long term forecasts. The MEA and PEA both estimate load disaggregated by business type with different specifications of the equations for different types of business. MEA have a greater tendency to use economic equations.

The TDRI is commissioned to prepare GDP forecasts by region and business type which are used in conjunction with the aforementioned energy intensity elasticities to estimate total energy consumption.
26 The structure of the ‘Commercial Model’ is illustrated in Figure A.6.
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Figure A.6 - Commercial Model
Model Structure
Stock of
Floorspace by
Type of Building
Floorspace by
Type of Building
New Construction by Type Building
Demolition
/Deferral
Take-Up Rate
Energy Use per
Floor Area
Efficiency
Factor
Short Run
Energy Use
(MEA) Energy Intensity
Source of Data
Consultant Studies,
Surveys
BMA and MEA
Applications
MEA and Consultant
Estimate
Consultant Studies
Consultant Studies and Survey
DSM
GRP Estimate
Long Run
Energy Use
(MEA /PEA)
TOTAL
FORECAST
Short Run
Energy Use
(PEA)
Industrial
27 EGAT, MEA and PEA all use the above energy intensity methodology for long term forecasting of industrial loads. However, for short term forecasts both
MEA and PEA survey their major customers directly to establish the extent to which their future electrical loads might change. The structure of the ‘Industrial Model’ is illustrated in Figure A.7
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Figure A.7 - Industrial Model
Model Structure
Short Run
Sources of Data
BOI
Expected Future
Energy Consumption by Type of Industry
MEA /PEA
Survey
MEA, PEA
Applications
Others
Long Run
Energy Intensity
Ratio
Efficiency Factor
Long Run Energy
Consumption by Sector
GRP and
MEA/PEA
Estimate
DSM ?
FP3AnnexA.doc
11

28 In the 1998 financial year (FY1998), EGAT generated 92 134 GWh, which was 0.64% less than the previous year. This reduction contrasts with past growth and can be attributed to the downturn in the Thai economy which started in July 1997. In the period FY1988 to FY1997, EGAT’s energy generation increased from
31 997 GWh to 92 725 GWh, an average annual growth rate of 12.5%.
29
EGAT’s peak generation in FY1998, 14 180 MW, was 2.25 % lower than in the previous year. This reduction can again be attributed to the downturn in the Thai economy, but is proportionately greater than the reduction in energy generation.
Consequently, the overall system load factor increased from 72.97 % in 1997 to
74.17 % in FY1998. Figure A.8 illustrates EGAT’s annual energy and peak power generation over the period 1961 to 1998.
Figure A.8 - EGAT’s annual energy and peak power generation (1961-1998)
16 000
14 000
12 000
10 000
Peak pow er generated (MW)
Energy generated (GWh)
160 000
140 000
120 000
100 000
8 000
6 000
4 000
80 000
60 000
40 000
2 000 20 000
0
1960 1965 1970 1975 1980
Year
1985 1990 1995
0
2000
30 In the past 10 years EGAT’s sales to PEA have grown faster than sales to
MEA. In FY1988, sales to PEA accounted for 43 % of all EGAT’s generation, in
FY1998 this value rose to 56 %, as illustrated in Figure A.9.
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Figure A.9 - Breakdown of EGAT’s total generation for FY1988 and FY1998
1988 1998
MEA
45%
Direct sales
4%
MEA
35%
Direct sales
2%
8 000
6 000
4 000
2 000
0
16 000
14 000
12 000
10 000
Ow n use
/Lossses
8%
PEA
43%
Ow n use
/Lossses
7%
PEA
56%
31 In FY1998, MEA, PEA and direct customers accounted for 41%, 56% and 2% of EGAT peak generation respectively. A further 4% was consumed within EGATs power plants. Data for prior years is not available.
32 Figure A.10 illustrates the load profiles for MEA, PEA and direct customers, and EGATs generation requirement for the peak day in FY1998.
Figure A.10 - Load profile for day of system maximum demand in FY1998
(28/04/98)
EGAT generation requirement
EGAT total sales
PEA
MEA
Direct customers
Tim e of day
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13

33
For the period FY1988 to FY1997, MEA’s energy purchases from EGAT increased from 14 564 GWh to 33 708 GWh showing an average growth rate of 9.8 % per annum. In FY1998, however, MEA purchased only 32 341 GWh, a reduction of
4.05 % over the previous year. This reduction was significantly greater than the national average decrease of 0.64 % and illustrates the fact, that from a national point of view, energy consumption in the metropolitan area has been most affected by the downturn in the Thai economy. Figure A.11 illustrates MEA’s power and energy purchases from EGAT for the period FY1988-FY1998.
Figure A.11 - MEA’s energy and power purchases from EGAT
7 000
6 000
5 000
4 000
3 000
2 000
1 000
Peak pow er
Energy purchases
0
1988 1989 1990 1991 1992 1993
Year
1994 1995 1996 1997
0
1998
34 Pie charts showing the distribution of sales to each tariff category are shown in
Figure A.12. The categories are residential, small general service, medium general service, large general service, specific business, government and non-profit organisations (NPOs) and street lighting. The pie charts also show that MEA’s own use/losses account for about 3.8 % of total purchases from EGAT.
70 000
60 000
50 000
40 000
30 000
20 000
10 000
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Figure A.12 Comparison of MEA sales by customer type for FY1996 and
FY1998
Government
& NPO
4.1%
Small general service
13.5%
1996
Specif ic business
4.0%
Government
& NPO
4.3%
1998
Small general service
13.9%
Specif ic business
4.3%
M edium general service
27.6%
M edium general service
22.8%
Resident ial
18.4%
Resident ial
21.6%
Own Use
/ Losses
3.8%
* Ot her
0.4%
Own Use
/ Losses
3.8%
* Ot her
0.4%
Large general service
28.1%
Large general service
29.0%
35 Whilst the overall level of sales in 1996 and 1998 were similar, there was a rearrangement of sales between customer groups: sales to medium general service’ customers declined by about 9.2 % over this two-year period, whereas sales to most other customer groups experienced modest increases.
PEA
36
For the period FY1988 to FY1997, PEA’s energy purchases from EGAT increased from 13 737 GWh to 50 192 GWh showing an average growth rate of
15.5 % per annum. In FY1998, however, PEA’s purchase increased by only 2.41 % to 51 403 GWh. This decline can be attributed to the downturn in the economy.
Figure A.13 illustrates PEA’s peak power demand and energy purchases from EGAT for the period FY1988-FY1998.
37 Prior to FY1998, PEA did not determine the coincident peak demand for its four regions in total, (i.e., north, north east, central and south), and simply calculated the sum of the separate maximum demands in each region. This fact underlies the significant “reduction” of PEA’s peak power demand in FY1998.
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Figure A.13 - PEA’s energy and power purchase from EGAT
10 000
9 000
8 000
7 000
6 000
5 000
4 000
3 000
2 000
Peak pow er
Energy purchases
100 000
90 000
80 000
70 000
Non-coincident peak before 1998 60 000
50 000
40 000
30 000
20 000
1 000
0
1988 1989 1990 1991 1992 1993
Year
1994 1995 1996 1997
10 000
0
1998
38 Pie charts showing the distribution of PEA’s sales are shown in Figure A.7.
Figure A.14 - Comparison of PEA sales by customer type for FY1996 and
FY1998
1998
Government
& NPO
4.0%
Small general service
8.6%
1996
Specif ic business
2.6%
M edium general service
26.8%
Government
& NPO
3.4%
Small general service
8.1%
Specif ic business
2.5%
M edium general service
17.8%
* Ot her
2.4%
Resident ial
21.3%
Resident ial
23.1%
* Ot her
2.4%
Own Use
/ Losses
5.1%
Large general service
29.2%
Own Use
/ Losses
5.8%
Large general service
36.9%
39 Between 1996 and 1998, PEA’s largest growth in sales was to ‘large general service’ customers, from 13 141 GWh to 18 952 GWh, equivalent to an average increase of 20 % per annum. PEA sales to ‘medium general service’ customers fell by an average of 13 % per annum over the same period from 12 055 GWh to
9 139 GWh. These two customer categories represent the most significant changes to
PEA’s market.
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40 The Moderate Economic Recovery scenario forecasts for EGAT’s Generation requirements, and MEA’s and PEA’s demand and energy take are shown in Tables
A.5, A.6 and A.7 respectively.
Table A.5 - EGAT’s generation requirements forecast, Sept. 1998 - (Moderate
Economic Recovery Case)
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
Fiscal
Year MW
Peak Generation
Increase
MW %
4 734
5 444
6 233
7 094
8 045
8 877
9 730
10 709
12 268
13 311
14 506
14 180
14 499
15 254
16 214
17 308
18 399
19 611
20 818
22 168
23 728
25 450
27 232
28 912
30 587
1 559
1 043
1 195
-
553
710
789
861
951
832
853
979
326
319
755
960
1 094
1 091
1 212
1 207
1 350
1 560
1 722
1 782
1 680
1 675
GWh
Energy Generation
Increase
GWh
Actual
13.23%
15.00%
14.49%
13.81%
13.41%
10.34%
9.61%
10.06%
28 194
31 998
36 458
43 190
49 226
56 007
62 181
69 651
14.56%
8.50%
78 880
85 924
8.98%
-2.25%
92 728
92 134
Forecast
3 414
3 804
4 460
6 732
6 036
6 781
6 173
7 470
9 229
7 044
6 804
- 593
2.25%
5.21%
93 178
97 858
6.29% 103 685
6.75% 110 436
6.30% 117 341
6.59% 124 532
6.15% 132 228
6.48% 141 300
7.04% 151 322
7.26% 162 438
7.00% 173 532
6.17% 184 213
5.79% 194 930
1 044
4 680
5 827
6 751
6 905
7 191
7 696
9 072
10 022
11 116
11 094
10 681
10 717
%
13.78%
13.49%
13.94%
18.46%
13.98%
13.78%
11.02%
12.01%
13.25%
8.93%
7.92%
-0.64%
1.13%
5.02%
5.95%
6.51%
6.25%
6.13%
6.18%
6.86%
7.09%
7.35%
6.83%
6.16%
5.82%
Load
Factor
%
67.99%
67.10%
66.77%
69.50%
69.85%
72.02%
72.95%
74.25%
73.40%
73.69%
72.97%
74.17%
73.36%
73.23%
73.00%
72.84%
72.80%
72.49%
72.51%
72.76%
72.80%
72.86%
72.74%
72.73%
72.75%
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Table A.6 - MEA’s forecast of demand and energy, TLFS Sept. 1998
(Moderate Economic Recovery Case)
Fiscal
Year
Energy demand by consumer category (GWh) Total
Sales
(GWh)
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
5 962
6 494
6 986
4 375
4 645
4 480
7 449
7 872
8 292
8 787
9 280
9 763
10 253
10 767
11 333
11 919
12 531
13 151
13 750
4 474
4 641
4 859
5 119
5 390
5 655
5 924
6 205
6 516
6 837
7 172
7 512
7 860
8 941
8 735
7 376
7 240
7 441
7 727
8 078
8 440
8 799
9 156
9 531
9 929
10 349
10 813
11 273
11 737
Actual
9 099
9 591
9 368
Forecast
9 521
9 848
10 273
10 782
11 299
11 806
12 304
12 858
13 358
13 908
14 484
15 051
15 602
1 290
1 338
1 386
1 337
1 443
1 391
122
127
134
31 126
32 373
31 121
1 431
1 493
1 567
1 626
1 686
1 738
1 788
1 841
1 897
1 965
2 027
2 089
2 164
1 431
1 491
1 562
1 640
1 692
1 765
1 826
1 892
1 968
2 035
2 093
2 151
2 207
137
143
148
153
160
168
175
180
185
189
193
197
200
31 683
32 929
34 428
36 185
37 947
39 694
41 426
43 274
45 186
47 202
49 313
51 424
53 520
Fiscal
Year
1996
1997
1998
Total
Sales
(GWh)
31 126
32 373
31 121
1999
2000
2001
2002
2003
2004
2005
31 683
32 929
34 428
36 185
37 947
39 694
41 426
2006
2007
2008
2009
43 274
45 186
47 202
49 313
2010 51 424
2011 53 520
* Other - street lighting
MW
Peak demand met by EGAT
Increase
5 636
5 938
5 657
5 716
5 935
6 225
6 598
6 892
7 147
7 457
7 788
8 166
8 567
8 872
9 250
9 631
MW
-
195
302
281
59
219
290
373
294
255
310
331
378
401
305
378
381
Energy received from EGAT
Increase
% GWh GWh
Actual
9.86%
5.36%
-4.73%
Forecast
1.04%
3.83%
4.89%
5.99%
4.46%
3.70%
4.34%
4.44%
4.85%
4.91%
3.56%
4.26%
4.12%
32 366
33 708
32 341
1 539
1 342
- 1 367
33 038
34 408
36 050
37 890
39 736
41 564
43 378
45 311
47 343
49 427
51 636
53 847
56 077
697
1 370
1 642
1 840
1 846
1 828
1 814
1 933
2 032
2 084
2 209
2 211
2 230
%
13.51%
4.15%
-4.06%
2.16%
4.15%
4.77%
5.10%
4.87%
4.60%
4.36%
4.46%
4.48%
4.40%
4.47%
4.28%
4.14%
Load
Factor
%
65.56%
64.80%
65.26%
65.98%
66.18%
66.11%
65.56%
65.82%
66.39%
66.41%
66.42%
66.18%
65.86%
66.44%
66.45%
66.47%
FP3AnnexA.doc
18

Table A.7 - PEA’s forecast of demand and energy, TLFS Sept. 1998
(Moderate Economic Recovery Case)
Fiscal
Year
Energy demand by consumer category (GWh) Total
Sales
(GWh)
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
9 569
10 635
11 879
3 853
4 119
4 154
13 245
14 589
15 999
17 444
18 940
20 498
22 124
238 330
25 622
27 511
29 505
31 613
33 844
4 226
4 391
4 621
4 898
5 210
5 562
5 958
6 405
6 872
7 360
7 872
8 410
8 976
12 055
10 208
9 139
8 817
9 164
9 649
10 233
10 891
11 633
12 470
13 415
14 413
15 467
16 583
17 764
19 015
Actual
13 141
17 920
18 952
Forecast
18 234
19 054
20 165
21 477
22 950
24 603
26 458
29 255
32 793
36 986
40 974
44 175
47 132
1 183
1 239
1 278
1 812
2 141
1 769
1 075
1 279
1 253
42 688
47 541
48 424
1 388
1 487
1 595
1 714
1 848
1 987
2 133
2 286
2 446
2 615
2 793
2 981
3 180
1 778
1 823
1 887
1 973
2 083
2 217
2 373
2 557
2 751
2 959
3 179
3 415
3 666
1 381
1 487
1 600
1 728
1 877
2 029
2 184
2 347
2 517
2 694
2 882
3 079
3 291
49 069
51 995
55 516
59 467
63 799
68 529
73 700
294 595
87 414
95 592
103 788
111 437
119 104
Fiscal
Year
Total
Sales
Peak demand met by EGAT
Increase
Energy received from EGAT
(GWh) MW MW % GWh
Actual
1996
1997
1998
42 688
47 541
48 424
44 981
50 192
51 403 7 736 n/a n/a
Forecast
1999
2000
2001
2002
2003
2004
2005
49 069
51 995
55 516
59 467
63 799
68 529
73 700
8 010
8 560
9 188
9 878
10 627
11 433
12 305
274
550
628
690
749
806
872
3.54%
6.87%
7.34%
7.51%
7.58%
7.58%
7.63%
51 975
55 064
58 762
62 921
67 493
72 481
77 940
2006
2007
2008
2009
294 595
87 414
95 592
103 788
13 339
14 500
15 782
17 081
1 034
1 161
1 282
1 299
8.40%
8.70%
84 648
92 305
8.84% 100 838
8.23% 109 406
2010 111 437 18 326 1 245 7.29% 117 443
2011 119 104 19 591 1 265 6.90% 125 514
* Other - agricultural pumping, temporary, free of charge
GWh
4 818
5 211
1 211
Increase
572
3 089
3 698
4 159
4 572
4 988
5 459
6 708
7 657
8 533
8 568
8 037
8 071
%
12.00%
11.58%
2.41%
1.11%
5.94%
6.72%
7.08%
7.27%
7.39%
7.53%
8.61%
9.05%
9.24%
8.50%
7.35%
6.87%
Load
Factor
%
75.85%
74.07%
73.43%
73.01%
72.71%
72.50%
72.37%
72.31%
72.44%
72.67%
72.94%
73.12%
73.16%
73.14%
FP3AnnexA.doc
19