Chapter 6
Forecasting Model for Peak Demand
6.1 Introduction
The models for peak demand will be developed within the same frame work as
the electricity energy demand models. Peak demand will be modeled at the EGAT’s
gross generation level, the MEA purchasing point, and the PEA purchasing point.
The maximum demand model has the same specifications as the electricity
energy demand model. The only difference is the dependent variable where electricity
energy demand variable is replaced by peak power demand variable.
6.2 EGAT’s Peak Demand Model
Peak demand in the model is the coincident peak demand of electrical power
generated by EGAT, power purchased from the independent power producers, and
power from foreign sources in a given month. Monthly data between January 1999
and December 2004 are used to estimate the models.
The following notations are used in EGAT’s peak demand model.
DEGAT
= EGAT’gross peak demand in month t
t
EGAT_D rt = EGAT’gross peak demand in region r in month t
TEMPt = sum of average kingdom daily temperature in month t
TEMPtr = sum of average daily temperature in region r in month t
PRICE t = average electricity prices in month t
Average electricity prices in the EGAT’s total gross generation model and the central
region model are averages of the MEA and PEA system. Electricity prices in the
EGAT’s northeastern, northern, and southern models are averages in the PEA system.
Two specifications are proposed for the peak demand model i.e.
3
nD t = CON +  A j nD t  j +  M j nM1t  j + T nTEMPt + P nPRICE t 1
jIS
j=0
+ D2 FEB + D3MAR + D4 APR + D5 MAY + D6 JUN + D7 JUL + D8 AUG
+ D9SEP + D10 OCT + D11NOV + D12 DEC + u t
(6.1)
nD t = CON +  A j nD t  j + B*t + T nTEMPt + P nPRICE t 1 + D 2 FEB + D3MAR
jIS
+ D4 APR + D5 MAY + D6 JUN + D7 JUL + D8 AUG + D9SEP + D10OCT
+ D11NOV + D12 DEC + u t
(6.2)
Estimation results of the proposed models are summarized in Table 6.1. The
93
model selection is based on the value of adjusted R2.
Estimation Results of EGAT’s Peak Demand Model
Table 6.1
Model (6.1)
Price variable
Model
Total Gross
Generation
Central
Northeast
North
South
6.2.1
sign
–
P–value
Neg.
Neg.
–
–
0.0008
0.0007
–
–
–
adj.R2
0.9880
Model (6.1) with EC
Price variable
P–value
adj.R2
sign
–
–
–
0.9741
0.9876
0.9634
0.9432
Neg.
Neg.
–
–
0.0042
0.0051
–
–
0.9755
0.9880
0.9675
0.9460
Model (6.2)
Price variable
sign
Neg.
P–value
0.0360
adj.R2
0.9830
Model (6.2) EC
Price variable
P–value
adj.R2
sign
0.5061
0.9859
Neg.
Neg.
Neg.
Neg.
Neg.
0.0015
0.0290
0.5117
0.3097
0.9711
0.9835
0.9545
0.9470
Neg.
–
Neg.
Neg.
0.0018
–
0.5914
0.3823
0.9733
0.9867
0.9719
0.9503
EGAT’s Total Gross Generation
Model (6.1) is selected as the long term and short term forecasting model since
the coefficient of the EC term is not significant.
nDEGAT
=  2.5438 + 0.3088 nDEGAT
+ 0.2451 nM1t 1 + 0.1197 nM1t 2
t
t 1
+ 0.6522 nTEMPt + 0.0721FEB  0.0010MAR  0.0096APR  0.0390MAY
 0.0149JUN  0.0272JUL  0.0104AUG  0.0074SEP  0.0089OCT
+ 0.0325NOV + 0.0096DEC
t = January 1999, February 1999, March 1999, …
(6.3)
6.2.2
EGAT’s Central Region
Model (6.1) without the EC term is selected as the long term forecasting
model and the same model with the EC term is selected as the short term forecasting
model. The two models are presented below
nEGAT_DCt =  3.0531 + 0.5227 nEGAT_D Ct 1 + 0.2989 nEGAT_DCt 12
 0.1623 nEGAT_DCt 14 + 0.2383 nM1t 2 + 0.4759 nTEMPtC
 0.1501 nPRICE t 1 + 0.0593FEB  0.0071MAR  0.0124APR
 0.0244MAY  0.0058JUN  0.0127JUL + 0.0001AUG + 0.0120SEP
+ 0.0078OCT  0.0119NOV + 0.0023DEC
(6.4)
nEGAT_DCt =  2.9308 + 0.5471 nEGAT_DCt 1 + 0.3158 nEGAT_DCt 12
 0.1884 nEGAT_DCt 14 + 0.2200 nM1t 2 + 0.4707 nTEMPtC
 0.1309 nPRICE t 1 + 0.0577FEB  0.0127MAR  0.0162APR
 0.0286MAY  0.0085JUN  0.0168JUL  0.0029AUG + 0.0089SEP
+ 0.0027OCT  0.0138NOV + 0.0014DEC + 0.2853u t 10
t = January 1999, February 1999, March 1999, …
(6.5)
94
EGAT’ Northeastern Region
Model (6.1) without the EC term is selected as the long term forecasting
model and the same model with the EC term is selected as the short term forecasting
model. The two models are presented below
NE
nEGAT_D tNE =  3.7218 + 0.4208 nEGAT_D tNE
1 + 0.1470 nEGAT_D t  2
NE
+ 0.2566 nEGAT_D tNE
12 + 0.1766 nM1t 1 + 0.4279 nTEMPt
 0.1488 nPRICE PEA
t 1 + 0.0042FEB  0.0265MAR  0.0729APR
 0.0837MAY  0.0750JUN  0.0623JUL  0.0510AUG  0.0377SEP
 0.0381OCT  0.0247NOV  0.0144DEC
(6.6)
NE
nEGAT_D tNE =  3.7461 + 0.3932 nEGAT_D tNE
1 + 0.1419 nEGAT_D t  2
NE
+ 0.2687 nEGAT_D tNE
12 + 0.1815 nM1t 1 + 0.4428 nTEMPt
 0.1313 nPRICE PEA
t 1 + 0.0031FEB  0.0292MAR  0.0738APR
 0.0851MAY  0.0760JUN  0.0629JUL  0.0514AUG  0.0384SEP
 0.0387OCT  0.0240NOV  0.0125DEC + 0.2151u t 5
t = January 1999, February 1999, March 1999, …
(6.7)
EGAT’ Northern Region
Model (6.1) without the EC term is selected as the long term forecasting
model and the same model with the EC term is selected as the short term forecasting
model. The two models are presented below
nEGAT_D tN =  1.9506 + 0.2719 nEGAT_D tN1 + 0.2482 nEGAT_D tN12
+ 0.2452 nM1t 3 + 0.3451 nTEMPtN + 0.0043FEB  0.0294MAR
 0.0414APR  0.0510MAY  0.0579JUN  0.0339JUL  0.0396AUG
 0.0173SEP  0.0410OCT + 0.0018NOV + 0.0144DEC
(6.8)
nEGAT_D tN =  1.4667 + 0.5639 nEGAT_DtN1 + 0.1374 nEGAT_D tN12
+ 0.1517 nM1t 3 + 0.2545 nTEMPtN + 0.0168FEB  0.0043MAR
 0.0234APR  0.0416MAY  0.0520JUN  0.0167JUL  0.0324AUG
 0.0100SEP  0.0425OCT + 0.0103NOV + 0.0026DEC  0.4334u t 1
+ 0.1827u t 6
t = January 1999, February 1999, March 1999, …
(6.9)
95
EGAT’ Southern Region
Model (6.2) without the EC term is selected as the long term forecasting
model and the same model with the EC term is selected as the short term forecasting
model. The two models are presented below
nEGAT_DSt =  7.3092 + 0.3145 nEGAT_DSt 1 + 0.4750 nM1t 3 + 0.8840 nTEMPtS
 0.0157FEB  0.0652MAR  0.0907APR  0.1018MAY  0.0835JUN
 0.1188JUL  0.0262AUG  0.0051SEP  0.0183OCT  0.0131NOV
 0.0003DEC
(6.10)
nEGAT_DSt =  8.8691 + 0.2025 nEGAT_DSt 1 + 0.5488 nM1t 3 + 1.0893 nTEMPtS
 0.0184FEB  0.0770MAR  0.1053APR  0.1148MAY  0.0941JUN
 0.1269JUL  0.0381AUG  0.0042SEP  0.0133OCT  0.0099NOV
+ 0.0069DEC + 0.1968u t 2 + 0.1972u t 3
t = January 1999, February 1999, March 1999, …
(6.11)
6.3 MEA’s Peak Demand Model
Peak demand in the MEA system is the maximum demand that MEA
purchases from EGAT in a given month. The MEA model have the same
specifications as the EGAT model with the following notations
D MEA
= peak demand MEA’s system in month t
t
TEMPtC = sum of average daily temperature in central region in month t
PRICE MEA
= average electricity price in MEA’s system in month t
t
Estimation Results of MEA’s Peak Demand Model
Table 6.2
Model (6.1)
Price variable
sign
–
P–value
adj.R2
–
0.9449
Model (6.1) with EC
Price variable
P–value
adj.R2
sign
–
–
0.9556
Model (6.2)
Price variable
Sign
–
Model (6.2) EC
Price variable
P–value
adj.R2
–
0.9685
sign
–
P–value
adj.R2
–
0.9801
Estimation results of the models are summarized in Table 6.2. Model (6.1)
without the EC term is selected as the long term forecasting model and the same
model with the EC term is selected as the short term forecasting model. The two
models are presented below
nD MEA
=  1.7915 + 0.3960 nM1t 1 + 0.7647 nTEMPtC + 0.1072FEB + 0.0436MAR
t
+ 0.0695APR + 0.0480MAY + 0.0723JUN + 0.0506JUL + 0.0475AUG
+ 0.0803SEP  0.0500OCT + 0.0700NOV + 0.0286DEC
(6.12)
96
nD MEA
=  1.7129 + 0.3881 nM1t 1 + 0.7685 nTEMPtC + 0.1053FEB + 0.0437MAR
t
+ 0.0688APR + 0.0485MAY + 0.0722JUN + 0.0510JUL + 0.0471AUG
+ 0.0810SEP + 0.0492OCT + 0.0709NOV + 0.0267DEC + 0.4727u t  2
(6.13)
6.4 PEA’s Peak Demand Model
The peak demand in the PEA distribution system is defined similar to the
MEA case. The basic models may be expressed as (6.1) and (6.2) where the
temperature variable is the cumulative average daily temperature in Thailand, TEMPt
and the price variable is the average PEA consumer electricity price per KWh,
PRICE PEA
.
t
The results of forecasting models of peak demand in the PEA distribution
system and the PEA regional distribution systems are summarized in Table 6.3. The
long–term forecasts of PEA’s peak demands follow the model (6.1) and the short–
term forecasts follow model (6.1) with EC terms.
nD MEA
=  1.7915 + 0.3960 nM1t 1 + 0.7647 nTEMPtC + 0.1072FEB + 0.0436MAR
t
+ 0.0695APR + 0.0480MAY + 0.0723JUN + 0.0506JUL + 0.0475AUG
+ 0.0803SEP  0.0500OCT + 0.0700NOV + 0.0286DEC
(6.14)
PEA
nDPEA
= 0.1404 + 0.2131 nDPEA
t
t 1 + 0.6285 nD t 12 + 0.1021 nM1t  2  0.2983u t 9
 0.3875u t 12
t = January 1999, February 1999, …
(6.15)
Estimation Results of PEA’s Peak Demand Model
Table 6.3
Model (6.1)
Price variable
Model
PEA
Central
Northeast
North
South
sign
P–value
adj.R2
–
–
–
–
–
–
–
–
–
–
0.9686
0.9698
0.8966
0.9599
0.9762
Model (6.1) with EC
Price variable
P–value
adj.R2
sign
–
–
–
–
–
–
–
–
–
–
0.9743
0.9741
0.9019
0.9683
0.9779
Model (6.2)
Price variable
Model (6.2) EC
Price variable
sign
P–value
adj.R2
sign
P–value
adj.R2
Neg.
Neg.
Neg.
–
Neg.
0.1036
0.1896
0.5771
–
0.7353
0.9885
0.9713
0.9164
0.9629
0.9738
–
–
0.0422
0.1680
–
0.6535
–
0.9748
0.9251
0.9699
0.9794
Neg.
Neg.
–
Neg.
The model of long–term forecasts of peak demands in the PEA central region
is chosen to use the model (6.2).
nPEA_DCt = 2.7125 + 0.2725 nPEA_D Ct 1 + 0.0052t + 0.4982 nTEMPtC
 0.0999 nPRICE t 1 + 0.0665FEB + 0.0131MAR + 0.0024APR
 0.0056MAY + 0.0044JUN  0.0091JUL  0.0094AUG + 0.0133SEP
 0.0072OCT + 0.0184NOV  0.0404DEC
(6.16)
97
The short–term forecast model of peak demands in the PEA central region is
the model (6.2) with EC terms.
nPEA_DCt = 2.5258 + 0.3558 nPEA_DCt 1 + 0.0047t + 0.4258 nTEMPtC
 0.1122 nPRICE Ct1 + 0.0575FEB + 0.0137MAR + 0.0008APR
 0.0077MAY  0.0006JUN  0.0104JUL  0.0113AUG + 0.0081SEP
 0.0100OCT + 0.0123NOV  0.0482DEC  0.3985u t 2
t = 1(January 1999), 2(February 1999), …
(6.17)
The long–term and short–term forecast models of peak demands in the PEA
northeast region are the model (6.2) and the model (6.2) with EC terms respectively as
the following details.
nPEA_D tNE = 4.2325 + 0.0036t + 0.4614 nTEMPtNE + 0.0480 nPRICE t 1
+ 0.0052FEB  0.0067MAR  0.0183APR  0.0318MAY  0.0385JUN
 0.0476JUL  0.0062AUG  0.0151SEP  0.0071OCT + 0.0302NOV
+ 0.0099DEC
(6.18)
nPEA_D tNE = 4.2521 + 0.0038t + 0.4646 nTEMPtNE  0.1033 nPRICE t 1 + 0.0053FEB
 0.0072MAR  0.0184APR  0.0384MAY  0.0406JUN  0.0488JUL
 0.0067AUG  0.0175SEP  0.0121OCT + 0.0258NOV + 0.0076DEC
 0.4377u t 9
t = 1(January 1999), 2(February 1999), …
(6.19)
In the PEA north region, the long–term and short–term forecasts of peak
demands are modeled as (6.2) and (6.2) with EC terms respectively as follows.
nPEA_D tN = 5.6967  0.2527 nPEA_D tN12 + 0.0055t + 0.4840 nTEMPtN + 0.0010FEB
+ 0.0118MAR + 0.0243APR + 0.0062MAY  0.0184JUN + 0.0095JUL
+ 0.0248AUG + 0.0144SEP + 0.0059OCT + 0.0506NOV + 0.0383DEC
(6.20)
nPEA_D tN = 5.1877  0.1443 nPEA_D tN12 + 0.0050t + 0.4453 nTEMPtN + 0.0017FEB
+ 0.0101MAR + 0.0197APR + 0.0012MAY  0.0223JUN + 0.0051JUL
+ 0.0225AUG + 0.0147SEP + 0.0032OCT + 0.0431NOV + 0.0323DEC
 0.5407u t 9
t = 1(January 1999), 2(February 1999), …
(6.21)
98
In the PEA south region, the long–term and short–term forecasts of peak
demands follow the model (6.1) and model (6.1) with EC terms respectively as the
following details.
nPEA_DSt =  0.0921 + 0.2958 nPEA_DSt 1 + 0.0032t + 0.7698 nTEMPtS
 0.0203 nPRICE PEA
t 1 + 0.0139FEB  0.0038MAR  0.0361APR  0.0335MAY
 0.0392JUN  0.0280JUL  0.0102AUG  0.0130SEP + 0.0061OCT
+ 0.0034NOV + 0.0046DEC
(6.22)
nPEA_DSt = 1.2382 + 0.1884 nPEA_DSt 1 + 0.0038t + 0.6865 nTEMPtS
 0.0273 nPRICE PEA
t 1  0.0210FEB + 0.0032MAR  0.0206APR  0.0218MAY
 0.0307JUN  0.0214JUL  0.0079AUG  0.0033SEP + 0.0086OCT
+ 0.0055NOV + 0.0084DEC + 0.3141u t 5  0.5252u t 11
t = 1(January 1999), 2(February 1999), …
(6.23)