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Predicting the Electricity Demand
of Turkey Using the Past Data
Assist. Prof. M. Erdem Gnay
Energy Systems Engineering
Istanbul Bilgi University
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Energy and Society
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ENERGY AND SOCIETY
The more a country is developed themore energy it consumes.
Populationand wealthof a country
directly affect the energy consumption
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List of countries by population
Ref: http://en.wikipedia.org/wiki/List_of_countries_by_population
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Map of Countries:Gross Domestic Product
GDP is the addition of the consumer spending, investment spending, government
spending and the value of the exports and subtract the value of the imports .
This measure is often used to find out the health of a country in an economic way.
A country with a high value of GDP can be called a large economy.
Ref: http://simple.wikipedia.org/wiki/Gross_domestic_product
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Map of Countries:
CO2emissions
The more energy is consumed the more pollutants are
released.
Ref: http://en.wikipedia.org/wiki/List_of_countries_by_carbon_dioxide_emissions
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ENERGY AND SOCIETY
The developed countries consume the most energyand produce the most pollution, primarily due tothe increase in the amount of energy per person.
Ref: Introduction to Renewable Energy, Abbas, Ghassemi, CRC Press
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Turkey is getting more populated
>20 Million
1950
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>30 Million
1960
Turkey is getting more populated
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0
10
20
30
40
50
60
70
80
1935 1955 1975 1995 2015
Population(Millio
nPeople)
Year
>50 Million
1985
Turkey is getting more populated
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0
10
20
30
40
50
60
70
80
1935 1955 1975 1995 2015
Population(Millio
nPeople)
Year
~80 Million
2014
Turkey is getting more populated
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Gross Domestic Product Per Capita of
Turkey is Also in an Increasing Trend
0
5,000
10,000
15,000
20,000
1975 1985 1995 2005 2015
G
DP
percapita(I
nt$)
Year
GDP per
capita is anindicatorof theaverage
livingstandards
http://www.google.com.tr/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&docid=RAXzOb36dT1--M&tbnid=JZ6zsqQGlUmmYM:&ved=0CAUQjRw&url=http://www.sundaylawbystealth.com/usd.htm&ei=Osx1U-_wJML0Ocj1gdAL&bvm=bv.66699033,d.ZGU&psig=AFQjCNFECMSNsqdR2mpheaftRHL0jIVArw&ust=1400315307902667http://www.google.com.tr/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&docid=RAXzOb36dT1--M&tbnid=JZ6zsqQGlUmmYM:&ved=0CAUQjRw&url=http://www.sundaylawbystealth.com/usd.htm&ei=Osx1U-_wJML0Ocj1gdAL&bvm=bv.66699033,d.ZGU&psig=AFQjCNFECMSNsqdR2mpheaftRHL0jIVArw&ust=1400315307902667http://www.google.com.tr/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&docid=RAXzOb36dT1--M&tbnid=JZ6zsqQGlUmmYM:&ved=0CAUQjRw&url=http://www.sundaylawbystealth.com/usd.htm&ei=Osx1U-_wJML0Ocj1gdAL&bvm=bv.66699033,d.ZGU&psig=AFQjCNFECMSNsqdR2mpheaftRHL0jIVArw&ust=1400315307902667http://www.google.com.tr/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&docid=RAXzOb36dT1--M&tbnid=JZ6zsqQGlUmmYM:&ved=0CAUQjRw&url=http://www.sundaylawbystealth.com/usd.htm&ei=Osx1U-_wJML0Ocj1gdAL&bvm=bv.66699033,d.ZGU&psig=AFQjCNFECMSNsqdR2mpheaftRHL0jIVArw&ust=1400315307902667http://www.google.com.tr/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&docid=RAXzOb36dT1--M&tbnid=JZ6zsqQGlUmmYM:&ved=0CAUQjRw&url=http://www.sundaylawbystealth.com/usd.htm&ei=Osx1U-_wJML0Ocj1gdAL&bvm=bv.66699033,d.ZGU&psig=AFQjCNFECMSNsqdR2mpheaftRHL0jIVArw&ust=1400315307902667http://www.google.com.tr/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&docid=RAXzOb36dT1--M&tbnid=JZ6zsqQGlUmmYM:&ved=0CAUQjRw&url=http://www.sundaylawbystealth.com/usd.htm&ei=Osx1U-_wJML0Ocj1gdAL&bvm=bv.66699033,d.ZGU&psig=AFQjCNFECMSNsqdR2mpheaftRHL0jIVArw&ust=1400315307902667http://www.google.com.tr/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&docid=RAXzOb36dT1--M&tbnid=JZ6zsqQGlUmmYM:&ved=0CAUQjRw&url=http://www.sundaylawbystealth.com/usd.htm&ei=Osx1U-_wJML0Ocj1gdAL&bvm=bv.66699033,d.ZGU&psig=AFQjCNFECMSNsqdR2mpheaftRHL0jIVArw&ust=1400315307902667http://www.google.com.tr/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&docid=RAXzOb36dT1--M&tbnid=JZ6zsqQGlUmmYM:&ved=0CAUQjRw&url=http://www.sundaylawbystealth.com/usd.htm&ei=Osx1U-_wJML0Ocj1gdAL&bvm=bv.66699033,d.ZGU&psig=AFQjCNFECMSNsqdR2mpheaftRHL0jIVArw&ust=1400315307902667http://www.google.com.tr/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&docid=RAXzOb36dT1--M&tbnid=JZ6zsqQGlUmmYM:&ved=0CAUQjRw&url=http://www.sundaylawbystealth.com/usd.htm&ei=Osx1U-_wJML0Ocj1gdAL&bvm=bv.66699033,d.ZGU&psig=AFQjCNFECMSNsqdR2mpheaftRHL0jIVArw&ust=1400315307902667http://www.google.com.tr/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&docid=RAXzOb36dT1--M&tbnid=JZ6zsqQGlUmmYM:&ved=0CAUQjRw&url=http://www.sundaylawbystealth.com/usd.htm&ei=Osx1U-_wJML0Ocj1gdAL&bvm=bv.66699033,d.ZGU&psig=AFQjCNFECMSNsqdR2mpheaftRHL0jIVArw&ust=1400315307902667http://www.google.com.tr/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&docid=RAXzOb36dT1--M&tbnid=JZ6zsqQGlUmmYM:&ved=0CAUQjRw&url=http://www.sundaylawbystealth.com/usd.htm&ei=Osx1U-_wJML0Ocj1gdAL&bvm=bv.66699033,d.ZGU&psig=AFQjCNFECMSNsqdR2mpheaftRHL0jIVArw&ust=1400315307902667http://www.google.com.tr/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&docid=RAXzOb36dT1--M&tbnid=JZ6zsqQGlUmmYM:&ved=0CAUQjRw&url=http://www.sundaylawbystealth.com/usd.htm&ei=Osx1U-_wJML0Ocj1gdAL&bvm=bv.66699033,d.ZGU&psig=AFQjCNFECMSNsqdR2mpheaftRHL0jIVArw&ust=14003153079026678/21/2019 Energy-Society Relation and Demand Prediction
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Energy Demand of Turkey
The energy demand of Turkey increases year by year asthe population rises and as we become more and more
dependent on power hungry machines and devices.
50
100
150
200
250
300
1975 1985 1995 2005 2015
Electrici
tyDeman
d(TWh
)
Year~20 TWh
~250 TWh
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Energy Supply of Turkey in 2013
44%
25%
25%
4% 2%
Natural Gas
Coal
Hydroelectricity
Renewable
Energy
Liquid Fuels
Reference: Ministry of Energy and Natural Sources Web Page (www.enerji.gov.tr)
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Foreign Dependence of Energy of Turkey
Reference: Ministry of Energy and Natural Sources Strategic Plan 2010
% Dependence
on Foreign Countries
E D d f T k
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Energy Demand of Turkey
Problem:
The energy demand of Turkey is expected to increase
in an accelerating trend in the future.
Energy sources satisfying thisdemand will become totally
insufficient.
The foreign dependence ofenergy will even become more
serious in the future
E D d f T k
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Energy Demand of Turkey
Solution:
Investments on alternative energy sources must be encouraged.The local resources must be used more effectively
The types of energy sources must also be increased.
We should predict the future energydemandfrom the historical data
with a good accuracy.
We need to know the exact energydemand in the future years for these
plans to be effective
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Predicting the Energy Demand of Turkey
What happens if we cannot predict the futureelectricity demand accurately?
Overestimation would lead tounnecessary idle capacity thatmeans wasted financial resources.
Underestimation of thedemand would lead toblackouts, economic crisis etc.
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Predicting Energy Demand for the FutureWhich Factors May Affect the Demand?
We know that
Populationand
wealthof a
country directly
affect the
energy
consumption.
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Inflation?
It may have an
effect on theenergy demand.
Predicting Energy Demand for the FutureWhich Factors May Affect the Demand?
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Summeraveragetemperature?
The hotter it isin the summerthe more we
use airconditioners.
Predicting Energy Demand for the FutureWhich Factors May Affect the Demand?
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Constructing
theDatabase
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Year PopulationGDP per
capita ($)
Inflation
(%)
Avg T Sum
(oC)
Demand
(TWh)
1975 40347719 2020 16.26 23.13 15.7
1976 41225567 2306 19.33 21.64 18.6
1977 42103414 2481 46.77 23.03 21.1
2008 71517100 15021 10.06 24.64 198.1
2009 72561312 14550 6.53 23.78 194.1
2010 73722988 16003 6.40 25.22 210.4
2011 74724269 17781 10.45 23.87 230.3
2012 75627384 18315 6.16 24.69 242.4
2013 76667864 18834 7.40 23.85 245.5
2014 ? ? ? ? Unknown
2015 ? ? ? ? Unknown
? ? ? ? Unknown
? ? ? ? Unknown2020 ? ? ? ? Unknown
The Data
Used for
training
(constructingthe model)
Used for validation(checking whether
the model worksor not)
Turkishstatisticalinstitute
Used for Testing(predictingenergy demand
for the future)
OECD: Organisation forEconomic Co-operationand Development
Turkish StateMeteorological Service
Turkish ElectricityTransmission Company
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Demand (TWh)
Pop: Population
Gdp: gdp per capita (Int $)
Inf: Inflation (%)
Ts: Average summer temperature (oC)
Step 1: Constructing the Model:Linear Multiple Regression to Model theDemand between the Years 1975-2008
0 1 2 3 4infDemand a a pop a gdp a a Ts
Advantage of Multiple Regression: It is not a black box modeling i.e artificial neural
networks.
After determining the coefficients we can use the
equation for predicting the demand of any year.
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Modeling the Demand between for the Years 1975-2008
Variables Coefficient
Standard
Error of theCoefficient t value p value
constant -198 55.9 -3.54 0.0014
Population 1.60E-06 4.22E-07 3.80 0.00069
GDP 0.010 1.35E-03 7.30 0.00000
inflation -0.19 0.0552 -3.42 0.0019
Ts 5.58 2.51 2.22 0.034
The two-tailed P values are smaller
than 0.05 By conventional criteria, all the
variables are considered to bestatistically significant.
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Modeling the Demand between for the Years 1975-2008
6198 1.60 10
0.010 0.19 inf 5.58
Demand pop
gdp Ts
Demand (TWh)
Pop: Population
Gdp: gdp per capita (Int $)
Inf: Inflation (%)
Ts: Average summer temperature (oC)
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Step 2: Validating the Model:Linear Multiple Regression to Model theDemand between the Years 2009-2013
6198 1.60 10
0.010 0.19 inf 5.58
Demand pop
gdp Ts
Year PopulationGDP per
capita ($)
Inflation
(%)
Avg T Sum
(oC)
Demand
(TWh)
2009 72561312 14550 6.53 23.78 194.1
2010 73722988 16003 6.40 25.22 210.4
2011 74724269 17781 10.45 23.87 230.3
2012 75627384 18315 6.16 24.69 242.4
2013 76667864 18834 7.40 23.85 245.5
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We normally know the pop., gdp, inf. and Ts,between the years 2009-2013.
The problem is, we do not know the valuesof these in the future.
If we can correctly estimate them betweenthe years 2009-2013, then we can alsopredict them for the future years.
We need another tool to predict thecorresponding values.
Step 2: Validating the Model:Linear Multiple Regression to Model theDemand between the Years 2009-2013
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Autoregressive Regression
( ) .( 1), .( 2), .( 3)...Population t f Popl t Popl t Popl t
( ) ( 1), ( 2), ( 3)...GDP t f GDP t GDP t GDP t
For example the population in the year 2014 depends on
the population 2013, 2012, 2011 etc.
The same is true for GDP and other variables.
The autoregressive regression model specifies that an
output variable depends on its own previous values.
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Autoregressive Regression to Predict the
Population Between the Years 2009-2013
( ) 408779 1.01 ( 1)Population t Population t
0
20
40
60
80
1935 1955 1975 1995 2015
Popu
lation
(Millio
ns)
Year
Real Estimated Predicted
R2predicted=0.995
R2estimated=1.000
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Autoregressive Regression for to Predict the GDPper Capita Between the Years 2009-2013
( ) 7.97 1.06 ( 1)GDP t GDP t
0
5,000
10,000
15,000
20,000
1975 1985 1995 2005 2015
GDP
percap
ita
(In
t$)
Year
Real Estimated Predicted
R2estimated=0.988
R2predicted=0.823
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Autoregressive Regression to Predict the
Inflation % Between the Years 2009-2013
2
( ) 1.00 1.40 ( 1) 0.0062 ( 1)Inf t Inf t Inf t
-20
0
20
40
60
80
100
120
140
1955 1975 1995 2015
In
flation%
Year
Real Estimated Predicted
R2estimated=0.722
R2predicted=0.499
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Autoregressive Regression to Predict the AverageSummer Temperature Between the Years 2009-2013
( ) 1.72 0.45 ( 1) 0.22 ( 2) 0.09 ( 3)0.11 ( 4) 0.41 ( 5) 0.05 ( 6)
Ts t Ts t Ts t Ts t Ts t Ts t Ts t
21.5
22.0
22.523.0
23.5
24.0
24.5
25.0
25.5
1975 1985 1995 2005 2015AverageSumm
erTemperature(oC)
Year
Real Estimated Predicted
R2estimated=0.597
R2predicted
=0.215
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Predicting the Electricity Demandfor the years Between 2009-2013
6198 1.60 10
0.010 0.19 inf 5.58
Demand pop
gdp Ts
Year Population GDP per capita ($)Inflation
(%)
Avg T Sum
(oC)
2009 72561384 15645 12.48 24.29
2010 73615026 16607 7.89 24.21
2011 74678109 17627 7.72 24.32
2012 75750718 18710 12.98 24.61
2013 76832939 19859 7.40 24.72
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Predicting the Electricity Demandfor the years Between 2009-2013
50
100
150
200
250
300
1975 1985 1995 2005 2015
Electrici
tyDemand
(TWh)
Year
Real Estimated Predicted
R2estimated=0.983
R2predicted=0.809
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Predicting the Electricity Demandfor the years Between 2009-2013
190
210
230
250
270
290
2008 2010 2012 2014
Electrici
tyDemand
(TWh)
Year
Real Demand Predicted by the current model
R2=0.81
Average% Error = 3.1%
190
210
230
250
270
290
2008 2010 2012 2014
Electrici
tyDeman
d(TWh)
Year
Real Demand
EPDK High Demand Scenario
EPDK Low Demand Scenario
R2=0
Average
% Error = 13.5% R2=0Average
% Error = 10.2
Republic of Turkey Energy Market
Regulatory Authority Prediction
Overestimation
Current Model
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The data between 1975 to 2013 were usedto construct a multiple regression model.
Population, gdp per capita, inflation and
average summer temperature werepredicted for the years 2014-2020. These values were used to calculate the
energy demand.
Step 3: Using the Data of the Past to Predict
the Demand between the Years 2014-2020
6181 1.61 10
0.010 0.19 inf 4.80
Demand pop
gdp Ts
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80
160
240
320
1975 1984 1993 2002 2011 2020
Electr
icity
Demand
(TWh)
Y
Real Estimated Predicted
R2estimated=0.991
~320 TWh
Step 3: Using the Data of the Past to Predict
the Demand between the Years 2014-2020
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