ENERGY SECTOR PROJECTIONS
Overview
Energy sector comprises energy industries that supply final energy vectors. This sector is also often referred
to as the “transformation sector” because it transforms primary energy to final energy forms. It include:
- power plants that produce electric energy and, sometimes, heat
- refineries that produce fuels for final use,
- coke and coal gas producing plants
- district heating plants and mining
In many statistical systems (Eurostat, IEA) it include also the consumption of natural gas network and
storage sites, in particular high pressure pipelines, and also oil pipelines. However the consumption of
those system is included in the transport sector according to UNFCCC reporting guidelines and we will see
them in the transport workshop.
By far the most important contribution to emissions is linked to power plants, with refineries that also
contribute to a sizeable quantity. Coke plants will be addressed in the industrial section because nowadays
the production of coal gasses is only a secondary product of steel producing plants.
Estimating the projected emissions of those two subsectors, power plants and refineries require the
knowledge of historical evolution and the projection of the following:
-
Activity factor (electricity, fuel consumption)
Specifications of technologies that will transform primary sources
Estimate of renewable electricity production / biofuels
Emission factors
Those items are sector specific, so they will be discussed at subsector level
Exogenous data needed for the energy sector projection estimates
For the purpose of projecting activity data other macroeconomic variables are needed:
- GDP historical data, in constant money, from at least year 2000 to now;
- GDP projection, in constant money, from now to 2030
- Population data in 2000, 2010 and 2015. Expected population in 2020 and 2030
GDP is needed in constant prices (not market prices) to skip the distortion effect of inflation.
The missing data will be taken from Turkey Sixth NC. The relevant table from chapter 5 of NC6 is attached
below.
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Power plants
Activity factor
The activity factor is the electricity produced. To project this quantity you can use the projection of the
consumption in sector of final use (industry, transport, civil), sum grid losses and you get the net electricity
production.
The import / export of electricity has also to be considered. After including import/export the net electricity
production is known. Gross electricity production will depends from primary source and plant efficiency, we
will see in detail.
The estimate of electricity required by final uses can be the result of the calculation by an integrated
bottom up model or the outcome of projection for each final use sector. In the next workshops we will see
how to calculate it. On my view this road is the best way to proceed and it gives the possibility of collecting
the expertise of different sectors and the effect of technology improvements that are difficult to quantify.
To estimate electricity consumption there are also other procedures. This commodity is so widely used and
well known that the experience of other countries can be used as guidance for the estimation.
Let us see how. I will show below broad averages of electricity consumption on a “per capita” basis and on
a “per GDP basis”. Those numbers are averages that include everything, but they are stable.
0.600
2013 data: kwh /GDP, 1000 $ 1995 ppa
0.500
0.400
0.300
0.200
0.100
Iran
India
Giappone
US
Brasile
Turchia
Argentina
Russia
Svizzera
Norvegia
Ungheria
Svezia
Spagna
Slovenia
Romania
Regno Unito
Ceca
Slovacca
Polonia
Portogallo
Paesi Bassi
Italia
Grecia
Irlanda
Germania
Francia
Estonia
Finlandia
Danimarca
Croazia
Belgio
Bulgaria
UE 27
Austria
0.000
Let us notice from this first figure that the data are estimated on constant prices and using also “ppa”
(purchasing power parity) so that differences in prices between countries can be taken into account.
Having said that you can see that the differences between many countries are not so huge, even if they are
on different level of economic development. The data for Turkey is 0.187 and the average of EU is 0.224.
The latter value or an average between actual data and EU average can be directly connected to estimates
of GDP growth and calculate an electricity consumption for the objective year.
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25.00
2013 data, MWh/inhabitant
20.00
15.00
10.00
5.00
Iran
India
US
Giappone
Brasile
Turchia
Argentina
Svizzera
Russia
Norvegia
Svezia
Ungheria
Spagna
Slovenia
Romania
Slovacca
Regno Unito
Ceca
Polonia
Portogallo
Paesi Bassi
Italia
Grecia
Irlanda
Germania
Francia
Estonia
Finlandia
Croazia
Danimarca
Belgio
Bulgaria
UE 27
Austria
0.00
As can be seen in the previous figure electricity consumption is also well correlated to population. The
actual value for Turkey is 2.64 while the weighted average for EU 27 is much higher, 5.49 MWh per capita.
Excluding Finland and Sweden, the value is a bit lower, around 5 MWh/inhabitant.
It is possible also to use the population average for projection: Turkey is rather low in the consumption per
inhabitant data, a bit less than half the EU average. However in this case it is not clear the time necessary
to reach the average value. It may require time, probably more than the 14 years between now and 2030.
Additionally the peak level of consumption per capita is different among countries depending on industrial
consumption and the time when the peak is reached. The more time is passing lower is the peak. So the
use of consumption per GDP is more suitable for the calculation of an estimate total consumption of
electricity.
Let us now to show two weak point of using international averages to estimate total electricity
consumption.
The first shortcoming has been already highlighted, there is no explicit connection with efficiency
improvements, consumption is independent from the efficiency policy that have been implemented. In
other words, no matter how many better appliances and lighting a country implement its consumption will
always be the same if calculated with this broad averages. This has also other implications: if you
implement a policy of electric car diffusion, consumption will grow as well as if you implement a lot of heat
pumps for heating / cooling. Your projection will not reflect this policies and will be wrong. This has to be
highlighted.
The second one is more subtle, it can be referred to as a “saturation effect”. Electricity use cannot grow
forever, a certain time you will reach a peak level that is different between countries and it is difficult to
forecast. Let us see the case for Italy.
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7.0
6.0
5.0
4.0
3.0
2.0
Italy, historical evolution of MWh / inhabitant
1.0
0.0
1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015
0.26
0.24
0.22
0.20
0.18
0.16
Italy, historica data, kWh / 1000 $, 1995
0.14
0.12
0.10
1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015
In the above figures you can see that around 2007, if measured on a per capita basis, or even before,
around 2003, if measured on a GDP basis, the specific consumption of electricity has stopped to grow in
Italy. This finding is common to all developed countries: above a certain percentage the electricity specific
consumption do not grow any more.
I underline that this is not (only) the product of an economic crisis, it is more connected to the ageing of
population and to the changes in industrial structure / production.
I do not have historical time series for other EU countries. In the case of Turkey I think we are far from the
saturation of the consumption market, however it has to be considered that the grow cannot continue
forever. Indicator of specific consumption offer guidance for this.
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Technological changes / renewable use
Given a fixed level of electricity production GHGs emissions can change a lot if you consider or not the
construction of more efficient power plants and changes in primary sources. Of course not all existing
plants will be replaced in 14years from now, so the simulation of technological changes has to consider, at
the same time, existing plants still working and new plants, both renewable, fossil or nuclear, as planned in
Turkey.
Again optimization model, if available, will take care of all this, however it is possible to use a small, simple,
simulation model to explore future scenarios. The use of simulation model is also very useful to define
precisely all the technologies that will be available for use in 2030 and renewable use. So it can be used in
standalone mode or to prepare the input to other models.
We will see in the excel file how to proceed. In general terms a series of simulation have to be performed
until a scenario that satisfy all conditions have been found. Additionally the simulations have to be
repeated for all years of interest. In the case of a scenario submission to international organization at least
the expected production / emissions in 2020 and 2030 have to be performed.
Before to start to use the model some info is needed:
- Due to the fact that a certain production has to be satisfied, information is needed on remaining
use full life of existing plants. In other term the available capacity in 2020 and 2020.
- Projected renewable use in 2020 and 2030 is also needed
- Other eventually planned carbon free plants (nuclear)
- Electricity required from network (consumption + network losses) is also needed.
In the file there are some data taken from NC 6 of Turkey for the general use of fuels and renewable and
from Italian plants and network for what is connected to efficiency.
Emission factors
They depend on primary fuel used. They can be derived from existing inventory data. Technological
improvement and / or fuel switching will not change a lot the primary sources emission factors.
Unless there are concrete plans we recommend to use existing EF estimates for projections.
Illustration of the simulation model and operating instructions.
The model consist in a list of technologies that ”produce” electricity linking capacity, operating hours, gross
and net efficiency. The most representative existing technical option are included. Technical data are taken
from the Italian database, the are there for guidance. The scenario to be effective Turkish data have to be
inserted, especially for existing plants.
The model list the plant in four main groups:
-producers,
-self producers (cogeneration)
- city plants
-small producers
The differences are in size, efficiency and fuel used.
Plants are also grouped in fossil fuel sources and non fossil sources. For the first group a summary of all fuel
consumption is also included, so that it is possible GHGs emission calculation.
After that all gross electricity “produced” is taken together and net electricity produced is astimated. After
this there is consideration for import – export and a box to estimate grid losses. In the end all electricity
“delivered” is calculated.
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The model comprise a small software in the form of a macro of the excel sheet that allow the fossil fuel
plants to match exactly a certain demand. There is also a section where total fossil fuel consumption can
be checked against actual data, to calibrate the model.
Refinery sector
According to our experience it is not possible to estimate a consumption of liquid fuels without a simulation
of the circulating fleet of vehicles and the needs of air / marine transport. In other word a system like a
certain amount of oil per inhabitant or per GDP is not reliable. Some statistics do exist (reference IEA
publications) however those numbers have limited use because in a modern economy there are many
possibility to use different primary sources, following the economic convenience and / or political
considerations.
So sound future consumption data has to be derived from sectorial estimates, in particular transport and
petrochemical sectors.
There is the possibility of import / export of products. This is standard practice for operators and allows to
maximize the use of existing refineries. Changing import / export results in greatly different refinery
consumption figure. This import / export activity follow oil market prices, that are word averages and
cannot be estimated from an emission projection team.
To perform those estimates you need models that simulate more than one country. My advice is to keep
constant the actual import/export data and ask operators of possible market evolutions. EU has a word
model to estimate oil market prices, as already seen in general presentations.
What can be done here is a guide to estimate refinery consumption on the basis of a certain production of
liquid fuels.
The excel sheet reports those data, averages from Italian data. The first set of specific consumption
represent the situation around year 2000 , the second set of data is the actual figure after the closure of
the more old refineries and the upgraded quality requirements of products.
The activity data required for calculation is an estimate of liquid fuel production, with the breakdown for
each fuel. Final consumption estimates are only part of the answer, as we will see a refinery is a vey
complex environment and other info is needed to make a correct calculation.
Emission factors
They depend on primary fuel used. They can be derived from existing inventory data.
Illustration of the simulation model and operating instructions,
In this case we are not speaking a software, we are simply performing some calculations, the important
part of this data sheet it the list of all info that is needed to match existing consumption – production data.
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Proposed hands on exercises for day 1 and day 2.
1) Prepare an estimate of electricity production in 2020 and 2030, to be used as objective for the
simulation.
2) Define new renewable generation from now to 2030 (to be taken from NC6).
3) Define other electricity generation plants that will be available in 2030 (to be taken from NC6,
notably nuclear).
4) Loading of data in the simulation model, GHG emissions estimate in 2030.
5) Estimation of refinery consumption:
a. Projected transport fuel use in 2030 using CRF and mitigation scenario data for energy
sector from NC 6;
b. Refinery GHG emissions estimate on the basis of transport fuel consumption of 2030.
For memory:
improvements in 2030 of the electricity generation according to NC6
5.4. Mitigation Scenario
In mitigation scenario, emissions for 2012-2030 were developed based on mitigation measures
from various policy papers and strategic documents. The plans and policies to be implemented are
listed below for each sector.
Electricity Generation Sector
The plans and policies in electricity generation sector are listed below;
• Increasing capacity of production of electricity from solar power to …… GW until 2030,
• Increasing capacity of production of electricity from wind power to …. GW until 2030,
• Tapping the full hydroelectric potential, (level?)
• Commissioning of a nuclear power plant until 2030 (capacity?),
• Reducing electricity transmission and distribution losses to 15% at 2030 (actual level?),
• Rehabilitation of public electricity generation power plants,
• Establishment of micro-generation, co-generation systems and production on site at electricity
production.
GHG emission growth:
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