EST Demand ModuleCalibration

July 2019, Ankara – Turkey

➢ GAMS files

➢ GAMS Demand Module program flow

➢ Calibration – Demand Module

➢ Industry

➢ Transport

➢ Residential & Tertiary

➢ Assignments – Fixing Calibration errors

Contents

GAMS Files

Main•00_EST_main: provides control over all EST modules

Data

•01_EST_data: calls the following .gms files related to data management

•01a_EST_def: includes definitions of sets, parameters, variables & reads data from CommonData files

•01b_EST_read: reads input data from input Excel files of Demand and Power/Heat Supply Module

•01c_EST_prices: calculates pre-tax and end-user prices of fuels (including excise tax and VAT)

•01d_EST_modelV: includes all equations of Demand, Power/Heat Supply and Biomass Modules

•01e_EST_assign: includes assignment of parameters for Power/Heat Supply Module

Demand

•02_EST_runD: calls the following .gms files related to Demand Module

•02a_EST_DlinkageIN: loads updated electricity & bio-energy prices from the results of Supply and Biomass Modules

•02b_EST_dyncalib & dyncalib1: includes dynamic initialization of variables

•02c_solve_FX_EST_Demand: solves the Demand Module problem for the base year (2015)

•02d_EST_rep: calculates reporting parameters of Demand Module as input in other Modules

•02e_EST_assign: includes assignments of parameters and variables

•02e_EST_fixVAR: sets fixed values for variables (initialization)

•02e_EST_update: updates parameter values

•02f_solve_EST_Demand: solves Demand Module

•02g_EST_DlinkageOUT: produces a log file that informs whether the Demand Module has been solved for a certain scenario and number of iteration

GAMS Demand Module program flow

• The full version of the model is located on the folder C:\EST

• Open the project on the folder C:\EST1\model\EST1_main.gpr

• Open the GAMS files:

GAMS model structure

• 00_EST_main.gms• 01_EST_data.gms• 01a_EST_def.gms• 01b_EST_read.gms• 01c_EST_prices.gms• 01d_EST_modelV.gms• 01d_EST_assign.gms

• 02_EST_runD.gms• 02a_EST_DlinkageIN.gms• 02b_EST_dyncalib.gms• 02c_solve_FX_EST_Demand.gms• 02d_EST_rep.gms• 02e_EST_assign.gms• 02e_EST_fixVar.gms• 02e_EST_update.gms• 02f_solve_EST_Demand.gms• 02g_EST_DlinkageOUT.gms

• These are the necessary files for:

➢ Importing data from the excel file

➢ Reading the model

➢ Solving the demand

➢ Linking the demand module with the rest of the model

GAMS program flow

00_EST_main.gms

01_EST_data.gms

01a_EST_def.gms

01b_EST_read.gms

01c_EST_prices.gms

01d_EST_modelV.gms

01d_EST_assign.gms

02_runD.gms

02a_EST_DlinkageIN.gms

02b_EST_dyncalib.gms

…..

02g_EST_DlinkageOUT.gms

$call

$include

$include$call03_runPHt.gms

• The model reads first the data and then runs the demand module. Demand provides data to the power supply module

• Power supply module is then executed

• The option of execution of the demand module is given by the command line, in the file 00_EST_main.gms:

• The execution of the demand module depends on the control variable rund.

• The projection years depend on the control variable horizon.

• Execution of the reference scenario.

• The execution of demand follows the execution of the data related .gms files.

00_EST_main.gms

00_EST_main.gms

• The control variable rundata controls the execution of the data import files

• If rundata equals to 1 then the model, then 01_EST_data.gms is executed

• $call expression is used, which is equivalent to the writing commands in the command line

• Scenario, paths and projection are used as arguments and have already been defined

• The option ‘s=’ creates a file save with all data and the results produced by the .gms files

• Saved files end with .g00. They include model equations and parameters assignment. In this case these are saved on the folder Data_reference.g00

• Saved data can be accessed on the command line with the option ‘r=‘

00_EST_main.gms

• The control variable runD controls the execution of the demand module:

• If rund equals to 1 then the model, then 02_EST_rund.gms is executed. Otherwise this step is skipped.

• As in this case rund equals to 1, the demand module is executed.

• The execution restarts from the saved data of the file Data_reference.g00.

• Output data are stored on the gdx file Demand_reference.gdx

02_EST_rund.gms

• The .gms file 02_EST_rund.gms uses the command $include and encompasses all the files relevant to the demand module execution.

• The first step of the model is to implement the calibration and solve all sectors together for the year 2015.

The set SAr is a subset of the set SA. With this loop command, it is filled with all the subsectors of the model. Then two .gms files are called:

EST_assign.gms:➢ Parameter assignment to the demand module.➢ Calibration of delta shares for the base year.➢ Initialization of the base year variables to the base year’s data.

EST_fixVar.gms:➢ Fixing variables where necessary

02_EST_rund.gms

• After the parameter assignment the model is solved for the base year only:

• The set year defines the solution years of the model. In this case, it is only with the yearbasis, which is equal to the year 2015.

solve_FX_EST_Demand.gms:➢ Solve statements

EST_rep.gms:➢ Reporting parameters

EST_update.gms:➢ Update for the next projection year

After the execution of the .gms, no sectors are included in the set SAr

02_solve_FX_EST_Demand.gms

• Solve statement for the yearbasis on the file solve_FX_EST_Demand.gms

• The result of final energy consumption per process is known for the year 2015.

• Variables are all initialized with the real data for the year 2015.

• If the model is calibrated appropriately, the results for 2015 should be replicated.

• As the variables are initialized, the model should come to a solution with no iterations.

• Solving with iterations signals calibration issues.

02_EST_rund.gms

• Apart from the base year, the sectors of the economy are solved separately. In terms of energy demand, no sectoral dependencies have been assumed.

• The energy demand by sector is solved year by year separately. The results feed the next year, but separate solve statements are called.

• For every sector and projection year the five .gms files are called in sequence

02_EST_rund.gms

EST_dyncalib.gms:➢ Initialization of variables. A staring point is given aiding the algorithm to find the

solution

EST_fixvar.gms:➢ Fixing variables where necessary

EST_solve_EST_demand.gms:➢ Solve statements

EST_rep.gms:➢ Reporting parameters

EST_update.gms:➢ Update for the next projection year

Calibration – Demand Module

Introduction

Given the available data for the base year(2015)…✓ Sectoral activity ✓ Fuel prices✓ Costs for sectoral processes✓ Specific energy consumption for sectoral processes

…the reproduction of the energy balances

• The model couples the sectoral activity(Ktons, pkm, GWh) with the final energy consumption, given in the balances.

• The calibration of demand module relies on the fitting of logit functions to the data of the energy balances by sector and fuel.

• Delta parameters, depicting the preferences of firms or individuals are adjusted in order to reach the balances data.

• Typical values have been given on price sensitivity parameters. Minor adjustments have been made where necessary.

The calibration of energy demand module requires detailed data of two categories:

1. Sectoral activity, representing the useful services that are obtained from energy.

➢ Production index for industry

➢ Passenger or tonne kM for vehicles

➢ Useful energy for households and services

2. Final energy consumption, representing the energy mix for covering sectoral activity.

Both data categories must be disaggregated on the resolution level of the EST. As the model is calibrated on the base year, data for 2015 are only required.

Introduction

Calibrating industry

• Data for industrial production is the starting point for calibrating industry. The model responds to the problem of the energy mix required for servicing industrial production:

21,800 Ktons Electric Arc Iron and steel plants

Industrial Production Process

Energy mix in electric arcplants

GDO; 8

NGS; 667

HCOAL; 614

ELEC; 1530

STEAM; 330,57

FINAL ENERGY CONSUMPTION IN KTOE

Calibrating industry

• In EST, activity must be given on the SB level of aggregation:

Level SB Code units

Iron and Steel Integrated FERRO_INT Ktons

Iron and Steel Electric Arc FERRO_EAR Ktons

Non Ferrous Metals Primary processing NONFER_PRIM Ktons

Non Ferrous Metals Secondary processing NONFER_SEC Ktons

Chemicals Fertilizers and Petrochemicals CHEM_ORG USD '15 value added

Chemicals Basic Chemistry Pharmaceuticals and Cosmetics CHEM_OTH USD '15 value added

Building Materials Cement and Others NMETM_CEM Ktons

Building Material Glass and Ceramics NMETM_GLCER Ktons

Paper Pulp and Printing PAPP Ktons

Food Beverages and Tobacco FDDRTB USD '15 value added

Textile and Leather TEXTL USD '15 value added

Equipment Goods Industries ENGNR USD '15 value added

Other Industries OTHR USD '15 value added

Non energy uses in industry NONEN USD '15 value added

Refineries REFIN GWh Crude refined

SB sectoral level EST

Calibrating industry

• Correspondence of sectors with NACE classification:

Iron and Steel -All technologies

C241, C242, C243, C2451, C2452 Manufacture of basic metals – iron and steel

Non Ferrous – primary & secondary C244, C2453, C2454 Manufacture of basic metals – non ferrous

FertilizersPetrochemicals

C2011, C2012, C2013, C2015C2014, C2016, C2017

Manufacture of industrial gases, dyes and pigments, other inorganic basic chemicals, fertilisers and nitrogen compoundsManufacture of other organic basic chemicals, plastics in primary forms, synthetic rubber in primary forms

Other chemicalsPharmaceuticals

C202, C203, C204, C205, C206C21

Manufacture of pesticides, other agro-chemical products, paints, varnishes and similar coatings, printing ink and mastics, soap and detergents, cleaning and polishing preparations, perfumes and toilet preparations, other chemical products, man-made fibresManufacture of basic pharmaceutical products and pharmaceutical preparations

Building Materials Cement and Others C235, C236, C237, C239 Manufacture of cement, lime, plaster and articles of concrete, plaster and cement

Building Materials Glass and ceramicsC234, C232, C233C231

Manufacture of other porcelain and ceramic products, refractory products, clay building materialsManufacture of glass and glass products

Paper and pulpPublishing and printing

C17,C18

Manufacture of pulp and paper and productsPrinting and reproduction of recorded material

Food industry C10, C11, C12 Manufacture of food products, beverages and tobacco

Textiles C13, C14, C15 Manufacture of textiles, wearing apparel and leather and related products

Engineering C25, C26, C27, C28, C29, C30 Manufacture of fabricated metal products, machinery and equipment n.e.c., electrical and optical equipment, transport equipment

Other industries B07, B08, B09, C22, C16, C31, C32, C33Mining and quarrying except for energy producing materials, manufacture of rubber and plastic products, manufacture of wood and wood products, manufacture of furniture, repair and installation of machinery and equipment, manufacturing n.e.c.

Correspondence with NACE classification

Calibrating industry: activity

A proxy for industrial activity is needed for each industrial sector:• Ktons of production can be used on industries that produce commodities, with low differentiation.

Examples:➢ Iron and Steel➢ Non ferrous metals➢ Cement

• Gross value added(GVA) can be used on products on highly differentiated products. GVA provides a tool for accounting industrial activity in different product categories. Examples:➢ Food, drink and tobacco➢ Engineering ➢ Textiles

Data sources

The sources used for each industrial sector:

Level SB Code units Source

Iron and Steel Integrated FERRO_INT Ktons MENR

Iron and Steel Electric Arc FERRO_EAR Ktons MENR

Non Ferrous Metals Primary processing NONFER_PRIM Ktons USGS

Non Ferrous Metals Secondary processing NONFER_SEC Ktons USGS

Chemicals Fertilizers and Petrochemicals CHEM_ORG USD '15 value added OECD - Eurostat

Chemicals Basic Chemistry Pharmaceuticals and Cosmetics

CHEM_OTH USD '15 value added OECD - Eurostat

Building Materials Cement and Others NMETM_CEM Ktons MENR - UNFCC

Building Material Glass and Ceramics NMETM_GLCER Ktons MENR - UNFCC

Paper Pulp and Printing PAPP Ktons FAOSTAT

Food Beverages and Tobacco FDDRTB USD '15 value added OECD

Textile and Leather TEXTL USD '15 value added OECD

Equipment Goods Industries ENGNR USD '15 value added OECD

Other Industries OTHR USD '15 value added OECD

Non energy uses in industry NONEN USD '15 value added OECD

Refineries REFIN GWh Crude refined MENR energy balance

Data issues

• Commodities of different types exist in certain industrial sectors.

• Examples: Paper and Pulp, Glass and Ceramics.

• Specific energy consumption is not the same for all industrial products.

• Thus, it is not possible to add ktons of production without unit conversion.

• The production of a pulp 1kton requires significant more energy comparing to the production of a paper kton.

How to add ktons of different commodities?Conversion to energy equivalent ktons must be implemented. An example for the sector of paper and pulp:

Commodity Production(ktons) Energy intensity(toe/t)

PULP 118 0.52

PAPER 2,920 0.21

Paper & Pulp in paper equivalent Ktons

=2.920+118*0.52/0.21=3,215

Paper and pulp Ktons calculation

Data issues

Gross value added:

Gross value added by sector was obtained from the detailed activity data of OECD.

https://stats.oecd.org/Index.aspx?DataSetCode=STANi4#

• In cases where the coverage of OECD data did not correspond to the resolution of EST, additional sources had to be used.

➢ Example: chemicals sector. Eurostat value added data were used for distributing value added to the EST sub-categories

Non-energy uses in the industry:

• It refers to the use of energy commodities in the industry as raw materials, not as fuels.

• The gross value added of:

• Petrochemicals & fertilizers

• Construction

is used as a proxy of the industrial activity of non-energy uses.

Activity calculation

Level SB Sector units 2015

Iron and Steel Integrated Industry Ktons 8,200

Iron and Steel Electric Arc Industry Ktons 23,800

Non Ferrous Metals Primary processing Industry Ktons 499.78

Non Ferrous Metals Secondary processing Industry Ktons 123.00

Chemicals Fertilizers and Petrochemicals Industry USD '15 value added 5,356.6

Chemicals Basic Chemistry Pharmaceuticals and Cosmetics

Industry USD '15 value added 3,599.27

Building Materials Cement and Others Industry Ktons 75,637

Building Material Glass and Ceramics Industry Ktons 6,879

Paper Pulp and Printing Industry Ktons 3,215

Food Beverages and Tobacco Industry USD '15 value added 16,049

Textile and Leather Industry USD '15 value added 17,587

Equipment Goods Industries Industry USD '15 value added 21,768

Other Industries Industry USD '15 value added 53,631

Non energy uses in industry Industry USD '15 value added 41,586

Refineries Industry GWh Crude refined 241,054

• The activity below is given as input on EST model.

• This activity is satisfied by the mix of energy commodities consumed in the balances.

Calibrating industry: energy

• The second pillar of the calibration process is the coupling of the activity with the final energy consumption.• A distinct feature of EST model is the detailed representation of industrial processes. An example for the paper

and pulp sector:

Paper and Pulp

Horizontal energy uses

Specific electricity uses

Heat uses

ProcessingThermal

processing

Product finishingSD

SC

SB

SA

SE SF

• Final energy consumption must be distributed on the level SF.

Energy balance

• The starting point of the energy demand distribution is the energy balance for the year 2015:

✓ The module of energy demand is devoted on the final energy consumption part of the energy balance table.

✓ The model must replicate the energy consumption in fuel and sectoral level.

✓ The coupling of demand, supply and biomass modules should reproduce all the data of energy balances.

• Final energy consumption per fuel for the sector of paper and pulp is given by the table:

Energy balance

The first step is to adjust the aggregate the figures on the level needed by the EST model:

Industry

Iron and steel

Non Ferrous metals

Chemicals

Non metallic minerals

Paper and Pulp

Textiles

Equipment good industriesFood Beverages and Tobacco

Non energy uses

Refineries

Other Industries

Level SA

Energy balance

Classification modification needed:

Equipment good industries:➢ Manufacture of fabricated metals➢ Machine, electrical and electronic

products➢ Production of transportation

equipment

Other industries:➢ Mining and quarrying➢ Construction➢ Wood and products➢ Furniture and other manufacturing➢ Other industry

Energy balance

The next step is to include steam produced from industrial boilers in the energy balances. The balance should also be cleared form industrial boilers, in order to avoid double counting.Example for the sector of iron and steel:

I&ST sector

Steam consumption Ktoe 626

Distributed from utility(-) Ktoe 60.1

CHP(-) Ktoe 178.5

Boilers(=) Ktoe 387.6Steam generation in the sector of iron and steel

I&ST sectorNatural

GasDerived

Gases

Gross Fuel consumption Ktoe 1145.39 504

Boilers fuel consumption(-) Ktoe 253.0 226.2

Final energy consumption (=) Ktoe 892 278

Cleared balance for fuels used in boilers

Energy balance

Balance of the iron and steel sector:

I&ST sector

GDO Ktoe 7.69

NGS Ktoe 1145

DGS Ktoe 504

HCL Ktoe 754

CKE Ktoe 1,639.2

ELEC Ktoe 1,779.4

STEAM Ktoe 238. 6

I&ST sector

GDO Ktoe 7.69

NGS Ktoe 892

DGS Ktoe 278

HCL Ktoe 754

CKE Ktoe 1,639.2

ELEC Ktoe 1779.4

STEAM Ktoe 626.15Final energy consumption for iron and steel,

fuels boilers includedFinal energy consumption for iron and steel,

fuels for boilers cleared

Energy balance

The net coke consumption and Derived gases consumption is considered. The energy amount of coke which is transferred to derived gases is subtracted.

Example for the sector of paper and pulp:

I&ST

Steam consumption Ktoe 375

Distributed from utility(-) Ktoe 204.3

CHP(-) Ktoe 51.5

Boilers(=) Ktoe 170.7Steam generation in the sector of paper and pulp

I&ST sectorHard Coal Lignite

Natural Gas

Diesel Oil

Gross Fuel consumption Ktoe 29.0 85.9 183.36 10.4

Boilers fuel consumption(-) Ktoe 19.3 57.2 130.1 10.4

Final energy consumption (=) Ktoe 9.7 28.7 53.2 0.0

Cleared balance for fuels used in boilers

Energy balance

Balance of the paper and pulp sector:

Paper and Pulp

GDO Ktoe 10.4

NGS Ktoe 183.4

LPG Ktoe 0.7

HCL Ktoe 29.0

LGN Ktoe 85.9

ELEC Ktoe 281.1

STEAM Ktoe 204.3Final energy consumption for paper and pulp,

fuels boilers includedFinal energy consumption for paper and pulp,

fuels for boilers cleared

Energy balance

Paper and Pulp

GDO Ktoe 0.0

NGS Ktoe 53

LPG Ktoe 0.7

HCL Ktoe 9.7

LGN Ktoe 28.7

ELEC Ktoe 281.1

STEAM Ktoe 375.4

Given the steam requirements, the next step is to distribute the energy on the level SB. In some cases, the resolution of the balances support the level SB of aggregation.

Example: non metallic minerals

Non metallic minerals

Cement and Others

Glass and Ceramics

In cases, where the resolution required by the SB level of the EST is higher, energy demand had to be disaggregated into SB levels:

Basic metal industry(24,25)

Manufacture of iron and steel products(24)

Manufacture of non-metallic mineral products-23

Manufacture of glass products(23)

Manufacture of ceramic products(23)

Manufacture of cement products(23)

Iron and steel

Integrated steelworks

Electric Arc

Energy balance

Iron and steel

Integrated steelworks

Iron and steel

Electric Arc

I&ST sector

GDO Ktoe 7.69

NGS Ktoe 892

DGS Ktoe 278

HCL Ktoe 754

CKE Ktoe 1,639.2

ELEC Ktoe 1779.4

STEAM Ktoe 626.15

Total Ktoe 5976

Final energy consumption for iron and steel,fuels for boilers cleared

Energy balance

The breakdown of final energy consumption is empirical and relies on:➢ the total activity per sub-sector➢ the total energy intensity per sub-sector➢ the intensity in the consumption of electricity➢ the fuel combustion intensity➢ the steam intensity➢ specific characteristics of fuel consumption per sector

Energy balance

Integrated Steelworks

8,200 ktons

DGS Ktoe 278

NGS Ktoe 343

CKE Ktoe 1639

ELEC Ktoe 328

STEAM Ktoe 296

Total Ktoe 2,884

Electric Arc 23,200 ktons

GDO Ktoe 7.69

NGS Ktoe 549

HCL Ktoe 754

ELEC Ktoe 1451

STEAM Ktoe 331

Total Ktoe 3,092

Final energy consumption on Blast furnaceFinal energy consumption on Electric Arc

Notice that:• Coke and DGS are consumed only on blast furnace plants.• Electricity intensity is higher on electric plants.• Electric arc plants are more efficient comparing to blast furnace plants.

Energy balance

Distribution into processes

Electric Arc

Horizontal energy uses

Specific Electricity Use

Heat Uses

Raw material preparation

Raw material preparation

Thermal and electric uses

Thermal processing

Electric Arc

Product finishingProduct finishing

The final step of the calibration is to distribute the energy into specific industrial processes:

???

???

???

???

???

???

Fuels have to be distributed in each separateprocess category.

The distribution of fuels into specific processes is based:➢ On the respective distribution of EU countries➢ On the specific characteristics of industrial

processes. Example for Electric Arc:

3,092 ktoe

Electric Arc

Horizontal energy uses

Specific Electricity Use

Heat Uses

Raw material preparation

Raw material preparation

Thermal and electric uses

Thermal processing

Electric Arc

Product finishing Product finishing

Electricity

172.3

Electricity Natural Gas

0.5 9.15

Electricity Steam Hard Coal Natural Gas16.57 25.7 434.8 527.8

Electricity Steam Hard Coal Natural Gas

59.8 82.6 226.2 56.58

Electricity

1090

ktoe

ktoe

ktoe

ktoe

ktoe

ktoe

3,092 ktoe

Example for Electric Arc Industry

The process of electric arc is the most intensive energy process. Electricity is the only commodity consumed.

Electricity Steam Diesel Oil Natural Gas

111.5 222.7 7.69 48.8

Example for Cement Industry

Cement

Horizontal energy uses

Specific Electricity Use

Heat Uses

Raw material preparation

Raw material preparation

Kilns Kilns

Product finishing Product finishing

Electricity

190.33 ktoe

Electricity Diesel Fuel Oil Natural Gas Steam4.82 13.46 158.92 158.9 181.17 ktoe

Electricity Fuel Oil

301.92 37.53 ktoe

Electricity Hard Coal Fuel Oil Lignite6.72 2025.7 3026.1 406.3 ktoe

Electricity Fuel Oi Natural gas 183.29 56.05 85.08 ktoe

6,707 ktoe

Kilns is the by far the most energy intensive process in cement industry.

Distribution into processes

The distribution of the fuels into the processes define the specific energy consumption of each separate process:Electric Arc Steel :➢ Electric Arc process: 0.046 toe/ton=0.54 MWh/ton

Cement:➢ Kilns: 0.072 toe/ton=0.84 MWh/ton

• The transformation of fuels into energy demand is made with specific type of equipment. • Sufficient installed capacity is assumed for the coverage of activity demand.• The calibrated values toe/ton are used as the specific energy consumption of the equipment for

each process.

𝐼𝑛𝑠𝑡𝑎𝑙𝑙𝑒𝑑 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝑖𝑛 𝑆𝐹 𝑙𝑒𝑣𝑒𝑙 =𝐹𝑖𝑛𝑎𝑙 𝐸𝑛𝑒𝑟𝑔𝑦 𝐶𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛𝑆𝐹8760 ∙ 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦_𝑓𝑎𝑐𝑡𝑜𝑟𝑆𝐹

𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦_𝑓𝑎𝑐𝑡𝑜𝑟𝑆𝐹: utilization factor for equipment in industrial process SF

Installed capacity

Integrated Steelworks: Example for Basic Oxygen Furnace

𝐼𝑛𝑠𝑡𝑎𝑙𝑙𝑒𝑑 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝐵𝑎𝑠𝑖𝑐 𝑂𝑥𝑦𝑔𝑒𝑛 𝐹𝑢𝑟𝑛𝑎𝑐𝑒 =𝐹𝑖𝑛𝑎𝑙 𝐸𝑛𝑒𝑟𝑔𝑦 𝐶𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛𝐵𝑂𝐹8760 ∙ 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦_𝑓𝑎𝑐𝑡𝑜𝑟𝐵𝑂𝐹

𝐼𝑛𝑠𝑡𝑎𝑙𝑙𝑒𝑑 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝐵𝑎𝑠𝑖𝑐 𝑂𝑥𝑦𝑔𝑒𝑛 𝐹𝑢𝑟𝑛𝑎𝑐𝑒 =1,090𝐾𝑡𝑜𝑒∙11.63

8760ℎ∙0.8= 1.81 𝐺𝑊

Cement: Example for Kilns

𝐼𝑛𝑠𝑡𝑎𝑙𝑙𝑒𝑑 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝐾𝑖𝑙𝑛𝑠 =𝐹𝑖𝑛𝑎𝑙 𝐸𝑛𝑒𝑟𝑔𝑦 𝐶𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛𝐾𝑖𝑙𝑛𝑠8760 ∙ 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦_𝑓𝑎𝑐𝑡𝑜𝑟𝐾𝑖𝑙𝑛𝑠

𝐼𝑛𝑠𝑡𝑎𝑙𝑙𝑒𝑑 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝐵𝑎𝑠𝑖𝑐 𝐾𝑖𝑙𝑛𝑠 =5,465𝐾𝑡𝑜𝑒∙11.63

8760ℎ∙0.8= 9.06 𝐺𝑊

Define the starting point for projections→ Calibration of the model with base year data

➢ Chosen base year: 2015

➢ Data input needs for 2015 according to model disaggregation level:

▪ Fuel prices

▪ Final energy consumption

▪ Activity/Useful energy for level SB

▪ Stock of equipment

▪ Vintages

Introduction (1/2)

Introduction (2/2)

Activity Final energy

Unlike Power Supply Module, data on final energy consumption on demand sectors in 2015 are limited to the energy balance.

➢ No data on the final energy consumption of the different types of equipment per end-use in households.

1st objective

• Break-down the final energy consumption reported in the 2015 Energy Balance into the disaggregated sub-sectors, end-uses and fuels defined by the EST Demand Module

• The disaggregation of the energy consumption into individual energy intensive processes allows the model user to simulate scenarios with distinct and targeted policy measures.

• These data have been inserted in Exogdata common input file.

• Main sources of information

• MENR energy balance of year 2015 (available online)

• Official statistical and other national reports on households

• Bibliographic references (research papers, international reports)

• PRIMES assumptions – EU average

Final Energy – Overview (1/3)

Final Energy – Overview (2/3)

• Energy Balance provides the final energy consumption in the households sector only byfuel

• The larger part of final energy consumption is for space-heating along with water-heating and air cooling.• approximately 80% -85% according to World Bank data and Turkish published research papers.

• Lighting, white and black appliances as well as air-conditioning consume only electricity→ 1st step: distribution of electricity consumption

Final Energy – Overview (3/3)

• According to a survey conducted by Turkish Statistical Institute on 2013, the average household appliances in a residence are refrigerator, air conditioning (AC), washing machine, dishwasher, television (TV), iron, vacuum cleaner, computer, oven, microwave oven; which means electrical energy is used for various purposes in this sector.

• Electrical household appliances sales have been growing as income levels increased and lifestyles changed in Turkey. Increased sales are a key driver of residential electricity consumption.

• Allocation of electricity consumption in the different end- uses has been performed within the margins included in the table above – possible revision after the calibration of the other uses.

Final Energy – Electric Uses (1/2)

End-uses Shares in ELC

Space heating 2-3%

Water heating 4-12%

Cooking 6-12%

Air-conditioning 4-5%

Lighting 12-28%

White appliances 30-38%

Black appliances 10-22%

Type of fuel

Space heating

Water heating Cooking Air-Cond Lighting White App Black App TOTAL

ELC 123.58 453.14 494.34 164.78 823.90 1277.04 782.70 4119.49

GDO 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

NGS 5626.50 1452.00 1996.50 0.00 0.00 0.00 0.00 9075.00

LPG 0.00 110.65 165.97 0.00 0.00 0.00 0.00 276.62

HCL 1080.99 56.89 0.00 0.00 0.00 0.00 0.00 1137.89

LGN 841.42 44.29 0.00 0.00 0.00 0.00 0.00 885.70

BMS 1648.37 54.34 108.68 0.00 0.00 0.00 0.00 1811.40

SOL 0.00 528.00 0.00 0.00 0.00 0.00 0.00 528.00

GEO 812.99 0.00 0.00 0.00 0.00 0.00 0.00 812.99

KRS 0.00 0.00 60.61 0.00 0.00 0.00 0.00 60.61

RFO 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

CKE 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

WSD 707.91 23.34 46.68 0.00 0.00 0.00 0.00 777.92

HET 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

TOTAL 10841.77 2722.65 2872.78 164.78 823.90 1277.04 782.70 19485.62

Final Energy – Electric Uses (2/2)

in Ktoe

• The equipment for space heating, water heating and cooking are distinguished by fuel type.

• Boilers: LPG, Diesel, Natural gas

• Stoves

• SH: solids (lignite, hard coal), biomass, waste solids

• COO: LPG, biomass, waste solids

• RES: solar, geothermal, heat pumps

• Heating uses should sum up to 80-85% of the total energy consumption.

• Space heating accounts for approximately 50-60% of the final energy consumption.

• According to Enerdata statistics, water heating represents around 15% of households’ energy consumption in Europe. In 2016, approximately 12% of Turkish households did not yet have a hot water system. Assumption: almost 13-14% of total energy consumption accounts for water heating in Turkey.

• Cooking: remaining share of 14-15%

• Calibration of the thermal end uses has been performed simultaneously.

Final Energy – Thermal Uses (1/4)

Space heating Water heating Cooking

Boilers (LPG, Diesel, Natural gas)

Boilers (LPG, Diesel, Natural gas)

Stoves (LPG, biomass)

Stoves (lignite, hard coal, biomass)

Stoves (lignite, hard coal, biomass)

Electricity

RES (solar, geothermal, heat pumps)

RES (solar, geothermal, heat pumps)

Gas (Natural gas)

Electricity Electricity

District-heating District-heating

Space heating

• In the last few years, a switch from stove heating to natural gas heating has been observed. According to statistics calculated using Turkish Household Budget Survey datasets, the share of stove heating decreased from 66% to 51% from 2010 to 2016, while the share of natural gas heating increased from 23% to 36%.

• In Turkey, the most common heating system is still solid-fuel stove heating with a share of 51% in 2016.

• Biomass (BMS) one of the main heating source of rural dwellings. Agricultural residues such as shell of nuts, animal wastes (called Waste Solids-WSD in EST) are used as energy source.

• Note: In EST for Turkey, geothermal in households is assumed to be supplied only as district-heating (fuel HET).

Final Energy – Thermal Uses (2/4)

Water heating

• The most common water heating systems are natural gas, electricity and solar heaters.

• Solar is assumed to be consumed only in water heating.

• The type of water heating technology strongly depends on the type of space heating system used in the household.

• For the households that use solid-fuel stoves for space heating purposes, the main options for water heating systems are electricity, solar and LPG-based heating systems as well as a small portion of solids.

Final Energy – Thermal Uses (3/4)

Final Energy – Thermal Uses (4/4)Type of

fuelSpace

heatingWater

heating Cooking Air-Cond Lighting White App Black App TOTAL

ELC 123.58 453.14 494.34 164.78 823.90 1277.04 782.70 4119.49

GDO 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

NGS 5626.50 1452.00 1996.50 0.00 0.00 0.00 0.00 9075.00

LPG 0.00 110.65 165.97 0.00 0.00 0.00 0.00 276.62

HCL 1080.99 56.89 0.00 0.00 0.00 0.00 0.00 1137.89

LGN 841.42 44.29 0.00 0.00 0.00 0.00 0.00 885.70

BMS 1648.37 54.34 108.68 0.00 0.00 0.00 0.00 1811.40

SOL 0.00 528.00 0.00 0.00 0.00 0.00 0.00 528.00

GEO 812.99 0.00 0.00 0.00 0.00 0.00 0.00 812.99

KRS 0.00 0.00 60.61 0.00 0.00 0.00 0.00 60.61

RFO 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

CKE 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

WSD 707.91 23.34 46.68 0.00 0.00 0.00 0.00 777.92

HET 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

TOTAL 10841.77 2722.65 2872.78 164.78 823.90 1277.04 782.70 19485.62

Only in WH

Only in SHAlmost all solids allocated in SH

Only in WH & COO

Only in COO

Calibration of NGS in order to keep the original shares

in Ktoe

• Activity in households per process is measured as follows:

• Thermal uses (space- & water – heating, air conditioning, cooking) in useful energy

• Lighting in number of lighting units

• White and Black appliances in number of appliances (data by MENR)

• Number of households in 2015: 22.348 million HHs

• Population: 78.218 million inhabitants

• Average HH size: 3.5 inhabitants per HH

• Approximately 8 lighting units per HH (TUBITAK)

Activity – Lighting & Appliances

End uses Number of units in 2015 (‘000)

Lighting 174597.70

White appliances 66838.44

Black appliances 40172.43

For the estimation of useful energy in thermal uses,

𝑼𝒔𝒆𝒇𝒖𝒍 𝒆𝒏𝒆𝒓𝒈𝒚 =𝑭𝒊𝒏𝒂𝒍 𝒆𝒏𝒆𝒓𝒈𝒚

𝑺𝑬𝑪 𝒓𝒂𝒕𝒆

• Final energy per process was divided to the respective specific energy consumption (SEC) rates

• SEC rates are measured in GWh final energy / GWh useful energy and are equivalent to heat rates (1 ÷𝑒𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦)

• Average heat rates per type of process/equipment and end-use were taken into account used also inPRIMES

e.g. for space-heating

Activity – Thermal Uses (1/3)

Supply processes/Equipment Efficiency rates SEC rates

HOU_SHCB (Boilers) 0.770 1.299

HOU_SHCS (Stoves) 0.600 1.667

HOU_SHCR (RES) 0.520 1.923

HOU_SHCE (Electric) 0.950 1.053

HOU_SHCH (Heat) 0.650 1.538

Let’s see the example for boilers!

Type of fuel

Space heating

Water heating Cooking Air-Cond Lighting White App Black App TOTAL

ELC 1437 5270 5749 1916 9582 14852 9103 47910

GDO 0 0 0 0 0 0 0 0

NGS 65436 16887 23219 0 0 0 0 105542

LPG 0 1287 1930 0 0 0 0 3217

HCL 12572 662 0 0 0 0 0 13234

LGN 9786 515 0 0 0 0 0 10301

BMS 19171 632 1264 0 0 0 0 21067

SOL 0 6141 0 0 0 0 0 6141

GEO 9455 0 0 0 0 0 0 9455

KRS 0 0 705 0 0 0 0 705

RFO 0 0 0 0 0 0 0 0

CKE 0 0 0 0 0 0 0 0

WSD 8233 271 543 0 0 0 0 9047

HET 0 0 0 0 0 0 0 0

TOTAL 126090 31664 33410 1916 9582 14852 9103 226618

Activity – Thermal Uses (2/3)

in GWh

65436/1.299=50386

• Thermal uses is the sum of space and water heating, cooling and cooking.

• The following table shows the activity in SB level.

Activity – Thermal Uses (3/3)

End uses Activity Units

Thermal uses 127709.94 GWh useful energy

Lighting 174597.70 ‘000 units

White appliances 66838.44 ‘000 appliances

Black appliances 40172.43 ‘000 appliances

• Stock of equipment for all processes (level SF) in Households were estimated in capacity units (GW), based on the following formula:

𝑺𝒕𝒐𝒄𝒌 =𝑨𝒄𝒕𝒊𝒗𝒊𝒕𝒚 × 𝑺𝑬𝑪 𝒓𝒂𝒕𝒆

𝒖𝒕𝒊𝒍𝒊𝒛𝒂𝒕𝒊𝒐𝒏 𝒓𝒂𝒕𝒆 × 𝟖𝟕𝟔𝟎

• The Excel input file of Demand Module contains this formula, so if the activity changes this would automatically calculate the respective stock.

e.g. for boilers in space heating it is assumed that utilization rate is approximately 0.25 (they are utilized almost one quarter of the year – 4 months full time)

𝑺𝒕𝒐𝒄𝒌𝒃𝒐𝒊𝒍 =𝟓𝟎𝟑𝟖𝟔 𝑮𝑾𝒉 × 𝟏. 𝟐𝟗𝟗

𝟎. 𝟐𝟓 × 𝟖𝟕𝟔𝟎 𝒉= 𝟐𝟗. 𝟕𝟒 𝑮𝑾

Stock and vintages (1/2)

• The vintages of the equipment per process were calculated based on an indicative histogram according to their lifetime

• Located in file Sets_EST in case someone wishes to change it

• With the assumption that, given their lifetime, the older equipment (close to the end of lifetime) is limited.

e.g. assuming that the lifetime of boilers is 20 years, the distribution of the vintages is:

Stock and vintages (2/2)

Vintages Stock of boilers in GW

0 8.55

5 8.55

10 8.42

15 3.83

20 0.39

TOTAL 29.74

• “An Assessment of Residential Energy Efficiency in Turkey”, 2018 by Erdal Aydın, link:https://iicec.sabanciuniv.edu/sites/iicec.sabanciuniv.edu/files/IICEC%20E%26C%20Paper%20Turkey%20Residential%20Efficiency%20210518_0.pdf

• Assessment of energy performance certificate systems: a case study for residential buildings in Turkey, Yigit K., Acarkan B., 2015

• “Examination of Electrical Energy Usage in Terms of Thermodynamic Efficiency and Sustainability in the Residential andCommercial Sector”, by Zafer Utlu, INTERNATIONAL JOURNAL OF ELECTRONICS, MECHANICAL AND MECHATRONICSENGINEERING Vol.7 Num.2 - 2017 (1403-1410)

• “Economic and demographic determinants of household energy use in Turkey.”, by Özcan, K. M., Gülay, E., & Üçdoğruk, Ş.(2013). Energy Policy, 60, 550–557. http://siteresources.worldbank.org/TURKEYEXTN/Resources/361711-1294661147811/TurkeyEE-en.pdf

• http://www.euromedina.org/bibliotheque_fichiers/Energaia08_TulinKeskin.pdf

• Presentation by Osram,Energy Saving by Smart Lighting ‖ at Energy Efficiency (Enver) Forum,15-16 January 2009, Istanbul

• OeEB study on Energy Efficiency Finance, prepared for OeEB by Allplan GmbH in cooperation with Frankfurt School and LocalPartners, Vienna, November 2013. Link:https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=34&ved=2ahUKEwjpzsP1rqfhAhVKM-wKHWtxCxk4HhAWMAN6BAgAEAI&url=https%3A%2F%2Fwww.oe-eb.at%2Fdam%2Fjcr%3Ae9c73d64-c299-4452-b294-70491d7673f0%2FOeEB-Study-Energy-Efficiency-Finance-Turkey.pdf&usg=AOvVaw1UDIHz1x740rK63evH56e7

• http://journals.tubitak.gov.tr/elektrik/issues/elk-16-24-6/elk-24-6-22-1407-87.pdf

• “A Model Based Analysis on End-Use Energy Efficiency for Çanakkale, Turkey”, Bakirci S., Razavi S, Sulukan E., Uyar T., 2018,Conference: IRENEC 2018

References

Introduction (1/2)

• The tertiary sector has been calibrated in a similar way as Households.

• Data on Services and Agriculture sectors are limited to those of the Energy Balance.

• Bibliographic references on the structure and the individual processes of these sectors are scarce.

• Assumptions were based on:

• Bibliographic references

• EU average (PRIMES)

Introduction (2/2)

• The end-uses and equipment are almost the same as in Households

• With an exception: Water heating is assumed to include cooking also.

1st step: electricity distribution among the different end-uses

• Lighting accounts for 30% of power consumption for retail chains and 40% for offices (2009).

• Same assumption for space heating, water heating and cooking as in Households.

Final Energy – Services (1/2)

End-uses Shares in ELC

Space heating 4-5%

Water heating 20-30%

Air cooling 4-5%

Lighting 30-40%

Electric uses 25-30%

2nd step: fuel distribution among the different end-uses (only SH and WH)

Final Energy – Services (2/2)

Type of fuel

Space heating

Water heating

Air-Cond LightingElectric

usesTOTAL

ELC 206.17 1804.01 206.17 1546.30 1391.67 5154.32

GDO 0.00 0.00 0.00 0.00 0.00 0.00

NGS 2477.15 130.38 0.00 0.00 0.00 2607.53

LPG 322.73 322.73 0.00 0.00 0.00 645.46

HCL 3374.40 177.60 0.00 0.00 0.00 3552.00

LGN 327.04 17.21 0.00 0.00 0.00 344.25

BMS 0.00 0.00 0.00 0.00 0.00 0.00

SOL 0.00 0.00 0.00 0.00 0.00 0.00

GEO 497.00 0.00 0.00 0.00 0.00 497.00

CKE 31.20 0.00 0.00 0.00 0.00 31.20

HET 0.00 0.00 0.00 0.00 0.00 0.00

TOTAL 7235.69 2451.93 206.17 1546.30 1391.67 12831.76

in Ktoe

Geothermal inserted as heat in EST

No detailed data on agricultural energy uses.

Assumptions based on EU average - PRIMES

Final Energy – Agriculture

Type of fuel

HeatingPumping& Motors

LightingElectric

usesTOTAL

ELC 270.32 86.48 20.99 41.97 419.77

GDO 2688.59 133.85 0.00 0.00 2822.45

NGS 109.91 0.00 0.00 0.00 109.91

GEO 580.09 0.00 0.00 0.00 580.09

TOTAL 3648.91 220.34 20.99 41.97 3932.21

in Ktoe

• Activity in tertiary sectors per process is measured in GWh useful energy

• For the estimation of useful energy,

𝑼𝒔𝒆𝒇𝒖𝒍 𝒆𝒏𝒆𝒓𝒈𝒚 =𝑭𝒊𝒏𝒂𝒍 𝒆𝒏𝒆𝒓𝒈𝒚

𝑺𝑬𝑪 𝒓𝒂𝒕𝒆• Average heat rates per type of process/equipment and end-use were taken into

account used also in PRIMES

e.g. in space heating of Services - Stoves

Activity (1/2)

Type of fuel

Space heating

Water heating

Air-Cond LightingElectric

usesTOTAL

ELC 2398 20981 2398 17983 16185 59945

GDO 0 0 0 0 0 0

NGS 28809 1516 0 0 0 30326

LPG 3753 3753 0 0 0 7507

HCL 39244 2065 0 0 0 41310

LGN 3803 200 0 0 0 4004

BMS 0 0 0 0 0 0

SOL 0 0 0 0 0 0

GEO 5780 0 0 0 0 5780

CKE 363 0 0 0 0 363

HET 0 0 0 0 0 0

TOTAL 84151 28516 2398 17983 16185 149233

Activity (2/2)

in GWh

=43410 / 1.667==26041 GWh useful

The same formula for stock and same histogram for vintages as in Households have been implemented.

• Stock of equipment for all processes (level SF) in Tertiary sectors were estimated in capacity units (GW), based on the following formula:

𝑺𝒕𝒐𝒄𝒌 =𝑨𝒄𝒕𝒊𝒗𝒊𝒕𝒚 × 𝑺𝑬𝑪 𝒓𝒂𝒕𝒆

𝒖𝒕𝒊𝒍𝒊𝒛𝒂𝒕𝒊𝒐𝒏 𝒓𝒂𝒕𝒆 × 𝟖𝟕𝟔𝟎

• The Excel input file of Demand Module contains this formula, so if the activity changes this would automatically calculate the respective stock.

e.g. for stoves in space heating of Services it is assumed that utilization rate is approximately 0.14

𝑺𝒕𝒐𝒄𝒌𝒔𝒕𝒐𝒗 =𝟐𝟔𝟎𝟒𝟏 𝑮𝑾𝒉 × 𝟏. 𝟔𝟔𝟕

𝟎. 𝟏𝟒 × 𝟖𝟕𝟔𝟎 𝒉≅ 𝟏. 𝟎𝟏𝟓 𝑮𝑾

Stock and vintages

Transport

Passenger

Inland Navigation

Private

Cars

2-wheelers

Public

Buses & Coaches

Tram|Metro

RailSlow rail

Fast rail

Freight

Inland Navigation

Rail

Trucks

Heavy-duty

Light-duty

Aviation

Introduction (1/2)

• Calibration of transport sectors has been performed using:

• Data provided by MENR on activity, stock and vintages -

• Bibliographic references

• EU average (PRIMES)

Introduction (2/2)

• Activity in transport per process is measured as follows:

• Passenger transport and aviation in million passenger-kms (Mpkm)

➢ A passenger-kilometer is the unit of measurement representing the transport of 1 passenger by a definedmode of transport (road, rail, air, sea, inland waterways etc.) over 1 kilometer.

• Freight transport in million tonne-kms (Mtkm)

➢ A tonne-kilometer is a unit of measure of freight transport which represents the transport of 1 tonne ofgoods by a given transport mode (road, rail, air, sea, inland waterways, pipeline etc.) over a distance of 1kilometer.

• Data provided by MENR

• Using assumptions for further break-down where necessary based on proxy statistics andbibliographic references.

Activity and Stock (1/3)

For the estimation of activity in transport, the following formula is used

𝑨𝒄𝒕𝒊𝒗𝒊𝒕𝒚 = 𝑺𝒕𝒐𝒄𝒌 ×𝑴𝒊𝒍𝒆𝒂𝒈𝒆 × 𝑶𝒄𝒄𝒖𝒑𝒂𝒏𝒄𝒚 𝒓𝒂𝒕𝒊𝒐

• Activity in pkm or tkm, depending on the transport category (passenger or freight)

• Stock in vehicles

• Mileage is the distance travelled by a vehicle (in km)

• Occupancy ratio is the average number of passengers per vehicle

• Empirical data used on mileage based on EU average

• Occupancy ratios calculated based on activity, stock and mileage.

• Data on activity and stock provided by MENR

• Where the calculation of occupancy ratios has been irrational, stock has been “adjusted” to complywith the formula used in EST.

Activity and Stock (2/3)

Example on Land/Water Passenger-Private-Private Cars:

Note: Although in TUIK, plug-in hybrid & electric cars were registered, no electricity consumption was reportedin energy balances for road transport.

Transport Mode Activity in Mpkm Stock in ‘000 vehicles Mileage in ‘000 km Occupancy ratio

PSCAR_DSL 91884 3358 15.43 1.77

PSCAR_GSL 39300 2938 7.72 1.73

PSCAR_GAS 68700 4287 12.02 1.33

PSCAR_PHEVDSL 0 0 15.43 1.54

PSCAR_PHEVGSL 0 0 7.72 1.54

PSCAR_ELE 0 0 7.72 1.54

PSCAR_H2 0 0 7.72 1.542015 data

=91884/(3358x15.43)

Actual data Actual data Assumption

Activity and Stock (3/3)

• In energy balances, fuel consumption in transport is broken down in road, rail, air and water transport modes.

• The main challenge was to distribute fuel consumption per transport mode in passenger and freight category.

• The distribution of activity and stock is taken into account.

• Main sources of information

• MENR energy balance of year 2015 (available online)

• Official statistical and other national and international reports on transport

• PRIMES assumptions – EU average

For the estimation of specific energy consumption (SEC) rates per transport mode and process

𝑺𝑬𝑪 𝒓𝒂𝒕𝒆 =𝑭𝒊𝒏𝒂𝒍 𝑬𝒏𝒆𝒓𝒈𝒚 × 𝑶𝒄𝒄𝒖𝒑𝒂𝒏𝒄𝒚 𝒓𝒂𝒕𝒊𝒐

𝑨𝒄𝒕𝒊𝒗𝒊𝒕𝒚

SEC rate in KWh/vehicle-km

Final Energy – Overview

Basic assumptions

• Gasoline is consumed mainly in private cars and a small portion in light duty vehicles and 2-wheelers.

• LPG is consumed only in private cars, public road transport (buses, coaches) and freight light-duty vehicles.

• A large portion of cars are converted to run on LPG. About 22% of all vehicles currently on the road run on LPG, and for private cars the share reported is even as high as 46% (WLPGA, 2015). According to TUIK, the largest share of private cars run on LPG and diesel (almost 73%). No electricity in road transport is reported.

• Public transport: penetration of CNG buses

Final Energy – Road passenger

GDO BFC NGS BGS LPG ELC GSLPSCAR_DSL 2065.73 41.75 0.00 0.00 0.00 0.00 0.00PSCAR_GSL 0.00 41.75 0.00 0.00 0.00 0.00 1759.24PSCAR_GAS 0.00 0.00 70.82 0.00 2982.69 0.00 0.00PSCAR_PHEVDSL 0.00 0.00 0.00 0.00 0.00 0.00 0.00PSCAR_PHEVGSL 0.00 0.00 0.00 0.00 0.00 0.00 0.00PSCAR_ELE 0.00 0.00 0.00 0.00 0.00 0.00 0.00PSCAR_H2 0.00 0.00 0.00 0.00 0.00 0.00 0.00PS2WL_GSL 0.00 0.00 0.00 0.00 0.00 0.00 72.87PS2WL_ELE 0.00 0.00 0.00 0.00 0.00 0.00 0.00PSPRD_DSL 2720.69 6.37 0.00 0.00 0.00 0.00 0.00PSPRD_GAS 0.00 0.00 0.04 0.00 242.78 0.00 0.00PSPRD_ELE 0.00 0.00 0.00 0.00 0.00 0.00 0.00PSPRD_H2 0.00 0.00 0.00 0.00 0.00 0.00 0.00PSRLM_ELE 0.00 0.00 0.00 0.00 0.00 13.83 0.00

in Ktoe

Basic assumptions

• New light commercial vehicles in Turkey run entirely on diesel fuel. Assuming that diesel percentage is higher compared to gasoline (55% diesel and 45% gasoline).

• Heavy-duty vehicles run only on diesel.

Final Energy – Road freight

GDO BFC NGS BGS LPG ELC GSLFRHDT_DSL 11816.16 30.41 0.00 0.00 0.00 0.00 0.00FRHDT_GAS 0.00 0.00 0.00 0.00 0.00 0.00 0.00FRHDT_ELE 0.00 0.00 0.00 0.00 0.00 0.00 0.00FRHDT_H2 0.00 0.00 0.00 0.00 0.00 0.00 0.00FRLDT_DSL 400.01 0.47 0.00 0.00 0.00 0.00 0.00FRLDT_GSL 0.00 0.47 0.00 0.00 0.00 0.00 337.85FRLDT_GAS 0.00 0.00 0.00 0.00 242.78 0.00 0.00FRLDT_PHEVDSL 0.00 0.00 0.00 0.00 0.00 0.00 0.00FRLDT_PHEVGSL 0.00 0.00 0.00 0.00 0.00 0.00 0.00FRLDT_ELE 0.00 0.00 0.00 0.00 0.00 0.00 0.00FRLDT_H2 0.00 0.00 0.00 0.00 0.00 0.00 0.00

in Ktoe

Basic assumptions

• 23% of Turkey’s conventional rail network is electrified (2017). The share of electric locomotives pulling cargo trains has expanded over the decade. In 2010, just 5% of Turkish freight trains were powered by electric units, while in 2015 electric cargo locomotive’s share had jumped to 21%.

Final Energy – Rail

GDO BFC NGS BGS LPG ELCPSRLL_DSL 27.93 0.00 0.00 0.00 0.00 0.00PSRLL_ELE 0.00 0.00 0.00 0.00 0.00 5.28PSRLL_H2 0.00 0.00 0.00 0.00 0.00 0.00PSRLF_ELE 0.00 0.00 0.00 0.00 0.00 22.80FRRLS_DSL 111.74 0.00 0.00 0.00 0.00 0.00FRRLS_ELE 0.00 0.00 0.00 0.00 0.00 27.15FRRLS_H2 0.00 0.00 0.00 0.00 0.00 0.00

in Ktoe

• Jet kerosene is the only fuel consumed for aviation, while fuel oil is the only fuel consumed in water transport.

Final Energy – Air & Water

KRS RFO ELC H2PSAIR_KERO 5108.44 0.00 0.00 0.00PSAIR_HYB 0.00 0.00 0.00 0.00PSAIR_ELE 0.00 0.00 0.00 0.00PSWTR_OIL 0.00 13.24 0.00 0.00PSWTR_GAS 0.00 0.00 0.00 0.00PSWTR_ELE 0.00 0.00 0.00 0.00PSWTR_H2 0.00 0.00 0.00 0.00FRWTR_OIL 0.00 175.86 0.00 0.00FRWTR_GAS 0.00 0.00 0.00 0.00FRWTR_ELE 0.00 0.00 0.00 0.00FRWTR_H2 0.00 0.00 0.00 0.00

• “THE AUTOMOTIVE SECTOR IN TURKEY-A BASELINE ANALYSIS OF VEHICLE FLEET STRUCTURE, FUEL CONSUMPTIONAND EMISSIONS”, ICCT (International Council on Clean Transportation), 2016. Link:https://www.theicct.org/sites/default/files/publications/ICCT_Turkish-fleet-baseline_20160318.pdf

• TÜİK – Turkish Statistical Institute. Link: http://www.tuik.gov.tr

• http://www.transport-exhibitions.com/Market-Insights/Turkey-and-Eurasia/Electrification-of-Turkish-railways

• “Autogas Incentive Policies - A Country-by-Country Analysis of Why and How Governments Encourage Autogas and What Works”, WLPGA (World LPG Association), 2015. Link: https://www.wlpga.org/wp-content/uploads/2015/09/autogas-incentive-policies-2015-2.pdf

• TRACCS database. Link: https://traccs.emisia.com/

References

Assignments - Fixing Calibration Errors

• Open the EST model from your C:\ drive.

• Run only the Demand Module for the Reference scenario and for 2015.

1. Go to 00_EST_main.gms file

2. In the command line, make the necessary options:

1. type the scenario name and the horizon

2. give the value 1 to the necessary control variables, else 0

3. keep the value 1 for the iterations

Run Reference scenario of Demand Module for 2015

• Useful parameter to check if all sectors SA are solved for a specificscenario without looking at the .lst file

• Parameter status_EST_Demand appearing in .gdx file

• in 02c_solve_FX_EST_Demand.gms (for base year) and 02f_solve_EST_Demand.gmsfiles, this parameter is defined using the attribute .modelstat

• This attribute stores the integer number that indicates the model status (optimal, infeasible,etc.) – values 1-19)

Check solving status of Demand Module (1/2)

Name of the modelAttribute of the model

• Open the output .gdx file Demand_Reference.gdx, located in the Outputgdx folder ofthe Reference scenario and check the parameter status_EST_Demand in the .gdx file

Check solving status of Demand Module (2/2)

Values of model status after solving 2015

Sectors of SA level

Status parameter

Number of iterations:Meaning zero

iterations to solve the model

Assignment No 1

• Run only the Demand Module for the ReferenceCalib1 scenario and for 2015.

1. Go to 00_EST_main.gms file

2. In the command line, make the necessary options:

1. type the scenario name and the horizon

2. give the value 1 to the necessary control variables, else 0

3. keep the value 1 for the iterations

Step 1: Run the Module for 2015 using Assignment1 input file

• Go to the Outputgdx folder of the ReferenceCalib1 scenario

• Open Demand_ReferenceCalib1.gdx file

• Check the values of the parameter status_EST_Demand

Note: The model should be solved with zero iterations for the base year, else the model is not calibrated!!!

Step 2: Check solving status of Demand Module

Value 6 for intermediate infeasible: solution not feasible, solver stopped, solver status will give more info.

Model solved with 1 iteration

• Go to LST folder of the ReferenceCalib1 scenario

• Open Demand_ReferenceCalib1.lst file and check it

• Check for the signs **** (error or warning) and INFES (infeasible) using the entry field of Search

Step 3: Check the Listing file for errors

Equation with the error

Process with the error

Level of equation zero and marginal non- zero, or the other way round. Else this is infeasible.

Equation with the error

Process with the error

• The error concerns PSCAR_GSL (Private Cars – Gasoline).

• Since final energy and activity are given, errors (linked with stock and final energy) show that something is wrong with the calculation of SEC rates.

• Check the calculation of SEC rate for PSCAR_GSL

𝑺𝑬𝑪 𝒓𝒂𝒕𝒆 =𝑭𝒊𝒏𝒂𝒍 𝑬𝒏𝒆𝒓𝒈𝒚 × 𝑶𝒄𝒄𝒖𝒑𝒂𝒏𝒄𝒚 𝒓𝒂𝒕𝒊𝒐

𝑨𝒄𝒕𝒊𝒗𝒊𝒕𝒚

Final energy is located in Exogdata file, while activity (Macro_data sheet), SEC rates and Occupancy ratios (techdata_sf sheet) are found in Input Demand file.

Step 4: Fix the error (1/4)

Final energy is located in Exogdata file.

Step 4: Fix the error (2/4)

Activity (Macro_data sheet), SEC rates and Occupancy ratios (techdata_sf sheet) are found in Input Demand file.

Step 4: Fix the error (3/4)

𝟐𝟗𝟑𝟖. 𝟐𝟎 =𝟑𝟗𝟑𝟎𝟎

𝟕𝟕𝟐𝟏×𝟏.𝟕𝟕= 𝟐𝟖𝟕𝟓. 𝟕𝟏 INFES

Either you change the occupancy ratio or the SEC rate.

Let’s change the occupancy ratio!

The right occupancy ratio should be:

O𝒄𝒄𝒖𝒑𝒂𝒏𝒄𝒚 𝒓𝒂𝒕𝒊𝒐 =𝟑𝟗𝟑𝟎𝟎 × 𝟎. 𝟗𝟐𝟑

𝟐𝟎𝟗𝟒𝟓. 𝟒𝟗≅ 𝟏. 𝟕𝟑𝟏𝟖𝟐𝟑𝟖𝟗

Most of these parameters are automatically calculated inside the Excel inputdemand file, therefore it is difficult to make such kind of calibration errors.

Step 4: Fix the error (4/4)

• Correct the occupancy ratio, save the input file with the change and re-run thescenario.

Step 5: Re-run the model

Assignment No 2

Steps

1. Run the Demand Module for ReferenceCalib2 scenario only for 2015

2. Check the status of Demand Module. Was it solved for this scenario and year?

3. If no, detect the error by checking the Listing file (INFES).

4. In which sector and in which equations the error appears?

5. Fix the error by checking the SEC rate.

Fix the calibration error(s) (1/2)

Steps

6. Where are the data on final energy located? In which file?

Exogdata file – sheet Exogdata

7. Where are the data on activity for each process located? In which file?

ReferenceCalib2_Input_Demand file – sheet Macro_data

8. Where is the SEC rate located?

ReferenceCalib2_Input_Demand file – sheet techdata_sf

9. Do the calculation of SEC rate? Is this calculation right?

10. If not, recalculate SEC rate, fill in with the right value & re-run the scenario for 2015.

11. Has the model been solved this time?

Fix the calibration error(s) (2/2)