IntERACT. WORKING PAPER NO January Abstract:

Transcription

1 IntERACT MODEL WORKING PAPER NO January 2014 Page 1 phase I Abstract: The TIMES-DK model implemented into the IntERACT model setup is documented in the following presentation. The documentation covers the phase 1 version of the model covering energy supply of electricity and district heat as well as use of energy from the household sector. The model does not include industry, services and agricultural use of energy nor any part of the transport sector. The development of the TIMES-DK phase 1 has been carried out by DTU Management Engineering in close cooperation with the Danish Energy Agency. Disclaimer: The views expressed in this Working Paper Series represent work in progress, and do not necessarily represent those of the Danish Energy Agency or policies of the Danish Ministry of Climate, Energy and Building. The papers do not themselves represent policy advice in any form. The papers are internal working papers published in good faith to inform a wide audience. While every effort is made to keep available working papers current, the Danish Energy Agency, its employees or agents make no warranty, expressed or implied, as to the accuracy of the information presented herein. The Working Paper Series include work undertaken by Danish Energy Agency staff as well as work undertaken by external researchers or consultants. Please do not cite without permission.

2 2

3 phase I DTU Management Engineering E4SMA IntERACT Team, Danish Energy Agency

4 Project consultancy team DTU Management Engineering Kenneth Karlsson Head of Energy System Analysis Helge Larsen Senior scientist Stefan Petrovic PhD candidate Olexandr Balyk research assistant E4SMA Maurizio Gargiulo president E4SMA Rocco De Miglio 2

5 TIMES-DK Vision Detailed bottom up model including all sectors in the Danish energy system Linked to a macro-economic CGE model of the Danish economy Finding least cost pathways to political RE or emission reduction targets Through the CGE model showing impact on Danish economy from energy policy and changed global framework A new tool for optimizing GHG reduction scenarios horizontal across all sectors Taking part in the international collaboration under IEA, ETSAP to develop and use the TIMES tool 3

6 TIMES-DK Phase I Phase I has been running from December 2012 to December 2013 DTU Management Engineering and e4sma has been consultancies on the development of TIMES-DK Focus has been on the power and district heating sector and the household sector Linking to the CGE-model has also been an important part 5 full week workshops and 2 half week workshops has been essential for developing the structure of the model The work has been presented at two international workshops; one in Lisbon and one in Paris 4

7 Deliverables from phase I 1. This presentation 2. Working and tested TIMES-DK model (databases, model files etc.) 3. Documentation of Power and District Heating Sector model 4. Documentation of Household Sector model 5. Short introduction paper to TIMES models and a tutorial 6. Excel result sheets for single scenarios and for comparison of scenarios 7. Interface to the RAMSES model (so RAMSES data can be used in TIMES-DK) 8. TimeSliceTool for aggregating hourly data to model time slices 9. Heat Atlas data for buildings (calculated heat loss, cost of heat savings, cost of expansion of district heating grid) 5

8 TIMES-DK Model (1/2) Before using the model the software VEDA and GAMS has to be installed on the computer Copy the model folder VEDA Models under VEDA (c:\veda\veda_models\times DK_HOU_v14) Copy the database folder Denmark to VEDA_BE\databases Result master files (can be found in \Results sheet masters\) should be placed at same level as the TIMES DK model folder 6

9 TIMES-DK Model (2/2) A TIMES model can optimize across all sectors Modules developed so fare are in green Resources Power & DH plants Refineries Fuels electricity district heat Households Industry Trade&service Agriculture Other Transport 7

10 Power and District Heating Model (1/3) Represent all existing non-industrial power and district heat producing plants in DK based on RAMSES database Include data for new power and district heat producing technologies from the Danish Technology Catalogue Two model regions: DK-W and DK-E Two heating areas in each region (central and de-central) Transmission lines to Norway, Sweden, Germany and Netherlands modelled as a price interface and capacity Model runs until 2050 with 32 time steps in a year 8

11 Power and District Heating Model (2/3) Simplified illustration of the models Reference Energy System (RES) The power and DH sector delivers electricity and DH to all the sectors in the model (household sector is also modelled, while the other sectors are represented by an exogenous demand 9

12 Power and District Heating Model (3/3) As existing plants gets old or uneconomic they can be replaced by new The endogenous response of the optimization is in size (GW), type of plant, utilization (operating hours) of the new capacities and in the calculation of the correspondent prices for electricity and heat. 10

13 Household Model(1/7) Two type of services are modelled in the Household model: Services from electric appliances and heat service 11

14 Appliances -model structure (2/7) The mix of appliances are modelled in two type of dwellings multi-storey and detached based dwellings 12 Seven different types of appliances are included and represent all electricity consumption in dwellings except from heating

15 Appliances in the model (3/7) Appliances in detached dwellings Stock in 1000 Electricity consump. Lifetime before replacement Appliances in multi-storey dwellings Stock in 1000 Electricity consump. Lifetime before replacement 13

16 Heat Services (4/7) Heat services are measured as Mm2 in the model The building are split in before and after 1972 and in multi-story (multi storey+non-detached) and detached (detached+farm houses) 14

17 Household heat (5/7) For each heating area (central, decentral and individual) building area and heat demand are retrieved from the heat atlas divided on DKW, DKE, the two building types and two construction periods. Buildings DKE Building age Energy Service Demand [Mm2] <72 >72 New Decentralised Detached Buildings Centralised Detached Buildings Indivdual Detached Buildings Decentralised Multi S. Buildings Centralised Multi S. Buildings Individual Multi S. Buildings Building age Energy Demand [PJ] <72 >72 New Decentralised Detached Buildings Centralised Detached Buildings Indivdual Detached Buildings Decentralised Multi S. Buildings Centralised Multi S. Buildings Individual Multi S. Buildings Building age Energy Unit Demand [PJ/Mm2] <72 >72 <2020 >2020 Decentralised Detached Buildings Centralised Detached Buildings Indivdual Detached Buildings Decentralised Multi S. Buildings Centralised Multi S. Buildings Individual Multi S. Buildings

18 Projection of heated area (6/7) Based on a projection of heated area within the building groups; the model keeps track on the change in heat demand due to replacement of old buildings with new and the increase in heated area. 16

19 Heat supply technologies (7/7) The heat demand from the building can be met by three different types of technologies: Indiv. boilers, district heating and energy savings. The latter will always be in combination with one of the other two 17

20 The TIMES tool (1/4) TIMES (The Integrated MARKAL-EFOM System) model generator was developed as part of the IEA-ETSAP (Energy Technology Systems Analysis Program), an international community which uses long term energy scenarios conduct in-depth energy and environmental analyses TIMES is a technology rich, bottom-up model generator, which uses linear-programming to produce a least-cost energy system, optimized according to a number of user constraints, over medium to long-term time horizons in-depth energy and environmental analyses Example of how energy systems are described in TIMES: Commodity coal, oil, wind etc. Process power plant, windturbine, etc. Commodity Electricity Commodity flow Electricity for household sector Process Electric appliances 18

21 The TIMES tool (2/4) VEDA Front End is the user interface for TIMES-DK from where input files are organised and updated When the files to include in a model run is checked, then the problem is send to GAMS for solving VEDA is checking all files for syntax and definition errors before executing GAMS VEDA FE 19

22 The TIMES tool (3/4) VEDA Back End collects all model output from several scenarios Scenarios can be compared and all processes and commodities can be inspected Standard tables are defined for the most interesting results Some of the tables are linking to the Excel Result sheets VEDA BE 20

23 The TIMES tool (4/4) A 12 step tutorial is delivered as a part of the documentation, which will be beneficial for new users of TIMES before running TIMES- DK E4SMA can provide training courses after agreement 21

24 Tools - Excel Result Sheets (1/2) Standard tables has been created in VEDA BE which are linked to Excel-sheets so result data easily are exported and presented in prepared tables and graphs TIMES-DK_Results_TIMES-DK.XLS TIMES_DK_Graphs_TIMES-DK.xlsb 22

25 Tools - Excel Result Sheets (2/2) Up to 3 scenarios can be compared in the Compare Scenarios Tool 23

26 Tools RAMSES Interface The RAMSES database holds data on almost all power and district heating producing plants in Denmark. In TIMES these around 1200 existing and new units are aggregated to around 60 plants using the RAMSES interface. The interface directly prepare input files for TIMES 24

27 Tools TimeSliceTool (1/2) This tool is developed to aggregate hourly data for wind production, PV production, power demand, heat demand etc. into the 32 time steps of TIMES DK 25

28 Tools TimeSliceTool (2/2) The time slices are defined to catch critical situations in the power system: A: Wind High, Power demand low B: Power demand High, Wind Low C: Peak PV D: Rest 26

29 Tools Heat Atlas (1/2) Danish heat atlas represents a collection of spatially referenced data about nearly 2.5 mill. buildings in Denmark From BBR information on type, construction year and heat supply is together with weather data from DMI used for heat loss calculation for each building SBI and DTU Civil Engineering reports are used to define standards of the existing buildings and heat saving potentials Energy Producer Count (Energiproducenttællingen) is used to link buildings with district heating grids This gives a dataset which can be aggregated to area specific building types used in the TIMES DK model with information on heat loss from the existing buildings, the cost of introducing heat savings in the different building and the cost of connecting them to the nearest district heating network 27

30 Tools Heat Atlas (2/2) Heating areas in the model Dark blue central Light blue next to central Dark green de-central Grey + rest - individual Marginal costs of heat savings Costs of expanding district heating 28

31 Tools Process diagram tool To illustrate the structure of TIMES-DK model a freeware yed is used to create flow diagrams the result of this can be seen in the flow diagrams following this slide 29

32 Flow diagram Power Sector Heat only plants 30

33 Flow diagram Power Sector Condensing power plants 31

34 Flow diagram Power Sector CHP plants de-central 32

35 Flow diagram Power Sector CHP plants central 33

36 Flow diagram Household Sector Appliances 34

37 Flow diagram Household Sector Heating of buildings 35

38 Scenarios For testing TIMES-DK throughout the development three scenarios has been run every time a new version on the model was ready. The Power sector model alone reached version 15 while starting up the combined power sector and household sector version of TIMES-DK. The combined version delivered here has also reached version 15. The three scenarios: 1. Base only a few constraints are added, such as limits of how fast wind can be implemented, heat savings can be introduced and all waste have to be used 2. WLP - as Base but including the target that 50% of the electricity production in Denmark has to be covered by wind power 3. WLP+NFE as WLP but including facing out fossil fuels for power and district heat production by

39 Scenario disclaimer No taxes are included in the presented model runs Fixed price profiles are used for import and export of electricity The house hold sector is the only demand sector modelled, which mean demand for power and district heat from industry, service, transport and others are kept constant throughout the scenario period Base is called A in the graphs WLP is called B and WLP+NFE is called C 37

40 Power production on fuel - compared In the first years there is export to Sweden. In 2020 the onshore wind potential is reached and offshore is growing. WLP+NFE has a huge import in 2045 until more offshore wind is put up in 2050 Biomass plays a small role as bridging fuel 38

41 Fuel consumption power & DH sector Coal is dominant until 2025, but geothermal kicks in already from 2015 and is faced out when new improved heat pumps based on ambient heat comes on the market in 2035 (only in WLP+NFE). From 2035 wind is the main fuel in the WLP+NFE only supplemented by waste and ambient heat from

42 Total cost in power & DH sector Total discounted investment costs (INCOST), fixed operational costs (FIXOM), variable costs (VAROM) and fuel costs. Over time when replacing old plants, the higher efficiency and less fuel based technologies switch the main cost from being fuel cost to investment costs. 40

43 Power production share on fuels in each time slice -1. quarter 2030 Shows average capacity activated in each time slice (MW). The time slice RNWB has a huge import from Norway and Sweden, while there is export to Sweden in RWDA 41

44 Power production share on fuels in each time slice -2. quarter 2030 Shows average capacity activated in each time slice (MW). There is not a large peak in the 2. quarter such as in 1. PV delivers more in 2.Q because of more full load hours and coal delivers less as heat demand is lower and the CHP benefit decreases 42

45 Zooming in on the scenarios Moving down into the result sheets created for each scenario, many more details are available especially on the household sector WLP+NFE is used as example in the following. The same graphs and more can be found in the result sheets (\model files\results\) 43

46 WLP+NFE power production on regions Electricity production divided on west and east DK shows a huge import to DKW from Norway from 2035 and from Sweden to DKE. The import is based on a fixed price profile and only limited by the transmission capacity. Therefore, will an ambitious Danish energy policy lead to more import as the Danish production price increase. 44

47 WLP+NFE District heat production District heat production divided on west and east DK. Waste is used for DH production throughout the period. Natural gas is almost faced out in 2015 where geothermal heat comes in strong to be replaced after 2035 by heat pumps based on ambient air. Biomass mainly play a role in DKE. 45

48 WLP+NFE District heat production District heat production divided on central and decentral heating areas. In general the demand for district heating goes down which is due to implementation of heat savings. The de-central areas switch to heat pumps already in 2015, while central area has a lot of big thermal CHP s waits until

49 WLP+NFE CO2 emissions The CO2 emissions are reduced dramatically until After that only CO2 emissions from burning of waste is remaining. 47

50 WLP+NFE - Heat supply to buildings Heat supply divided on boilers, exchangers (DH), and heat savings. In the central heating areas most buildings are connected to DH grid and the model connects the last buildings in In the central areas heat savings does not become profitable before 2025 where the large CHP s begins to shut down. 48

51 WLP+NFE - Heat supply to buildings Heat supply divided on boilers, exchangers (DH), and heat savings. In the de-central heating areas boilers covers one third in the base year. Heat savings are profitable already from

52 WLP+NFE - Heat supply to buildings Heat supply divided on boilers, exchangers (DH), and heat savings. In individual heating areas boilers covers 100% and heat savings are profitable already from

53 WLP+NFE - Heat supply to buildings Heat supply divided on boilers, exchangers (DH), and heat savings. Looking at heat supply to the group detached buildings shows an equal share between boilers and DH in the beginning. Heat savings become profitable from 2012 and are gradually replacing district heat. 51

54 WLP+NFE - Heat supply to buildings Heat supply divided on boilers, exchangers (DH), and heat savings. Heat supply to the group Multistorey buildings are mainly district heat in central areas as they mainly are located in larger cities. Heat savings becomes profitable from

55 WLP+NFE - Heat supply to buildings Heat supply divided on fuels in DKW and DKE. Heat demand drops as a result of implementation of heat savings. CPW=wood DSL=oil ELC=heat pumps HCE=central DH HDE=decentral DH NGA=natural gas SOL=solar heat STR=straw 53