TIMES-DK Developers 11/11/2013. TIMES DK phase 1 Structure and some first results. Kenneth Karlsson, Senior Scientist. Rikke Næraa, Technical Adviser

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1 TIMES DK phase 1 Structure and some first results Kenneth Karlsson, Senior Scientist Head of Energy Systems Analysis group, System Analysis Division, DTU Management Engineering Rikke Næraa, Technical Adviser Models and Analysis, Danish Energy Agency Maurizio Gargiulo President/owner e4sma Olexandr Balyk, PhD Fellow/Research assistant DTU Management Engineering, Energy Systems Analysis group TIMES-DK Developers 2 1

2 Danish Energy Agreement - March % wind power in 2020 No fossil fuels for power and heat production in 2035 Fossil independent in 2050 Development of a general equilibrium model for modelling the energy system and societal economics to identify efficient policies and regulation measures The work runs to 2015 TIMES was chosen as tool for modelling the energy system 3 4 Title of the presentation 2

3 5 Sweden Norway Germany TIMES-DK model geography DK-West Regions Power trade DK-East Sweden Germany Central De-central Individual Central De-central Individual 6 3

4 Some focus areas from TIMES-DK 1. Time slices that catch intermittency in the energy system =>Time slice Tool checking for critical situations 2. District heating expansion potential 3. Heat savings potential => The tool used for analysing 2. and 3. is a Heat Atlas 7 Heat Atlas Geographical area Building types Age of buildings Use of building Heat source => Calculation of heat loss and potential savings on building level 8 4

5 9 Heat atlas analysis of expansion of district heating and Energy Savings d DH IND,2 d DH IND,1 10 5

6 Heat atlas analysis of expansion of district heating 11 Heat atlas analysis of heat savings in building stock Marginal annualised costs of heat savings ( /TWh/y) 12 6

7 13 Time slices Want to : Catch the critical periods Have a low number of time slices Model a system with high share of intermittent renewable power production. Working thesis: If we capture the most critical combinations then we can minimise the problems of modelling intermittent in relatively few time slices. 7

8 Time Slices Critical combinations : 1. Wind High, Power demand low 2. Power demand High, Wind Low 3. Peak PV 4. High heat demand, high wind 15 Title of the presentation 8

9 Time Slices Ending up with 4 timeslices: A: Wind High, Power demand low B: Power demand High, Wind Low C: Peak PV D: Rest The combination High heat demand, High wind production is left out, because there was no hour left for this group, after taking out the other combinations. 17 Title of the presentation Time Slices spring Summer Fall Winter Work Day A D C B Non Work day A D C B Chronology SWDA SWDD SWDC SWDB = 32 Time slices 9

10 Finding the thresholds for High and Low - Again using the profiles Power Heat PV Wind Level Season demand demand 2 R S F W R S F W Relative to annual average. High: If Value > Level 2; Medium: Else If Value > Level 1; Low: else Analysing the thresholds 10

11 Size of time slices 11

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14 Some results For testing the model we are running 3 different scenarios Base Existing plants and their decommissioning Already decided new power plant until 2017 WLP Base + Meet 50% wind target in 2020 WLP+NFE Base + WLP + No fossil fuels are allowed for power and DH production from

15 18000 Power Production Capacity by fuel [MW] - Denmark Waste Wind On-Shore Wind Off-Shore Coal and Peat PV A B C A B C A B C A B C A B C A B C A B C A B C A B C A B C Orimulsion, Heavy Fuel Oil, Diesel Hydro Natural Gas Biomass, Crops, Straw, Wood Biogas 29 Title of the presentation 200 Electricity Production by fuel [PJ] - Denmark Endogenous NET imp-exp DKW Exogenous Import from SE 150 Exogenous Export to SE Exogenous Import from NO Waste 100 Wind On-Shore Wind Off-Shore 50 Coal and Peat PV Hydro 0 Natural Gas -50 A B C A B C A B C A B C A B C A B C A B C A B C A B C A B C Biomass, Crops, Straw, Wood Biogas 30 Title of the presentation 15

16 160 CHP and DH Heat Only Plants Heat Production [PJ] - DK Waste 140 Solar 120 Natural Gas 100 Geothermal 80 Electricity 60 Coal and Peat Biomass, Crops, Straw, Wood Biogas 0 A B C A B C A B C A B C A B C A B C A B C A B C A B C A B C Title of the presentation Power Production Capacity by fuel [MW] - Denmark Biogas Biomass, Crops, Straw, Wood Natural Gas Hydro Orimulsion, Heavy Fuel Oil, Diesel PV Coal and Peat Wind Off-Shore Wind On-Shore Waste 32 Title of the presentation 16

17 180 Electricity Production by fuel [PJ] - Denmark Biogas Biomass, Crops, Straw, Wood Natural Gas Geothermal Hydro PV Coal and Peat Wind Off-Shore Wind On-Shore Waste Exogenous Import from NO Exogenous Export to SE Exogenous Import from SE Endogenous NET imp-exp DKW 160 CHP and DH Heat Only Plants Heat Production [PJ] - DK Biogas Biomass, Crops, Straw, Wood Coal and Peat Electricity Geothermal Natural Gas Solar Waste 34 Title of the presentation 17

18 Future work on TIMES-DK Expanding the model with more sectors and power sector of the surrounding countries in the existing project group (not finally decided yet) New research project under the Danish Research Council together with e4sma, UCC and a lot of stakeholders focussing on advanced modelling of the transport sector in TIMES-DK (Decision on funding comes mid November) Using TIMES in master course in DTU Master in Sustainable Energy 35 18