LUT ENERGY MODEL RESULTS FOR LUT/VTT ASSUMPTIONS

Transcription

1 ENERGY MODEL RESULTS FOR / ASSUMPTIONS Michael Child, Dmitrii Bogdanov and Christian Breyer Lappeenranta University of Technology Jussi Ikäheimo, Esa Pursiheimo, Juha Kiviluoma, Pasi Vainikka and Hannele Holttinen Technical Research Centre of Finland Neo-Carbon Energy 8th Researchers Seminar, August 23-24, 2017, Lappeenranta, Finland

2 Highlights scenario showed higher domestic production of electricity, particularly by prosumers with batteries in Finland and Sweden results showed more trade of electricity, particularly from hydro-rich Norway and wind-rich Denmark financial assumptions were typically higher, leading to roughly 10% higher LCOE Generation mix was rather similar, with the noted exception of fewer prosumers in the case Role of wind power quite similar in both cases Less biomass, waste and hydro resource use in case Substituted by solar PV prosumers 2

3 Motivation and Methods To compare simulation results using two different set of financial and resource assumptions for the Energy System Model and This comparison was done in parallel with the same basic assumptions using the TIMES model (with results from WILMAR/Balmorel) To what extent do the assumptions affect the outcome? Several key assumption differences existed between the two groups Simulation was 2050 overnight scenario with power trade between regions Each country represented a single node Results were developed graphically, and discussed within members of WP2 3

4 Assumption differences - Resource PV fixed tilted PP Capex Opex fix Lifetime PV rooftop - residential Capex Opex fix Lifetime PV rooftop - commercial Capex Opex fix Lifetime PV rooftop - industrial Capex Opex fix Lifetime PV single-axis PP Capex Opex fix Lifetime Wind PP Capex Opex fix Lifetime Wind Offshore Capex Opex fix Lifetime The division of solar PV into a greater number of categories was ultimately a very influential factor How prosumers are defined is very important 4

5 Assumption differences - Transformer Water Electrolysis Capex Opex fix Opex var Lifetime Efficiency 84% 84% CCGT PP Capex Opex fix Opex var Lifetime Efficiency 60% 60% OCGT PP Capex Opex fix Opex var Lifetime Efficiency 43% 40% Int Combust Generator Capex Opex fix Opex var Lifetime Efficiency 40% 40% Higher costs for elements of PtG in case 5

6 Assumption differences - Transformer Biomass PP Capex Opex fix Opex var Lifetime Efficiency 45% 49% MSW incinerator Capex Opex fix Opex var Lifetime Efficiency 30% 30% Methanisation Capex Opex fix Opex var Lifetime Efficiency 77% 77% CO2 direct air capture Capex Opex fix Opex var Lifetime Efficiency 78% 78% 6

7 Assumption differences Storage and biomass Battery Capex Opex fix Opex var Lifetime Efficiency 94% rt 91% rt PHS Capex Opex fix Opex var Lifetime Efficiency 85% rt 83% rt Cost assumptions for batteries are quite different Biomass NOR /kwh DEN SWE FIN biomass cost is weighted average of wood residue cost of approx /kwh and /kwh for agricultural and other solid residues; cost based on 5 /GJ for all biomass 7

8 Interconnections All countries treated as single nodes with single connections between them. 8

9 Load profile 9

10 Import/Export Key insights: Higher volume of power trade in case Also higher transmission capacity 10

11 Grid utilisation Finland is strong importer, while Norway is a strong exporter 11 Michael Child Michael.Child@lut.fi

12 LCOE Overnight LCOE is mainly affected by prosumer costs, and to a lesser extent the higher cost of biomass in the case 12

13 LCOE Overnight Breakdown of components essentially the same 13

14 LCOE System System LCOE (excluding prosumers) slightly higher in the case due to slightly higher generation costs 14

15 LCOE System Higher generation costs are due to higher cost assumptions (generation and biomass) in the case Higher impact of storage and transfer costs related to prosumers in the case 15

16 LCOE Prosumers The higher LCOE of PV prosumers in the case was a determining factor in the results Due to cost assumption differences in prosumer PV systems and batteries 16

17 Installed capacities 17 Higher PV prosumer generation in simulation results in lower biomass and hydro-based generation, but wind capacities are still quite similar Technology (GW) CCGT OCGT Biomass PP Waste PP Biogas PP Hydro ROR Hydro dams CSP 0 0 Geothermal 0 0 PV prosumers total PV 0-axis system PV 1-axis system 0 0 Wind onshore Wind offshore

18 Annual generation Biomass use: 300 TWh; including 8 TWh of MSW Biomass use: 322 TWh; including 30 TWh of MSW 18

19 Storage capacities Battery RES [GWh] Battery COM [GWh] Battery IND [GWh] Battery SC [GWh] Battery System [GWh] Battery total [GWh] PHS storage [GWh] TES storage [GWh] A-CAES storage [GWh] Gas storage [GWh] Higher PV prosumer generation in case combined with higher battery capacity a factor of lower battery cost assumption Also slightly more gas storage a factor of lower PtG costs 19

20 Storage capacities 20

21 Generation from storage case showed double the storage output of the case Greater relative role of battery storage in the case 21

22 Conclusions The role of prosumers with batteries was a critical difference between the two cases Assumptions concerning the cost of distributed solar PV and batteries affected the outcome of the simulation It appears reasonable to conclude that both the price of electricity and the cost of PV/Batteries will drive prosumer behaviour This will ultimately have a significant impact on the energy system, including the nature and amount of electricity trade Other assumption differences were less significant in the impact they had on the outcome Prosumers not only decrease their own cost of power, but also that of others in the energy system 22

23 Thank you for your attention! NEO-CARBON Energy project is one of the Tekes strategy research openings and the project is carried out in cooperation with Technical Research Centre of Finland Ltd, Lappeenranta University of Technology () and University of Turku, Finland Futures Research Centre. Please check next slides for an overview of all data, assumptions and references.