Arman Aghahosseini, Dmitrii Bogdanov, Mahdi Fasihi and Christian Breyer Lappeenranta University of Technology, Finland

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1 The Role of Hydrogen Production in 100% Renewable Energy Systems in the Power and Industrial Gas Sectors - Implementing Biogas-to-Methane to the LUT Model Arman Aghahosseini, Dmitrii Bogdanov, Mahdi Fasihi and Christian Breyer Lappeenranta University of Technology, Finland Neo-Carbon Energy 9th Researchers Seminar LUT, Lappeenranta - December 11-13, 2017

2 Agenda Motivation Methodology and Data Results of the Energy System modeling Summary 2

3 Motivation Fossil fuels GHG emissions Increasing demand Limited resources Promising possibility to build cost competitive independent 100% RE system using current technologies Green job opportunities source: Ram M. et al., Global Energy System based on 100% Renewable Energy Power Sector, study by LUT and EWG, COP23, November 8 3

4 Motivation Historically, fossil fuels have dominated the power generation globally RE is growing, but still not on track to meet the climate goals agreed upon at COP21 Hydropower, wind and solar energy have the largest roles in total generation from RE across the world RE has an intermittent nature and needs further flexibility Hydrogen is found to be a solution to balance the energy system source: Farfan J. and Breyer Ch., Structural changes of global power generation capacity towards sustainability and the risk of stranded investments supported by a sustainability indicator; J of Cleaner Prodcution, 141, Hydrogen technology can be used as long-term storage in Power-to-Gas (PtG) systems and for Power-to-X (PtX) applications What can be the role of hydrogen in a 100% RE system in the future? 4

5 Agenda Motivation Methodology and Data Results of the Energy System modeling Summary 5

6 Key Objective Definition of an optimally structured energy system based on 100% RE supply Optimal set of technologies, best adapted to the availability of the regions resources, Optimal mix of capacities for all technologies in the studied regions, Optimal operation modes for every element of the energy system, Least cost energy supply for the given constraints. Input data Historical weather data for: solar irradiation, wind speed and hydro precipitation Available sustainable resources for biomass and geothermal energy Synthesized and national power load data Non-energetic industrial gas demand Efficiency/ yield characteristics of RE plants Efficiency of energy conversion processes Capex, opex, lifetime for all energy resources Min and max capacity limits for all RE resources Nodes and interconnections configuration LUT Energy System model, key features Linear optimization model Hourly resolved configuration Multi-node approach Overnight and transition modelings Flexibility and expandability 6

7 LUT Energy System Model Full system Renewable energy sources PV rooftop PV ground-mounted PV single-axis tracking Wind onshore/ offshore Hydro run-of-river Hydro dam Geothermal energy CSP Waste-to-energy Biogas Biomass Electricity transmission node-internal AC transmission interconnected by HVDC lines Storage options Batteries Pumped hydro storage Adiabatic compressed air storage Thermal energy storage, PtH Gas storage based on PtG Water electrolysis Methanation CO 2 from air 7 Energy Demand Electricity Industrial Gas The role Gas of hydrogen storage production in 100% renewable energy systems in the power and industrial gas sectors

8 LUT Energy System Model Enhanced model (developed for biogas upgrading and power-to-gas technology) bio-waste (e.g. municipal) is used as feedstock to generate biogas for electricity production In countries with sustainable biomass resources, depending on the optimised cost: 60 mol.% of feedstock is converted into bio-methane (CH 4 ) 40 mol.% is CO 2 together with CH 4 forming biogas The separated CO 2 in the biogas upgrading process can be utilised for SNG production Currently operated by ETOGAS GmbH (previously Solarfuel) in cooperation with MT-BioMethan GmbH in Germany Biogas potential: 850 TWh th for Europe and 34 TWh th for Eurasia 8

9 Global Overview Regional study Results for the standard model (energy transition): Ram M. et al., Global Energy System based on 100% Renewable Energy Power Sector, study by LUT and EWG, COP23, November 8 The world is structured into 9 major regions, which are further divided to 92 sub-regions Some sub-regions are comprised of more than one smaller (by population) country, while others represent parts of a larger country The sub-regions are interconnected by power lines within the same country All results shown are for the Power and Integrated Scenarios Two major regions marked in yellow are selected for this presentation The LUT model will be further applied to the whole world for the peer-reviewed paper 9

10 Scenarios assumptions key data and assumptions for the year 2030 Country-wide scenario (power sector) grid interconnection between the sub-regions within the same country Integrated scenario (power and non-energetic industrial gas sectors) Country-wide configuration with additional industrial gas demand Assumptions Key data for the selected regions Country-wide Scenarios Integrated PV self-consumption X X Grid interconnection X X Power demand X X Industrial Gas demand X Assumptions (2030) Europe Regions Eurasia Population (million) Electricity demand (TWh el ) Non-energetic industrial gas demand (TWh th )

11 Global Full Load Hours Key insights for solar PV: most evenly distributed energy resource around the world diurnal variation seasonal stability in Sun Belt region stronger seasonality in northern hemisphere Key insights for wind energy: uneven global distribution excellent conditions available in all major regions in the world seasonal variation of availability 11 Arman Aghahosseini

12 Scenarios assumptions Generation profiles for the selected regions PV generation profile 2030 (Eurasia) PV generation profile 2030 (Europe) 12 Wind generation profile 2030 (Eurasia) Wind generation profile 2030 (Europe) Arman Aghahosseini

13 Agenda Motivation Methodology and Data Results of the Energy System modeling Summary 13

14 Results LCOE - Europe Key insights: LCOE dropped in the Integrated scenario compared with the Country-wide scenario in both models A reduction in LCOE is observed by 1.7% (Country-wide) and 0.7% (Integrated) in the Enhanced model in comparison to the Standard model Country-wide scenario Enhanced model Standard model Integrated scenario 14

15 Results LCOE - Eurasia Country-wide scenario Enhanced model Integrated scenario Standard model 15 Key insights: LCOE declined by 2.2% (Country-wide) and 0.2% (Integrated) from the Standard model to the Enhanced model

16 Results Hydrogen capacity - Europe Key insights: Significant increase is observed in the Enhanced model for both scenarios Country-wide: +440% Integrated: +71% UA (Ukraine Moldova), Germany, BRI (UK Ireland) and Benelux (Belgium, Netherlands, Luxembourg) have the most contribution to the total hydrogen capacity in Europe Country-wide scenario Enhanced model Standard model Integrated scenario 16

17 Results Hydrogen production - Europe Key insights: UA (Ukraine Moldova), Baltic (Estonia, Latvia, Lithuania), Germany, BRI (UK Ireland), Benelux (Belgium, Netherlands, Luxembourg) and TR (Turkey, Cyprus) experienced the most increase in the Integrated scenario compared to the Country-wide scenario Country-wide scenario Enhanced model Standard model Integrated scenario 17

18 Results Hydrogen capacity - Eurasia Country-wide scenario Enhanced model Integrated scenario Standard model 18 Key insights: Tremendous hydrogen capacity is installed in the Integrated scenario (both models) to satisfy the demand for power and non-energetic industrial gas sectors

19 Results Hydrogen production - Eurasia Country-wide scenario Enhanced model Integrated scenario Standard model 19 Almost all the regions contribute to hydrogen production, especially Russian regions High FLH (average for Eurasia: 6090 h) for the integrated scenario in the Standard model results in Arman slightly Aghahosseini higher Arman.Aghahosseini@lut.fi generation despite the lower capacity

20 Results Methane production share Europe (Standard model) Country-wide scenario Integrated scenario 20

21 Results Methane production share Europe (Enhanced model) Country-wide scenario Integrated scenario 21

22 Results Methane production share Eurasia (Standard model) Country-wide scenario Integrated scenario 22

23 Results Methane production share Eurasia (Enhanced model) Country-wide scenario Integrated scenario Key insights: Due to no extra cost for capturing the CO 2 from air in the biogas upgrading process, the costs of Hydrogen-to-SNG conversion drops for the CO 2 from biogas-to-sng route The gas output of PtG is higher in the Integrated scenario because of additional demand for the non-energetic industrial gas sector 23

24 Results Installed Capacities (Europe) [GW el ], CSP [GW th ] Country-wide Integrated Country-wide Integrated Enhanced Standard Europe Steam turbine OCGT CCGT Geothermal Bioenergy Hydropower CSP PV Wind Key insights: Solar PV dominates, while wind energy, hydropower and bioenergy complement Very similar installed capacity in both scenarios due to low industrial gas demand Slightly higher capacity needed in the Enhanced model compared to the Standard model, where cost is lower and role of hydrogen is remarkable 24

25 Results Installed Capacities (Eurasia) [GW el ], CSP [GW th ] Country-wide Integrated Country-wide Integrated Enhanced Standard Eurasia Steam turbine OCGT CCGT Geothermal Bioenergy Hydropower CSP PV Wind Key insights: Very high installed capacity is observed in the Integrated scenario due to high industrial gas demand All electricity and industrial gas demand can be covered by RE resources, where wind energy dominates followed by solar PV 25

26 Results Storage Technologies Europe Eurasia Enhanced Standard Enhanced Standard Integrated Country-wide Integrated Country-wide Integrated Country-wide Integrated Country-wide [TWh] Gas storage A-CAES storage TES storage PHS storage Battery storage 26 Battery storage is found to be the leader of storage technologies due to lower cost and optimised for daily storage cycles, which matches best with solar PV The need for storage is more significant in Europe due to higher electricity demand

27 Agenda Motivation Methodology and Data Results of the Energy System modeling Summary 27

28 Summary Existing RE technologies can generate sufficient energy to cover all electricity demand for the power and non-energetic industrial gas sectors in Europe and Eurasia for the year 2030 The use of hydrogen, in the availability of free CO 2 from biogas upgrading process, is beneficial for the energy system and provides additional flexibility Solar PV and wind energy dominate the energy system in power and industrial gas sectors 28-52% and 24-49% of total RE capacity in the Enhanced model, respectively 28-52% and 23-52% of total RE capacity in the Standard model, respectively Other sources of RE can provide energy security and system flexibility The need to eliminate dependency on fossil fuel resources has been an urgent issue for many countries throughout the region for the last few years 100% RE system is cost competitive at a cost of /MWh for the Standard model and /MWh for the Enhanced model, depending on the region and scenario The model needs to be applied for the whole world to better understand the impact of hydrogen in a 100% RE based system 28

29 Thank you for your attention! Further information and all publications at: The authors gratefully acknowledge the public financing of Tekes, the Finnish Funding Agency for Innovation, for the Neo-Carbon Energy project under the number 40101/14.