1. The role of power-to-gas in the future energy system: how much is needed and who wants to invest?
Valentin Bertsch (ESRI + TCD)
Muireann Lynch (ESRI + TCD)
Mel Devine (UCD)
ESRI-UCC-MaREI Energy Research Workshop: National Energy & Climate Policy
17/05/2018

2. Background and Motivation Model & Data Selected Results Conclusion
Outline
Background and Motivation
Model & Data
Selected Results
Conclusion
Limitations and Outlook 2
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3. Background & Motivation
Background and Motivation
Energy systems based on renewable energy sources (RES) have an increasing demand for flexibility
Largely untapped source of flexibility: Energy Systems Integration (ESI)
Increasing integration between energy pathways that were traditionally considered in isolation
Increasing integration across scales
Making use of the arising synergies
Power-to-Gas (PtG) as one example for ESI
Possibility to integrate the power and gas systems more strongly
Use electricity for electrolysis (output: hydrogen + oxygen)
Inject hydrogen directly into gas grid, or
Convert hydrogen with CO2 to methane
Efficiency: ̴80% vs. ̴50%
Research objective: understand the role of PtG in a future energy system
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4. Background & Motivation
Literature and Research Questions
Literature
Broad strands:
Power-to-Gas technology itself
Cost-benefit of Power-to-Gas
Power-to-Gas in electricity system (especially 100% RES-E)
No real examination of endogenous investment decision
No market or portfolio effects, e.g., the potential of a technology, such as PtG, to render another technology more or less profitable
Research questions
What is the optimal investment in Power-to-Gas?
How does it depend on increasing variable renewables?
Are there portfolio effects?
What are the effects on consumer costs and RES curtailment/integration?
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5. Model: Mixed Complementarity Problem
Model & Data
Model: Mixed Complementarity Problem
Generators:
Minimise costs
Decisions:
PV or micro generation
(Load shifting)
(Load shedding)
Consideration of residential and industrial/commercial consumer groups (different load profiles)
Consumers:
Maximise profit
Decisions:
Generation
Investment/Decommission
Revenues from energy market, capacity market and feed-in premium (FIP) for RES generation
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6. Power generation firms and technologies
Model & Data
Power generation firms and technologies
Firms can invest in new / exit existing conventional generation capacity
Firms can invest in PtG
Wind capacity varied and fixed exogenously
Fixed gas price assumed (18€/MWh gas) 6
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7. Power-to-Gas itself is loss-making
Results
Power-to-Gas itself is loss-making
Considered as a stand-alone technology, PtG makes a loss of 25,950 €/MWa
Corresponds to price gap of 25€/MWh of gas (hydrogen) on top of the gas price of 18€/MWh 7
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8. Results
Optimal investment in Power-to-Gas increases with installed wind capacity
Power-to-Gas investment once wind generation exceeds 50% of annual demand 8
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9. Results
Changing profits of renewable generators for increasing levels of wind penetration
Adding more wind generation to the system is more profitable in the presence of PtG 9
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10. Generator profits by firm
Results
Generator profits by firm *
Firms with wind generation have an incentive to invest in PtG 10
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* Assuming for each firm that it is facing the investment costs

11. Changes in market price structure: comparison of price duration curves
Results
Changes in market price structure: comparison of price duration curves
Wind 100% of peak demand
Wind 135% of peak demand
PtG increases demand and, hence, prices in hours with low residual demand and therefore increases profitability of RES generation 11
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12. Consumer costs with vs. without PtG
Results
Consumer costs with vs. without PtG 12
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13. Curtailment with vs. without PtG
Results
Curtailment with vs. without PtG 13
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14. Conclusion
Conclusion
Increasing flexibilities in the system helps to integrate renewables
Firms with RES generation benefit from investing in PtG
While technology itself is loss-making, power-to-gas particularly increases demand and hence prices in low-load hours, which makes the RES generation more profitable
Total transfer from consumers to producers increases in presence of PtG
Methodologically: work highlights importance of considering technology impact on generation portfolio, rather than considering costs and benefits of a technology in isolation (e.g., using metrics such as Levelised Cost of Electricity (LCOE) or NPV) 14
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15. Limitations and Outlook
Limitations & Outlook
Limitations and Outlook
All firms modelled as price takers
No consideration of investment decisions by consumers or behavioural aspects related to their decisions
Outlook
Competition of large-scale PtG with consumer investments in small-scale (battery) storage technologies and demand response
Understand potential benefits of using “green gas” from PtG outside the electricity sector 15
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16. Working papers available on ESRI website
Muireann Lynch, Mel Devine, Valentin Bertsch (2018) The role of power-to-gas in the future energy system: how much is needed and who wants to invest? ESRI Working Paper No. 590 (under journal review). Valentin Bertsch, Mel Devine, Conor Sweeney, Andrew C. Parnell (2018) Analysing long-term interactions between demand response and different electricity markets using a stochastic market equilibrium model. ESRI Working Paper No. 585 (under journal review).
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17. Thank you very much for your attention!
Contact:
Valentin Bertsch
Associate Research Professor Economic and Social Research Institute
Adjunct Professor Trinity College Dublin
Tel: Fax: /
Web: 17
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18. Acknowledgements
ESRI Energy Policy Research Centre, funded by DCCAE, ESB, Ervia, CER, EirGrid, Viridian/Energia, SSE Airtricity
Sustainable Electrical Energy Systems cluster, funded by Science Foundation Ireland
Energy Systems Integration Partnership Programme, funded by Science Foundation Ireland
Collaborative Research of Decentralisation, Electrification, Communications and Economics, funded by Science Foundation Ireland, National Science Foundation (US) and Department for Employment and Learning (NI)
Gas Innovation Group, funded by Gas Networks Ireland and Science Foundation Ireland
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19. BACKUP 19
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20. Assumptions (selection)
Gas price: €/MWh_th
Coal price: 9.36 €/MWh_th
CO2 price (ETS): 10 €/t CO2
Power-to-Gas
Specific investment + annual O&M costs (electrolysis): 750 €/kW, corresponding to an annualised specific costs of 54,487 €/MWa
Efficiency (electrolysis): 70%

21. Model & Data
Renewable generation: main source of uncertainty considered in the model
Similar capacity factor scenarios for uncertain PV generation
Spatial and temporal correlation between wind and PV
FIP assumed for RES generation 21
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Source: Bertsch et al. (2018)

22. Considered consumer groups
Model & Data
Considered consumer groups
Industrial/Commercial
Residential
Without PV
Group 1
Group 3
With PV
Group 2
Group 4 22
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