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Optimization of hydrogen supply from renewable electricity including cavern storage

  • Timo Wassermann ORCID logo EMAIL logo , Henry Mühlenbrock , Philipp Kenkel ORCID logo , Jorg Thöming and Edwin Zondervan
Published/Copyright: June 17, 2022
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Abstract

The present study introduces a methodology to model electricity based hydrogen supply systems as a Mixed Integer Linear Programming (MILP) problem. The novelty of the presented approach lies especially in the linear formulations of the models for electrolysis and salt cavern storage. The proposed linear electrolysis model allows for an accurate consideration of operating limits and operating point-specific efficiencies, while the two-dimensional cavern model treats the cavern volume as a decision variable. The developed formulations are implemented in the open energy modeling framework (oemof) and applied to representative case studies with 2020 marginal conditions. Thereby, it has been confirmed that the individual consideration of power supply and hydrogen demand is crucial for optimal system design and operation. If electricity is drawn exclusively from the German grid, hydrogen costs of 2.67   kg H 2 1 are identified along with an increased CO2 footprint compared to natural gas based hydrogen. By contrast, a significantly reduced CO2 footprint results from autarkic wind power supply at costs of at least 4.28   kg H 2 1 . Further findings on autarkic operation include optimal ratios of electrolyzer and wind farm nominal power, as well as power curtailment strategies. Evidence is provided that salt cavern interim storage is beneficial. With grid connection, it serves to exploit electricity price fluctuations, while with renewable autarkic operation, it is essential to compensate for seasonal fluctuations in generation.


Corresponding author: Timo Wassermann, Advanced Energy Systems Institute, University of Bremen, Enrique-Schmidt-Straße 7, 28359, Bremen, Germany; and artec Sustainability Research Center, University of Bremen, Enrique-Schmidt-Straße 7, 28359, Bremen, Germany, E-mail:

This work is dedicated to Prof. Dr. Stefan Gößling-Reisemann, who inspired us, shared his knowledge with us and unfortunately cannot be with us today.


Funding source: German Federal Ministry for Economic Affairs and Climate Action

Award Identifier / Grant number: 03EIV051A

  1. Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: Funding of this research by the German Federal Ministry for Economic Affairs and Climate Action within the KEROSyN100 project (funding code 03EIV051A) is gratefully acknowledged.

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

Appendix
Table A1:

Technology lifetime of the different components.

Component [-] Lifetime [a] Reference [-]
AEL 25 [38]
Cavern 25 [19, 47]
Compressor 15 [47]
Battery 10 [21]
Table A2:

Relevant parameters for salt cavern simulation [39].

Cavern Volume Cavern height T s a l t T i n p m i n p m a x d i d o λ α i
[m3] [m] [°C] [°C] [bar] [bar] [m] [m] [W/(mK)] [W/(m2K)]
100,000 100 45.5 50 70 170 35.68 39.68 5.5 133
Table A3:

Configuration of wind farm “Norderwöhrden-Oesterwurth”. Latitude: 54.19°, longitude: 9.02°.

Turbine model [-] Hub height [m] Number of turbines [-] Nominal power per turbine [MW]
Enercon E-70/2300 99 6 2.30
Vestas V112/3300 119 3 3.30
Vestas V112/3450 119 11 3.45
Vestas V112/3450 94 11 3.45
Senvion 114/3200 93 2 3.20
33 106.00
Table A4:

Configuration of wind farm “Wöhrden Ost”. Latitude: 54.16°, longitude: 9.04°.

Turbine model [-] Hub height [m] Number of turbines [-] Nominal power per turbine [MW]
Vestas V112/3075 94 14 3.08
43.05
Table A5:

Configuration of wind farm “Kaskasi II”. Latitude: 54.49°, longitude: 7.70°.

Turbine model [-] Hub height [m] Number of turbines [-] Nominal power per turbine [MW]
Siemens-Gamesa SG167/8000 107.5 38 8.00
304.00
Table A6:

Ancillary costs of electricity procurement under EEG2021 based on 2020 price levels [78, 79].

Ancillary cost parameter Electrolyzer with grid supply without green PPA Electrolyzer with direct RE supply
[-] Remission scheme [-] Costs [€ MWh−1] Remission scheme [-] Costs [€ MWh−1]
Grid fees Total remission 0.00 Total remission 0.00
Concession fee Total remission 0.00 Total remission 0.00
CHP levy Fixed reduced tariff: electricity cost intensive business 0.30 Total remission 0.00
§ 19 StromNEV levy Fixed reduced tariff: electricity cost intensive business 0.25 Total remission 0.00
Interruptible loads levy No remission 0.07 Total remission 0.00
Offshore grid levy Fixed reduced tariff: electricity cost intensive business 0.30 Total remission 0.00
Electricity tax Total remission 0.00 Total remission 0.00
Renewable energy levy Remission to 15% 10.13 Total remission 0.00
11.05 0.00
Table A7:

Cost breakdown for the scenario “present H2 demand”.

Component Variable Unit Wind power autarkic Wind plus grid power Grid power
Cavern Capex € kg H 2 1 0.40 0.24 0.24
Cavern Opex € kg H 2 1 0.17 0.10 0.10
Cavern Electricity € kg H 2 1 0.04 0.03 0.03
Battery Capex € kg H 2 1 0.17 0.00 0.00
Battery Opex € kg H 2 1 0.03 0.00 0.00
Battery Electricity losses € kg H 2 1 0.01 0.00 0.00
Electrolyzer Oxygen revenue € kg H 2 1 −0.14 −0.14 −0.14
Electrolyzer Repl. Costs € kg H 2 1 0.14 0.13 0.13
Electrolyzer S&M € kg H 2 1 0.24 0.17 0.17
Electrolyzer T&I € kg H 2 1 0.20 0.15 0.15
Electrolyzer Water € kg H 2 1 0.02 0.02 0.02
Electrolyzer Electricity € kg H 2 1 2.02 2.23 1.83
Electrolyzer Capex € kg H 2 1 0.73 0.53 0.53
Compressor Capex € kg H 2 1 0.06 0.06 0.06
Compressor Opex € kg H 2 1 0.02 0.02 0.02
Compressor Electricity € kg H 2 1 0.05 0.07 0.05
Curtailment Electricity € kg H 2 1 0.13 0.00 0.00
Total € kg H 2 1 4.28 3.62 3.19
Table A8:

Cost breakdown for the scenario “PtM H2 demand”.

Category Variable Unit Wind power autarkic Wind plus grid power Grid power
Cavern Capex € kg H 2 1 0.17 0.05 0.05
Cavern Opex € kg H 2 1 0.07 0.02 0.02
Cavern Electricity € kg H 2 1 0.06 0.05 0.02
Battery Capex € kg H 2 1 0.24 0.00 0.00
Battery Opex € kg H 2 1 0.04 0.00 0.00
Battery Electricity losses € kg H 2 1 0.01 0.00 0.00
Electrolyzer Oxygen revenue € kg H 2 1 −0.14 −0.14 −0.14
Electrolyzer Repl. Costs € kg H 2 1 0.12 0.11 0.11
Electrolyzer S&M € kg H 2 1 0.20 0.17 0.16
Electrolyzer T&I € kg H 2 1 0.15 0.12 0.12
Electrolyzer Water € kg H 2 1 0.02 0.02 0.02
Electrolyzer Electricity € kg H 2 1 3.71 3.72 1.82
Electrolyzer Capex € kg H 2 1 0.54 0.44 0.41
Compressor Capex € kg H 2 1 0.02 0.02 0.02
Compressor Opex € kg H 2 1 0.01 0.01 0.01
Compressor Electricity € kg H 2 1 0.11 0.11 0.06
Curtailment Electricity € kg H 2 1 0.01 0.00 0.00
Total € kg H 2 1 5.33 4.69 2.67

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Received: 2022-02-17
Accepted: 2022-04-13
Published Online: 2022-06-17

© 2022 Walter de Gruyter GmbH, Berlin/Boston

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  9. Latest developments on the synthesis of bioactive organotellurium scaffolds
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  22. Accessing the environmental impact of tellurium metal
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  25. Educators’ reflections on the teaching and learning of the periodic table of elements at the upper secondary level: a case study
  26. Optimization of hydrogen supply from renewable electricity including cavern storage
  27. A short review on cancer therapeutics
  28. The role of bioprocess systems engineering in extracting chemicals and energy from microalgae
  29. The topology of crystalline matter
  30. Characterization of lignocellulosic S. persica fibre and its composites: a review
  31. Constructing a framework for selecting natural fibres as reinforcements composites based on grey relational analysis
  32. Polybutylene succinate (PBS)/natural fiber green composites: melt blending processes and tensile properties
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  34. Thermal properties of wood flour reinforced polyamide 6 biocomposites by twin screw extrusion
  35. Manufacturing defects and interfacial adhesion of Arenga Pinnata and kenaf fibre reinforced fibreglass/kevlar hybrid composite in boat construction application
  36. Wettability of keruing (Dipterocarpus spp.) wood after weathering under tropical climate
  37. Simultaneous remediation of polycyclic aromatic hydrocarbon and heavy metals in wastewater with zerovalent iron-titanium oxide nanoparticles (ZVI-TiO2)
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