Sustainability assessment in R&D of Power-to-X technologies

Transcription

1 Sustainability assessment in R&D of Power-to-X technologies Dominik Poncette, Andreas Patyk, Mara Scherrieb Source: IEC/TU Freiberg KIT The Research University in the Helmholtz Association

2 Motivation for R&D integration Early assessment enables influence on R&D process High Influence on innovation Cost for corrections/ changes Low Low Stage of technology / knowledge High [Source: Vassiliadis 2017] 2

3 Copernicus Power-to-X project: Long chained alcohols Supply chain Electricity Water CO 2 Upstream Downstream CO 2 -Elektrolysis H 2 / CO Fermentation Alcohols 3

4 Copernicus Power-to-X project: LNG production Supply chain Electricity Water CO 2 Upstream Downstream Water electrolysis H 2 3-phase methanation Liquefaction LNG 4

5 Copernicus Power-to-X project: Syngas-to-fuel Downstream Supply chain Biogas-CO 2 Electricity Water DAC-CO 2 Methanol synthesis CO 2 Upstream Downstream Water electrolysis H 2 Gasoline synthesis (MTG) Gasoline O 2 5

6 Sustainability assessment Life Cycle Assessment with comprehensive impact assessment (method ReCiPe) Particulate matter Trop. ozone formation (hum) Ionizing radiation Stratos. ozone depletion Human toxicity (cancer) Human toxicity (non-cancer) Global warming Water use Freshwater ecotoxicity Freshwater eutrophication Trop. ozone (eco) Terrestrial ecotoxicity Terrestrial acidification Land use/transformation Marine ecotoxicity Mineral resources Fossil resources Increase in respiratory disease Increase in various types of cancer Increase in other diseases/causes Increase in malnutrion Damage to freshwater species Damage to terrestrial species Damage to marine species Increased extraction cost Oil/gas/coal energy cost Damage to human health Damage to ecosystems Damage to resource availability [Source: Goedkoop 2008] 6

7 Life Cycle Assessment Life cycle assessment framework Goal and scope definition Inventory Analysis Interpretation Direct applications: Product development and improvement Strategic planning Public policy making Marketing Other Impact Assessment [Source: DIN EN ISO 14040] 7

8 Methodology of modeling in LCA The assessment is based on elementary flows Material or energy entering or leaving the system without previous or subsequent human transformation. Product(s) Emissions Resources Process chain Solid waste Waste water Creation of linear input/output models for each process step Supply chains are taken from the ecoinvent database 8

9 Life cycle inventory (Process chain) Life Cycle Inventories comprise data mining and calculation methods for quantifying relevant input and output flows of a product system. Different CO 2 sources e.g. Biogas plant, industry (emissions), direct air capture Electricity Water Electrolysis CO 2 H 2 Methanol synthesis Methanol Gasoline MtG process 9

10 Life cycle inventory (Data mining) Process structure Material and energy flows 10

11 Life cycle inventory (Data mining) Process structure Material and energy flows 11

12 Modelling process chain Hydrogen source Carbon source Methanol synthesis Gasoline synthesis 12

13 First (exemplary) results 13

14 Data uncertainty Possible data sources: (Expert) estimations Literature Measurements Different kind of uncertainties unreducible Aleatory: Resulting from random incidents Epistemic: Resulting from fragmentary knowledge Increase of research and/or data collection expenditure reducible Source: Data uncertainty decreases with increasing technology maturity. 14

15 Uncertainty assessment via TRL CO 2 source Electrolysis 0: No data 1: stoichiometric data / estimates / literature values (possibly incomplete) ~TRL 1-3 2: Laboratory measurement data and elaborated simulation data ~TRL 4-5 3: Derived data for marketable investment (well-founded forecast data) ~TRL 6-7 4: Measurement data from a marketable system ~TRL 8-9 Methanol Synthesis Gasoline synthesis Biogas Industry plant emissions DAC Process structure Educt/product flows Energy flow data (thermal, electrical, chemical) Process steam (pressure, temp., quantity) Coolant (temp., quantity) Operating & auxiliary materials (e.g. cat.) Apparatuses (material composition & production)

16 Identification of key elements Analysing outputs regarding specific indicators inputs: Contribution to considered output Uncertainty [Source: Heijungs 1996] Reducing uncertainty Reducing contribution 16

17 Classification of elements (exemplary) high Hydrogen source uncertainty Water Electricity low low contribution high 17

18 Classification of elements (exemplary) high Hydrogen source Methanol synthesis Electricity uncertainty Water Wastewater treatment Steam Electricity low low contribution high 18

19 Classification of elements (exemplary) high Hydrogen source Methanol synthesis Electricity Fuel synthesis uncertainty low Water Nitrogen Wastewater treatment Compressed air Wastewater treatment Steam Electricity Electricity Steam low contribution high 19

20 Interference of key elements (Partly) Exogenic: Not included in the system and not influenceable (Partly) Endogenous: Included in the system and influenceable Reducing uncertainty Reducing contribution/ improving performance 20

21 Conclusion of method Modelling / simulation Adaptation, improvement, optimization 5 1 Iterative improvement 2 Sensitivity analysis 4 3 Identification of key elements Uncertainty analysis 21

22 Literature DIN EN ISO DIN EN ISO 14040: , Environmental management Life cycle assessment Principles and framework. Beuth Verlag GmbH. International organization for standardization: ISO Environmental management - Life cycle assessment - Principles and framework International organization for standardization: ISO Environmental management - Life cycle assessment - Requirements and guidelines Goedkoop, Mark Jacob, Reinout Heijungs, Mark Huijbregts, An De Schryver, Jaap Struijs, und Rosalie van Zelm ReCiPe A life cycle impact assessment method which comprises harmonised category indicators at the midpoint and the endpoint level. Report I: characterisation. 1st ed. Ruimte en Milieu - Ministerie van Volkshuisvesting, Ruimtelijke Ordening en Milieubeheer. Heijungs, Reinout Identification of Key Issues for Further Investigation in Improving the Reliability of Life-Cycle Assessments. Journal of Cleaner Production 4 (3 4): Vassiliadis, Michael, Hrsg Digitalisierung und Industrie 4.0: Technik allein reicht nicht. Hannover: Industriegewerkschaft Bergbau, Chemie, Energie. 22

23 Thank you! Contact: Scientific staff / doctoral student Research area: Energy - Resources, technologies, systems Raum: 519 Tel.: Dominik.poncette@kit.edu 23