Overall PYSOLO System Performance - Process Design & Economic Analysis

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Climate, Infrastructure and Environment Executive Agency. Neither the European Union nor the granting authority can be held responsible for them. Overall PYSOLO System Performance Dissemination Event, 6 November 2025, Zaragoza Marco Colombi, Matteo Romano, Marco Binotti Process Design & Economic Analysis www.pysolo.eu 2 Scope of the Work 1st PYSOLO Dissemination Event -Overall PYSOLO System Performance, Marco Colombi (POLIMI), 06/11/25 Perform a preliminary techno-economic assessment of the PYSOLO concept, considering the integration of a biomass pyrolysis plant with a solar receiver (no electrical heating) www.pysolo.eu 3 Conventional biomass pyrolysis is typically sustained by burning char and pyrogas,an economically and ecologically inefficient step which also results in additional CO₂ emissions. Benchmark Conventional Fast Pyrolysis 1st PYSOLO Dissemination Event -Overall PYSOLO System Performance, Marco Colombi (POLIMI), 06/11/25 Conventional Pyrolysis Plant Biomass Dryer Ash Air Cyclone Combustor Cyclone Filter Pyrolyzer Biochar Soil Amendment Solid Separator PHC Oil Filter Bio-Oil Quencher To Market / Biorefinery Sludge Pyrolyzer Outlet Temperature:430°C PHC Inlet Temperature:610°C Biomass Flow:50 dry tons/d (10 MWLHV) Thermal Power requested for Pyrolysis: 1.65 MWTH (~16.5% of biomass LHV) Hot Flue Gases Gas Exit Pyrogas Compressor Electricity from Pyrogas Fluidizing Gases Hot PHC www.pysolo.eu 4 PYSOLO: Solar Pyrolysis 1st PYSOLO Dissemination Event -Overall PYSOLO System Performance, Marco Colombi (POLIMI), 06/11/25 !"#ABCDEFG#AH,E -K/ACH#EM!F-1E !"#$%"&'& !%()* O/KEPDQ#E RCS#S PDQT8T9TGHE RCS#S :,;D/G#E PTDK#A <,A/D,9#A RCSE F=TK :/B>QSK/A -/DT8E -#?CACK/A @TDEPTDK#A AT/BCSS BA,#A O/KE !CGC :/D8E !CGC !"#$B"& aTA :/B?A#SS/A bQ#G;"#A !"#'()* -/DCAEc/KCA, dTDGEc#;#Te#A +$%(#, !%()* !"#$%&'"() -/DCAE !/f#A O#DT/SKCKE PT#D8 +&,-./ 01*#.)O RCSEO/D8#A !/ gCAC#KEh AT/A#iTG#A, -/TD aB#G8B#GK FD#;KAT;TK,EiA/B <,A/HCS <O: www.pysolo.eu 5 PYSOLO: Hybrid Pyrolysis 1st PYSOLO Dissemination Event -Overall PYSOLO System Performance, Marco Colombi (POLIMI), 06/11/25 !"#ABCDEFG#AH,E -K/ACH#EM!F-1E !"#$%"&'& !%()* O/KEPDQ#E RCS#S PDQT8T9TGHE RCS#S :,;D/G#E PTDK#A <,A/D,9#A RCSE F=TK :/B>QSK/A -/DT8E -#?CACK/A @TDEPTDK#A AT/BCSS BA,#A O/KE !CGC :/D8E !CGC !"#$B"& aTA :/B?A#SS/A bQ#G;"#A aS" aTA :,;D/G# :/B>QSK/A !"#'()* -/DCAEc/KCA, dTDGEc#;#Te#A +$%(#, !%()* !"#$%&'"() *"+,)+-."+$#&'"() -/DCAE !/f#A O#DT/SKCKE PT#D8 +&,-./ 01*#.)O RCSEO/D8#A !/ gCAC#KEh AT/A#iTG#A, -/TD aB#G8B#GK FD#;KAT;TK,EiA/B <,A/HCS :,;D/G# <O: www.pysolo.eu 6 Components Modeling: Pyrolyzer 1st PYSOLO Dissemination Event -Overall PYSOLO System Performance, Marco Colombi (POLIMI), 06/11/25 Pyrolyzer •The adopted pyrolysis model has been developed by CRECK group at Politecnico di Milano. •The CRECK model has been calibrated to characterize each biomass type based on its elemental composition, mapping it onto CRECK reference species (e.g., various forms of lignin, hemicellulose, cellulose), for which detailed thermal degradation mechanisms have been developed. •Based on the Reactor Network Model approach, the pyrolysis reaction is simulated in afluidised bed reactor, a component which has been manually integrated in Aspen Plus. !"#$B&&'B(#)*+(',)-+."$"/B-012 !"#$"%F'( )F*##"+ ,"-%F.# !'/012'.31,"-%F.# www.pysolo.eu 7 Components Modeling: Rotary Kiln Receiver 1st PYSOLO Dissemination Event -Overall PYSOLO System Performance, Marco Colombi (POLIMI), 06/11/25 !"#$%&'"($%) *+#,&'-K-+/-% •1-D optical and thermal model to predict annual thermal energy generation. HTo w e r Optical model –Soltrace Solar Heat Flux Distribution •Main Parameters: •Tilt Angle (𝛿!"#$) •Fill Ratio •Residence time •PHC Flowrate and Thermal Power •Tower Height www.pysolo.eu 8 Components Modeling: Rotary Kiln Receiver 1st PYSOLO Dissemination Event -Overall PYSOLO System Performance, Marco Colombi (POLIMI), 06/11/25 !"#$%&'"($%) *+#,&'-K-+/-% •1-D optical and thermal model to predict annual thermal energy generation. HTo w e r •Main Parameters: •Tilt Angle (𝛿!"#$) •Fill Ratio •Residence time •PHC Flowrate and Thermal Power •Tower Height Thermal model PHC and Lateral Wall Temperature Distribution www.pysolo.eu 9 Components Modeling: Rotary Kiln Receiver 1st PYSOLO Dissemination Event -Overall PYSOLO System Performance, Marco Colombi (POLIMI), 06/11/25 !"#$%&'"($%) *+#,&'-K-+/-% •1-D optical and thermal model to predict annual thermal energy generation. HTo w e r •Main Parameters: •Tilt Angle (𝛿!"#$) •Fill Ratio •Residence time •PHC Flowrate and Thermal Power •Tower Height Optical, thermal and solar-to-thermal efficiencies www.pysolo.eu 16 Preliminary Results: MFSP Sensitivity Analysis 1st PYSOLO Dissemination Event -Overall PYSOLO System Performance, Marco Colombi (POLIMI), 06/11/25 A parametric analysis on the most important economic parameters affecting MFSPPYSOLO and MFSPCONV is carried out to understand under which economic conditions the PYSOLO system maintains its economic advantage: www.pysolo.eu 17 Conclusions 1st PYSOLO Dissemination Event -Overall PYSOLO System Performance, Marco Colombi (POLIMI), 06/11/25 •Solar-based pyrolysis can achieve over 90%carbon efficiency (50%in bio-oil, 35%in biochar, 8% in pyrogas), 20%percentage points higher than the conventional case. •Similarly, hybrid pyrolysis can achieve net negative emissions of -67.8 kgCO2/GJOIL compared to the conventional pyrolysis ones equal to -47.4 kgCO2/GJOIL (30%reduction). •MFSP reduction of 8% is obtained with respect to the conventional plant for the hybrid plant. •Even when subject to a50%variation in key economic and profitability parameters,the hybrid system maintains aclear competitive advantage over the conventional alternative. www.pysolo.eu Occasion, Speaker, Date 18 Safety as a pillar of PYSOLO’s sustainable technology •Safety integrated from the start •Embedded from the concept phase, not as aretrofit; •Proactive hazard identification to mitigate hazards early •Comprehensive risk assessment •Systematic risk assessment of each subsystem and the whole process chain. •Dual focus: substance hazards (flammable gases, biomass dusts, reaction products) + process hazards. •Use experimental results, modelling, past-incident learnings to close knowledge gaps and warn on regulatory bottleneck •Pysolo Technical choice -safer by Innovation •Adopt Solid Particle Heat Carrier (PHC) - removes moltensalt failure modes (leaks, corrosion), HTF leaks & fires. •Lower hazardous inventory on site → simplified maintenance and emergency response…but new emerging risks? Safety, sustainability and performance are co-equal design drivers TECHNOLOGICAL BLOCK RISKS Input preparation & Storage Biomass self-heating, dust explosions (ATEX), mechanical injury, dust inhalation Pyrolysis reactor Fire/explosion, gas leaks, oxygen ingress during startup/shutdown, burns, CO/CO₂exposure Gas treatment & product handling Biochar self-heating, dust explosion, gas leaks (CH₄, H₂, CO) Examples of a few conventional risks In 40 years of CSP operation: •~15% of plants faced an accident •~3% had off-site effects (fire plumes, toxic release) •Triggers: HTF/ molten-salt leaks, fires, explosions, Natech www.pysolo.eu Occasion, Speaker, Date 19 Life Cycle Assessment (Partner: nova-Institut GmbH) •Goal: Scientific evaluation of environmental impacts of the PYSOLO project •LCA is applied to assist the decision-making of the technology development and the selection of PHC, biomass feedstock, plant location, etc. •Recent activities: LCA hotspot analysis to identify the driving factors of environmental impacts •Assessment of Climate Change, Resource use (water, land, minerals, metals, etc.), Toxicity for humans and ecosystem 23% 71% -15% -60%-100% -50% 0% 50% 100% Scenario A Scenario B Scenario C Scenario D Deviation from the baseline scenario LCA scenario analysis supports the PYSOLO consortium to optimize the environmental performance and to design the most favourable system à Occasion, Speaker, Date 1st PYSOLO Dissemination Event -Overall PYSOLO System Performance, Marco Colombi (POLIMI), 06/11/25 Thank you! 20 www.pysolo.eu