Integrated computer-aided working-fluid design and thermoeconomic - PowerPoint PPT Presentation

IV International Seminar on ORC Power Systems 13 – 15th September, 2017, Milan, Italy Integrated computer-aided working-fluid design and thermoeconomic ORC system optimisation MT White, OA Oyewunmi, MA Chatzopoulou, AM Pantaleo, AJ Haslam and CN Markides Clean Energy Processes (CEP) Laboratory Department of Chemical Engineering Imperial College London South Kensington Campus, London, SW7 2AZ, UK

White et al., ORC2017 13 – 15th September Project aims and objectives Key challenges in ORC system design: – Identification of optimal working fluids – Development of optimised systems based on thermoeconomic analyses – Explore novel cycle architectures to enhance system performance Research aim: Develop an advanced CAMD-ORC optimisation framework based on SAFT- γ Mie capable of evaluating advanced cycle architectures, system operation parameters and fluids based on thermoeconomic performance indicators Presentation objectives: – To introduce computed-aided molecular design (CAMD) within the context of ORC optimisation – To apply thermoeconomic analysis within a CAMD-ORC framework

White et al., ORC2017 13 – 15th September Computer-aided molecular design (CAMD) H Thermodynamic model Group- H C H contribution H C equation of H C state H Normal-alkanes H H H H C C H H Cyclo-alkanes C C Mixed-integer non-linear H H C C programming (MINLP) optimisation H H H H H H • Maximise/minimise objective function H C C • Integer optimisation variables: working fluid H C C C H • Continuous variables: thermodynamic cycle C C H • Binary variables: cycle architecture Aromatics H H

White et al., ORC2017 13 – 15th September CAMD-ORC model

White et al., ORC2017 13 – 15th September Group-contribution methods: SAFT- 𝜹 Mie • Molecular-based, free-energy equation of state:      assoc. ideal mono. chain assoc. A m , , , , u A A A A     NkT NkT NkT NkT NkT Association term Real gas term, monomers, Ideal gas term EoS for hard spheres r [1] V. Papaioannou et al., 2014, J. Chem. Phys. [2] S. Dufal et al., 2014, J. Chem. Eng. Data. [3] T. Lafitte et al., 2013, J. Chem. Phys. Grouping of monomers into chains Mie potential Chain term

White et al., ORC2017 13 – 15th September Group-contribution methods: Transport properties • Transport properties ( 𝑙, 𝜈, 𝜏) are required to size heat exchangers • Transport properties are not available from SAFT- 𝛿 Mie • Group-contribution methods are sought that are: o Applicable to a large range of fluids o Suitable for the functional groups used within the CAMD-ORC model o Straightforward to implement • Various methods have been implemented in the CAMD-ORC model (White et al ., 2017) Critical properties ( 𝑈 cr , 𝑄 cr , 𝑊 • cr ) are estimated using Joback and Reid Liquid phase Vapour phase Joback and Reid ( n -alkanes) Dynamic viscosity Reichenberg Sastri-Rao (branched alkanes) Thermal conductivity Sastri Chung Surface tension Sastri-Rao White et al ., Energy Conversion and Management, in press (2017).

White et al., ORC2017 13 – 15th September ORC thermodynamic modelling • Simple, sub-critical, non-regenerative ORC systems • Energy balance applied to main system components (pump, evaporator, expander, condenser) • Defined heat source and sink (temperature, mass-flow rate and specific-heat capacity) Fixed pump and expander efficiencies, 𝜃 p and 𝜃 e • • ORC variables: Condensation temperature, 𝑈 o 1 Reduced evaporation pressure, 𝑄 o r Evaporator pinch point, 𝑄𝑄 h o Expander inlet condition parameter, 𝑨 o • Constraints: Minimum evaporator pinch point, 𝑄𝑄 h,min o Minimum condenser pinch point, 𝑄𝑄 c,min o o Condensation pressure cannot be sub-atmospheric o Expansion cannot be into the two-phase region

White et al., ORC2017 13 – 15th September Component sizing • Evaporator and condenser units selected are of tube-in-tube construction • Heat transfer coefficient (HTC) and heat-transfer areas (HTA) as functions of Nusselt numbers • Evaporator is split into 3 sections: o Preheating section o Evaporating section o Superheating section • Condenser is split into 2 sections: o Desuperheating section o Condensing section • Each section is discretised spatially to account for changes in working-fluid properties over the length of the heat exchanger

White et al., ORC2017 13 – 15th September Component costing • Pump, pump motor and heat exchangers are costed using the correlations proposed by Seider et al . [1]: 0 = 𝐺 exp 𝑎 1 + 𝑎 2 ln 𝑌 + 𝑎 3 ln 𝑌 2 + 𝑎 4 ln 𝑌 3 + 𝑎 5 ln 𝑌 4 𝐷 𝑞 • Expander costed using the correlation proposed by Turton et al . [2]: 0 = 𝐺10 (𝑎 1 +𝑎 2 log 𝑌+𝑎 3 log 𝑌 2 ) 𝐷 𝑞 𝑌 the sizing attribute (power, heat-transfer area etc.) 𝐺, 𝑎 𝑜 correlation coefficients • Costs converted to todays prices using the CEPCI [1] Seider et al ., 2009, Product and Process Design Principles – Synthesis, Analysis and Evaluation. [2] Turton et al ., 2009, Analysis, Synthesis and Design of Chemical Processes.

White et al., ORC2017 13 – 15th September Optimisation max 𝑋 n (𝐲, 𝐳) Subject to: 𝑕 𝐲, 𝐳 ≤ 0 ; ℎ 𝐲, 𝐳 ≤ 0 ; 𝐲 min ≤ 𝐲 ≤ 𝐲 max ; 𝐳 min ≤ 𝐳 ≤ 𝐳 max • CAMD-ORC framework developed in the gPROMS modelling environment • MINLP optimisation solved using built-in outer approximation algorithm OAERAP

White et al., ORC2017 13 – 15th September Case study

White et al., ORC2017 13 – 15th September Definition • Three heat-source temperatures considered: 150, 250 and 350 ° C • Assumptions for waste-heat recovery case study: 𝑛 𝑑 p,h 𝑈 ci 𝑛 𝑑 p,c 𝜃 p 𝜃 e 𝑄𝑄 h,min 𝑄𝑄 c,min 𝑄 1,min h c kg/s °C kg/s kJ/(kg K) kJ/(kg K) °C °C bar 1.0 4.2 15 5 4.2 0.7 0.8 10 5 0.25 Alongside the ORC variables ( 𝑈 1 , 𝑞 r , Δ𝑈 sh , 𝑄𝑄 h ) the effect of the number of • >CH 2 groups on ORC performance is investigated for four fluid families n- alkanes methyl alkanes CH 3 – (CH 2 ) n – CH 3 (CH 3 ) 2 – CH – (CH 2 ) n – CH 3 1-alkenes 2-alkenes CH 2 = CH – (CH 2 ) n – CH 3 CH 3 – CH = CH – (CH 2 ) n – CH 3 • The aim is to maximize the net power output from a basic ORC system

White et al., ORC2017 13 – 15th September Thermodynamic results 250 °C 150 °C 350 °C Increasing heat-source temperature  Increasing system size

White et al., ORC2017 13 – 15th September Thermodynamic results 250 °C 150 °C 350 °C n- propane 2- pentene 2- hexene 35.2 kW 136.7 kW 219.0 kW

White et al., ORC2017 13 – 15th September Component sizing results: Heat transfer areas 250 °C 150 °C 350 °C Increasing heat-source temperature  Increasing system size  Increased HTA

White et al., ORC2017 13 – 15th September Component sizing results: Heat transfer areas 250 °C 150 °C 350 °C Maximum power output Highest heat-transfer area requirements

White et al., ORC2017 13 – 15th September Component sizing results: 250 ° C, n- alkane n -hexane n -butane n -pentane C n = 6 C n = 4 C n = 5

White et al., ORC2017 13 – 15th September Component sizing results: 250 ° C, n- alkane n -hexane n -butane n -pentane C n = 6 C n = 4 C n = 5  Minimise two-phase heat transfer Maximise evaporation pressure  Minimise vapour heat transfer Minimise superheating  Small temperature differences Pinch at preheater inlet Maximise power output Maximum heat-transfer area

White et al., ORC2017 13 – 15th September Component sizing results: 250 ° C, n- alkane n -hexane n -butane n -pentane C n = 6 C n = 4 C n = 5  Minimise two-phase heat transfer Maximise evaporation pressure  Larger superheater but high Δ T More superheating required  Small temperature differences Pinch at preheater inlet 16% reduction in power output 16% reduction in heat-transfer area

White et al., ORC2017 13 – 15th September Component sizing results: 250 ° C, n- alkane n -hexane n -butane n -pentane C n = 6 C n = 4 C n = 5  More two-phase heat transfer Reduced evaporation pressure  No superheater required No superheating required  Higher temperature differences Not pinched at preheater inlet 13% reduction in power output 51% reduction in heat-transfer area

White et al., ORC2017 13 – 15th September Thermoeconomic results 250 °C 150 °C 350 °C Increasing heat-source temperature  Increasing system size  Reduced SIC

White et al., ORC2017 13 – 15th September Thermoeconomic results 250 °C 150 °C 350 °C 2-pentene 2-heptene isobutane 4.03 £/W 2.22 £/W 1.84 £/W

White et al., ORC2017 13 – 15th September Thermoeconomic results 250 °C 150 °C 350 °C 2-pentene 2-heptene isobutane ↓ 𝑿 ↓ 𝑿 ↓ 𝑿 𝐨 = 2.3% 𝐨 = 4.9% 𝐨 = 0% 4.03 £/W 2.22 £/W 1.84 £/W Minimising SIC can identify different optimal working fluids