PSE Challenges in Solar Research CAPD Review Sunday March 6, 2011 B. Erik Ydstie

Transcription

1 PSE Challenges in Solar Research CAPD Review Sunday March 6, 2011 B. Erik Ydstie Solar grade silicon Float Process for Silicon Wafers Dye Sensitized Solar cells Solar and wind on the Grid (J. Du) (G. Oliveros (R. Panella (J. Liu) 1

2 Supply Chain for Silicon Solar Cells 50% of system cost PV System = Solar cell module + Balance of system (BOS) 30% of module cost Crystalline silicon Wafer production Solar-grade silicon Cell fabrication REC Silicon, Moses Lake, WA Fluidized Bed Si Production: Pilot plant Demonstration scale 2008 Commercial scale Aim: $20/kg $40-60/kg IC supply chain Metallurgical grade silicon SiCl 3 H distillation Decomposition Crystallization Wafer Integrated circuit $3-5/kg $40-60/kg 2

3 Supply Chain for Silicon Solar Cells 50% of system cost PV System = Solar cell module + Balance of system (BOS) 30% of module cost Crystalline silicon Wafer production Solar-grade silicon Cell fabrication REC Silicon, Moses Lake, WA Fluidized Bed Si Production: Pilot plant Demonstration scale 2008 Commercial scale Aim: $20/kg $40-60/kg IC supply chain Metallurgical grade silicon SiCl 3 H distillation Decomposition Crystallization Wafer Integrated circuit $3-5/kg $40-60/kg 3

4 The proposed solution Design and Control of Solar Silicon FBR processfrom Silane to Solar Silicon Ron Reis REC Silicon, Paul Ege Reactech 2 PhD students Si powder H 2 increase throughput Reduce energy cost H E A T H E A T SiH 4 H 2 Si Fluid Bed Reactor Continuous Process Large surface area 650 C Goal: develop scale-up and control models to optimize granular yield and control particle size.

5 Multi-scale model paradigm Multi-scale Modeling Approach Population balance Particle size Granular yield Plug flow reactor Dust Yield loss Bed temperature Bed density Computational fluid dynamics Particles are wellmixed Gas and powder are plug flow Control fluidization regime Integrate over time for particle size distribution Integrate over height for granular yield Operation challenges Fast dynamics fluidization, reaction Slow dynamics particle size distribution Distributed parameters Particle size distribution Chemical reaction, yield loss Bed fluidization Simulate to obtain model input

6 Momentum CFD model and for energy fluidization balance modeled using Fluent and COMSOL multi-physics Solid phase is well mixed Gas phase exhibits pressure gradients concentration gradients temperature gradients 6

7 Model Verification using Pilot Plant Data Time constant for particle size distribution about 50 hours. Weak control of distribution function Difficult to control yield loss (sensitive system) 7

8 Model Validation and Scale-up Scale-up models: from pilot to demonstration plant Y-Yield S-silane feedrate D- average diameter(p - product, s-feed) n- particle feedrate (p -product, s-feed) Full Scale Production on Moses Lake in 2009

9 Summary Multi-scale modeling Captures physics of system (CFD, Chemistry, Population balance) Useful for scale-up and design Predicts process dynamics Natural Discretization of population balance New closure relation Stability and control (Juan Du) REC Silicon's $970 million expansion project in Moses Lake houses 24 fluid bed reactors to produce 6,500 metric tons of polysilicon per year Acknowledgements Christy s Thesis has been sold from the library Ground Breaking August 2006 Mar Sept NSF Graduate Research Fellowship Program REC Silicon Reactech Process Development Inc. Production Nov. 2009

10 Silicon Wafers using Float Process Current methods are carried out in batch Continuous processes yield inferior product Single crystalline 18-20% Multi-crystalline 14-16% EGF etc 10-14% Edge-Defined Film Fed Growth (EFG) Shaping die Silicon sheet Crystal growth Ribbon pulling Silicon melt Substrate 10

11 The Pilkington float Glass Process Replaced the drawn glass process in 1960ies High throughput Low cost (capital and opearting) Very high quality glass In line processing is possible (CVD) 11

12 Float Process for Silicon Wafers NSF and PA Nano grants to study crystallization fluid flow and heat flow process scale-up and detailed design process control commercialization 12

13 Stability of Float Process for Silicon Wafers Theory: Stability and process modeling Experiments: Water models 13

14 Power System Frequency Control Wind power fluctuations frequency deviation from 60Hz. Conventional generation or storage compensates wind power variations. Decentralized robust control for conventional generators Need for decentralized approaches for stability analysis and design Our Approach: Use thermodynamic stability analysis (entropy as Lyapunov function ) 14