Coal to biomass (wood pellet) mill conversion

Transcription

1 Coal to biomass (wood pellet) mill conversion presented by Corniel Zwaan Coal Milling Projects STAR Global Conference, Berlin 2017

2 Company background CMP is a South African company and was formed in December Celebrating 20 years this year. The company consists of three departments namely: Design and CAD department. Manufacturing and refurbishing department. Maintenance department. License agreements: Southwestern Corporation USA Merrick Feeders USA Synergy Australia Patented technologies: Version 1 to 6 rotating throats (vane wheels, port rings or nozzle rings). Ultra high performance static classifiers (UHPSC). Static modified air re-entrainment technology (SMART) for Low NOx purposes. High ash coal de-sanding technology to remove abrasive materials from coal. Coal to biomass mill conversion classifier.

3 Company background CMP s design department started to use in 2008 as CAE software to do computational fluid dynamic analysis (CFD) and discreet element modelling (DEM). Since May 2014, CMP have a full time design engineer that uses to do CFD and DEM in house. 9 years using

4 Company background

5 Presentation content Project background Project outcomes CFD setup Geometry Computational mesh Physics Results Lagrangian Multiphase CFD compared to site tests How CFD helped the milling industry Questions

6 Project background Drax Power Station (UK) approached CMP to help convert their Babcock 10 E vertical spindle mills from coal to biomass equivalents MW Power station (6 Units) Replacing coal with biomass pellets as primary energy source. The mill is used to break up the pellet into its primary shape called a flake. Ultimately replacing coal which is a carbon accumulator, with biomass, a carbon neutral, to help reduce CO₂ emissions.

7 Project background The modifications imposed before our involvement had the following issues: Could not get the mill throughput up (maximum load required) Settling of biomass material in one of the production pipes. The accumulative settling effect blocked the pipes causing uneven distribution to the burners. Due to material settling, they continuously need to open the mill to clear the blockages. The mill primary air (PA) fan continuously trips on high amp-alarm. The mill was not able to run on auto operation.

8 Project background

9 Project outcomes All biomass flakes (broken pellets) must pass to the burners. No passing of biomass pellets to the burners. No reject of biomass material into the mill reject boxes Increased throughput to accommodate lower calorific value of biomass. Equal fuel distribution to the burners. Static classifier design. Use most of the existing mill components (i.e. the primary air fan) Easy to manufacture and maintain.

10 Biomass with a coal classifier?

11 CFD Setup Geometry PA inlet PA ducting Biomass classifier Biomass feed pipe Loading cylinders Loading ring Grinding elements Biomass build up (bed) CMP v 4 port ring Mill table Plenum chamber

12 CFD Setup Geometry

13 CFD Setup Computational mesh 10.7 million polyhedral cells Volume refinement in areas with high gradients. High Y+ (2 layer) prism layer to solve the boundary layer. Extruded mesh on production pipe outlet generating a separate region to incorporate mill back pressure effects.

14 CFD Setup Physics Steady state analysis Reynolds stress model (RSM) to solve turbulence Energy extraction field function, used in a cell set, to simulate heat losses due to conduction and moisture driven off. Extruded region on pipe outlets, set with desired porous inertial resistances to simulate wind-box back pressures. Operating Data Value Units PA flow rate kg/s PA inlet temp 170 ᵒC Mill outlet temp 87 ᵒC Barometric pressure (Ermelo) kpa

15 CFD Setup Results mill temperature

16 CFD Setup Results mill velocities

17 CFD Setup Results mill velocities 0

18 CFD Setup Results mill pressure With just replacing the existing port ring with a CMP version 4, the system resistances came down with 30 %.

19 P2 P1 Drag Coefficient CFD Setup Lagrangian Multiphase Calibration Drag Force = 1 2 ρv2 C D Area 1000 Drag coefficient data for a sphere vs. a square prism SN (Sphere) Stoke's Law Square Prism (Experimental Data) Square Formula Gravity Force = mass g Reynold's Number P3

20 CFD Setup Lagrangian Multiphase particle size distribution Flake specification Flake to sphere Height/Thickn ess (mm) Length = Width (mm) Dh (mm) Diameter (mm) Length (mm) Dh (mm) Pellet to sphere

21 CFD Setup Lagrangian Multiphase setup Pellet injection plane Flake injection plane Biomass material passed plane Value Units Number of flake injectors 14 # Number of pellet injectors 6 # Particles per injector 300 # Density of biomass 700 kg/m³ Track time 30 Seconds

22 CFD Setup Lagrangian Multiphase flakes animation

23 CFD Setup Lagrangian Multiphase pellets animation

24 CFD Setup Lagrangian Multiphase pellets and flakes animation

25 CFD Setup Lagrangian Multiphase flakes in pipes animation

26 Percentage of injected particles passing to burners, % CFD Setup Lagrangian Multiphase biomass passing % Particle Size Passed 90.00% 80.00% 70.00% 60.00% 50.00% 40.00% 30.00% 20.00% 10.00% 0.00% Particle Size, hudraulic diameter (µm) Flakes passing Pellets passing

27 CFD Setup CFD compared to site tests Pipe 2 Pipe 1 Mill load (Tons/h) Pipe split (%) Pipe 1 Pipe % 52 % CFD maximum load run (incident mass flux % 50.95% run) Pipe 1 and 2 temp were within 0.5 C indicating no settling (on site test). System resistance (mill differential pressure) reduced with 50 % (confirmed on site).

28 How CFD helped the milling industry Accurately predict Eddy Accurately currents predict that might wear patterns lead to particle suspension

29 How CFD helped the milling industry Optimise patented technology

30 Conclusions STAR-CCM+ played an integrate role in the design process of the biomass classifier. The ability to incorporate field functions determined from calibration experiments etc. STAR-CCM+ identified areas of focus to help overcome problems that will not be able to be solved with conventional design methodologies. The CFD model correlated well with on site results and this ultimately led to solving the distribution problems at Drax. With the help of STAR-CCM+ we managed to solve all the outcomes of this project and the mill was able to run on auto for the first time. The STAR-CCM+ software is a platform where a set CFD methodology for mills can be applied and still correlate well with conventional design methodologies and on site test results. Ultimately, STAR-CCM+ helped to understand mills better Help solve real-world engineering problems. Complex Multiphysics solution

31 Any questions? Thank you Tel: Website: