1. HKUST EVNG Seminar series

2. o ptimum Biomass Drying for Combustion – A Modeling Approach
Tesfaldet G
tgaa@ust.hk
March-11-2013

4. Contents
• Biomass Types
• Biomass to Energy Routes
• Biomass drying for heating value Enhancement-Modeling
and optimization
• Results
• Discussions
• Future work

5. Biomass Types
• Not limited to woody biomass and crops .
• Includes some organic wastes with high moisture contents
like sludge ,microalgae and etc .

6. Biomass to Energy Routes
•While biomass with moisture levels of 55 - 65wt% can sustain
combustion, the optimum moisture content is 10wt% - 15wt%.
http://www.toyo-eng.co.jp/en/product_line/environment/baiomass/index.html

7. Why Drying?
• Burning biomass with high moisture content :
• reduces the combustion temperature
• incomplete combustion
• undesirable reaction products
• requires a large amount of auxiliary fuel to make it combustible
• Drying of biomass:
– Can increase the combustion efficiency, reduce pollution and improve
operation.
• BUT
– Drying of biomass is an expensive process that requires huge capital
investment and energy input.
• Therefore ,the level of drying should be optimized.

8. Biomass Drying for combustion-Modeling
GOAL
• To develop a validated model of the drying kinetics of solids
like wood, solid wastes and sludge for heating value
enhancement before combustion process.
• To use the model to analyze the drying time , moisture removal
rate ,Energy requirement and design parameters for practical
drying of solids.
How?
• Material and energy balances, heat transfer and drying kinetics.

9. Drying process
• Regardless of drying particle shape, there exists simultaneous
heat and mass transport.

10. Drying…..
Solid in
Heat
source?
Air in Heater Hot air Exit air
Solid out
Air •TGA………………..…☑
•Temperature ……☑ •TG-DSC……………. ☒
•Humidity ………….☑ •Dryer Type …....…☒
•Velocity ……………☒ •Drying models……☒

11. Things to do
Air Heater
• Mathematical model- Psychometric analysis
Dryer
• Drying kinetics models-
• Experiment-Thermogravimetric analysis (TGA)
• Sample (Type, shape, moisture content)
Product value
• Heating value enhancement.

12. Air heater
• The corresponding property change of air for moisture removal
from the solid is calculated by making use of psychometric
relations (equations).
• The air heater cost was determined for the required air property
change.

13. Dryer
• For sizing the dryer as well as determining the level of the
drying, it is important to obtain the drying kinetics of
which the drying rate inside the dryer is calculated.

14. Drying Kinetics models
• General forms:
1. Diffusion based model….Fick’s Diffusion Equation
2. Thin layer drying curve based models (log, modified log)

15. L
Fick’s Diffusion Equation
rc
rs

16. Experimental Drying kinetics determination
• The moisture ratio is determined using TGA.
1
0.9
0.8
0.7
Moisture Ratio
0.6 60°C
0.5 70°C
0.4 80°C
0.3 90°C
0.2
0.1
0
0 100 200 300 400 500 600
Drying Time (sec)
-20.2
-20.3 lnDeff
-20.4
-20.5
ln(Deff)
-20.6
-20.7
-20.8 y = -2045.x - 14.71
R² = 0.936
-20.9
0.0027 0.0028 0.0029 0.003 0.0031
1/T

17. The product value
• Monetary value gained upon drying.

18. Over all process

19. Objective Function
• Maximizing the net annual profit (AP) of the process
represented by :
AP= Product value- (Heater cost +Dryer cost+ Operating Cost)
• Operating cost=Steam cost
Constraints
1. Air preheated temperature, 60oC Ta,2 110oC
2. Relative Humidity of the exhaust air, RH3 60%
3. The LHV of the final product, LHV 15MJ/Kg
4. Residence time > 100sec
• Solver
• Standard GRG Non-linear Solver-Excel.

20. Design parameters
Parameters Value
Feed rate of wood chips, Ws,1 (Kg/hr) 5000
Moisture ratio of the wood feed, X1 1
Temperature of the wood feed, Ts,2 ( C) 25
Pressure of the air feed, Pa,1 1atm or 101325Pa
Temperature of the air feed, Ta,1 ( C) 25
Relative Humidity of the air feed, RH1 (%) 50
Temperature difference of air and solid at the dryer outlet, DT ( C) 5
Air heater Cost, Chtr ($/yr) 500 + 100 A 0.8
Dryer Cost , Cdyr ($/yr) 5000 + 5000 V 0.6
Steam Cost, CLP ($/kW) 0.1
Heat value of wood ($/kW) 0.05
Specific Heat of Air, Cpda( kJ/kg-C) 1.006
Specific Heat of Wood, Cpds, (kJ/kg) 1.2566
Specific Heat of Water Vapor, Cpv , (kJ/kg-C 1.89
Specific Heat of Water, Cpw, (kJ/kg-C) 4.186
Latent Heat of Water, LHw, (kJ/kg-C) 2270
Latent heat of LP steam, LHLP (KJ/Kg) 1999
Size of the wood , L, (m) 0.0005
Annual operation time, top (hrs) 2000

21. Results
Base Case/1 Case 2 Case 3 Case 4 (L=0.05m)
(L=0.0005m) (L=0.005m ) (L=0.05m)
Moisture content of the dried wood, X3 (wt %) 17 17 17 43
LHV of the dried wood, LHVs (KJ/kg) 15000 15000 15000 9698
Solid residence time, t (hr) 0.11 8 247 0.03
Air feed rate, Wa,1 (kg/hr) 179,496 83,358 158,187 59,842
Air preheated temperature, Ta,2 (°C) 62 97 107 60
Air Exhausted Temperature Ta,3 (°C) 35 43 78 35
Heater Cost ($/yr) 50,250 71,138 160,818 21,161
Dryer Cost ($/yr) 21,495 219,008 1,700,822 12,237
Energy Cost ($/yr) 357,913 353,818 766,027 119,324
Product Value ($/yr) 1,260,453 1,260,453 1,260,453 1,172,979
Annual Profit ($/Yr) 830,795 616,489 -1,367,214 1,020,258

22. Discussion
• The optimum solutions indicated that the size of the wood chips
strongly affects the economy.
• When the size of the wood chips become too large, the drying time
becomes too long thus significantly increases the dryer size and
energy cost.
• Another observation is that if a lower heating value of the dried
wood chips is acceptable, the profitability is resumed.
• in order to satisfy the constraint of minimum heating value without
upsetting the environment and/or operation of the combustion
process when drying too large or too wet biomass, auxiliary fuel is
one of the options to be considered.

24. Research on pipe line,,,,,,
Differential Scanning Calorimetry
(DSC)
-Exactly we can predict heat flow!

25. Thank you
Go green!