Design of Raceway Ponds for Algae Biomass Production using ...€¦ · Design of Raceway Ponds for Algae Biomass Production using Produced Water October 15, 2014 Soumya Yadala, Selen

Design of Raceway Ponds for Algae Biomass Production using

Produced Water

October 15, 2014

Soumya Yadala,Selen Cremaschi, PhDThe University of Tulsa

2014 International Petroleum Environmental ConferenceHouston, TX

October 14-16,2014

2

Presentation outlineAlgae based-Biodiesel

Algae oil Production

Research Objective

Soumya Yadala, Selen Cremaschi 2014 IPEC

Results

Mathematical Modeling

Future directions

Questions?

3

Motivation – Produced waterIntroduction Application Methodology Results Conclusion

� Salty water trapped in the reservoir rock and brought up along with oil or gas during production

� It can contain very minor amounts of chemicals, oil, and metals

� These waters exist under high pressures and temperatures

� Every year in the United States about 800 billion gallons of produced water is brought


� Scientists recently were successful in conducting the first pilot-scale test of algae growth using water from an oil-production well in Jal, New Mexico

� However, these large quantities of saline water have great potential value for algal biofuel production

� Every year in the United States about 800 billion gallons of produced water is brought to the surface along with oil and gas and about 98% of this water is routinely disposed as a waste product

4

Advantages

Higher growth rates & productivities

CO2 capture

Introduction Application Methodology Results Conclusion


Higher oil yieldAlgae oil

Grown on non-arable land and using produced water

No sulfur, non-toxic & biodegradable

Food vs. fuel

5

Challenges

High capital, operating & production costs



Algae biofuel

Difficulty in scaling up

Variety of algae strains

Lack of optimal design of cultivation systems

Relatively new technology

6

Algae oil Production

Selection of Algae Species

Selection of Location

Algae Cultivation

Varying oil content and specific growth rates

Influences climatic conditions and sunlight



Cultivation

Harvesting

Drying

Extraction

7

Research Objective

� Find a suitable algaespecies for cultivation

� Find the most suitable location to cultivate the selected algae strain

� Design an optimal cultivation



� Design an optimal cultivation system depending on the species and location selected

� The purpose of the study is to design a cultivation system that suits an algae species when cultivated at a selected location

8

Optimization

Optimization focuses on finding the best solution from a set of availablealternatives subject to constraints.

AlternativesAlternatives Objective FunctionObjective Function

Decision VariablesDecision Variables ConstraintsConstraints

OptimizationOptimization

To minimize the cultivation costs of algae oil by designing optimal cultivation systems



CW = Channel width

length = Pond length

p = Channel length

q = Pond width

CD = Pond depth

Raceway Pond Cultivation TechnologyVariablesVariables ConstraintsConstraints

9

AlternativesResults ConclusionIntroduction

� Small capital investment� Free solar energy� Easy maintenance� Lower energy requirements

Variation




MethodologyApplication


P.Tricornutum I.GalbanaAlgae strain

Cultivation Raceway Ponds

Tulsa Hyderabad Cape Town Rio de JaneiroLocation� Latitude� Longitude� Sunlight

� Growth rate� Oil content� Productivity

10

Decision VariablesMethodologyApplication Results ConclusionIntroduction




Physical Properties

Culture Properties


Design Properties

11

Formulation



OptimizationOptimization ( )∑=

+++

++

++=

10

0nn

eCtMaintenanc

ChemicalCtNutrientCt

LaborCtWaterCtElecticCt

MARR11

CpCtZMin

1%2%

3%1%

1% 0%5%

1% Site Preparation

Pond levees

Capital Costs Operating Costs

MethodologyApplication Results ConclusionIntroduction


3%4%

8%

70%

3%1% 1%

5% Pond levees

Paddle wheel

Harvesting

Flocculation

Extraction

Water & nutrient supply

Waste treatment

Buildings, roads, drainage

Electric Supply and distribution

Instumentation and machinery

Engineering and contingency

Land

18%

19%

44%

4% 12%

3% Nutrients

Chemicals

Labor

Maintenance and repair

Operating supplies

Taxes and insurance

12

Formulation




0Xi t

ti, =∑ ∑ Mass balance constraint

Extraction nodeDrying nodeThickening nodeConcentration node

p

f io

f g k f gb

aGrowth node

Pond

f g h

8768764484476 wastewateraewaterinaaedrya

cgfea OjHiOOhHPNOHCgNcPObHaCO 22

lg

2

lg

22 +++→+++


tons/year1000=∑t

talgaeoil,X Algae oil demand constraint

lkout j iou

t

o

Harvesting nodes

c

d

Pond

e

a = carbondioxide inletb = water inletc = nitrogen inletd = phosphorous inlete = oxygen outlet

f = dry algae outletg = water in algae outleth = waste water outletk = waste water remainKout = waste water remain removed

l = waste water removedi = water in algae remainIout = water remain in algae removedj = water in algae removedo = lipidp = cake

13

Formulation



OptimizationOptimizationm/s0.30 Um/s 0.15

davg ≤≤

m 1CDm0.10 ≤≤m10 CW ≤

Bound constraints

kg/l10 BC td, ≤

Location relating constraints

=)cos(θ

CDCD

tl,eq tl,

θCD

θ

CDeq


td,td,td, BCµPrV ×= Constraint relating productivity and algae species


)cos(θ tl,

××−×

=××−

tl,seq

)BCKa(CD

Oavg BCKaCD

]e[1II

tl,

tl,stl,eq

l

tl, CDeq BC

IO Ka

+×

= navg

nk

navgmax

td,

td,s

td,td,

II

Iµµ

td,pond

td,

TB

max eAµ××=

Relationship b/w culture properties (species) & location

14

Formulation

( ) icvevaspsurrpondtout, QQQQQQTTCpm +++++=−××& Energy balance constraint

VPrVX tl,tdryalgae, ×=

staedryatWIA

taedrya

XX

X%100

,lg,

,lg =×+

ρBC

XX

t

tdryalgae,tWW, ×

=

Relationship b/w culture properties, algae species &pond geometry


SATσεQ 4pondwp tt

×××−=

( ) SAIof1Q tast××−=

SATσεεQ 4surrawa tt

××××=

SALmeQ wtev t××−=

( ) SATThQtttt pondsurrcvcv ×−×=

( ) tWW,recycletWIA,ti Xη1XSAmeQt

×−++×=

( )tttttttt icvevaspsurrpondtout, QQQQQQTTCpm +++++=−××& Energy balance constraint


15

Formulation

34

h

22avg

F

D

lengthRCUh d

××=

g2

UKh

2avg

kd

××

= KFT h2hh ×+=

( )

−++×= ∑∑ ∑∑ ∑∑ td,WW,recycletd,WIA,td, Xη1XSAme

1Adwater Water Constraint

PW

Ttd,out,td,

η

hgmPP

××=

& ( ) ( )[ ] ( )332

2td,WW,recycletd,WIA,td,

td, CWCDρ

CWCD2lengthµXη1XSAme2PW

××+×××××−++××

=

Power Constraints


( )

−++×= ∑∑ ∑∑ ∑∑d t d t d t

td,WW,recycletd,WIA,td, Xη1XSAmeρ

Adwater Water Constraint



OptimizationOptimization GAMS(General Algebraic Modeling System) CONOPT


40CWlength ×= CW2q ×= qp4πq

SA2

×+= CDSAV ×=

Design Constraints

tavg

tout,

UCDρ

mCW

××=

&

16

ResultsApplication Methodology Results ConclusionIntroduction

Raceway Pond

P.Tricornutum I.Galbana

Tulsa Hyderabad Cape Town Rio de Janeiro

67%

22%

0%

3%3% 5%

Production Costs

Zraceway

Zwater

ZelectricPW

ZNutrients

ZChemicals

Zlabor


Total cost of producing about 1000 tons/year of algae oil = $ 0.062 per gallon

Z ($)Depth

(m)Width

(m)Length

(m)V (m3) SA (m 2)

Iavg (µE m-2

s-1)Uavg (m

s-1)BC (g l -1) µ (h -1)

PrV (g m -

3 h-1)Tpond (C)

1 275,383 0.103 5.45 217.92 242 2349 43 0.108 5.24 0.324 2381 212345678

183,454347,304236,427423,761227,540662,802341,389

0.1050.1040.1000.1000.1000.1180.100

4.076.294.957.084.739.076.22

162.80251.46198.01283.10189.15362.75248.96

138326194396177770307

1311312819393964177065093066

44454256516152

0.1090.1040.1040.1330.1440.1220.134

7.264.595.894.296.743.074.90

0.4780.2780.3890.3340.6020.2510.438

4185177129742148481111062777

28192621281926

17

ResultsApplication Methodology Results ConclusionIntroduction


18

Sensitivity AnalysisApplication Methodology Results ConclusionIntroduction

Z ($) Depth (m)Width

(m)Length

(m)V (m3) SA (m 2)

Iavg (µE m-

2 s-1)Uavg (m s -

1)BC (g l -1) µ (h -1)

PrV (g m -3

h-1 Tpond (C)

29

183,454198,838

0.1050.300

4.074.20

162.80167.91

138418

13111395

4426

0.1090.100

7.264.65

0.4780.265

41851379

2829

10 213,816 0.500 4.33 173.25 742 1485 20 0.100 3.70 0.198 777 29

Width Length I (µE m- Uavg (m s - PrV (g m -3

Sensitivity Analysis -1 (Variation in pond depth)

Sensitivity Analysis -2 (Variation in recycle effic iency)



(m)Length

(m)V (m3) SA (m 2)

Iavg (µE m-

2 s-1)Uavg (m s -

1)BC (g l -1) µ (h -1)

PrV (g m -3

h-1 Tpond (C)

1112

424,689298,429

0.1000.100

4.144.13

165.40165.22

135135

13531350

3838

0.1110.111

10.010.0

0.4260.427

42624272

2828

2 183,454 0.105 4.07 162.80 138 1311 44 0.109 7.26 0.478 4185 28


(m)Length

(m)V (m3) SA (m 2)

Iavg (µE m-

2 s-1)Uavg (m s -

1)BC (g l -1) µ (h -1)

PrV (g m -3

h-1 Tpond (C)

132

183,319183,454

0.1050.105

5.794.07

115.72162.80

137138

13101311

4444

0.1000.109

7.267.26

0.4790.478

41984185

2828

14 183,585 0.105 3.32 199.06 138 1311 43 0.119 7.26 0.477 4171 28

Sensitivity Analysis -3 (Variation in length/width ratio)

19

ConclusionsApplication Methodology Results ConclusionIntroduction

� A mathematical framework is developed to estimate the best combination of algae species, geographical location, and raceway pond geometry by combining experimentally validated temperature, irradiance, and algae growth models with optimization

� In order to represent the actual behavior of the outdoor raceway pond, the current model takes into account the diurnal pattern of sunlight, temperature fluctuations, the dynamic behavior of solar zenith angle, and mixing which makes it more realistic compared to the other models in the literature


� Model the dynamic behavior of algae biomass cultivation and biodiesel production using HYSYS simulation software

� Model the network flow topology of algae oil distribution in the United states

Future directions

it more realistic compared to the other models in the literature

� This method enables to record the change in culture properties such as biomass concentration, productivity, and growth rate over time

20

AcknowledgementMethodology Application Results ConclusionIntroduction

� Department of Chemical Engineering, The University of Tulsa

� TUPSE Research Group


THANK YOU

Total cost of producing about 10,000 gallons/day of biodiesel = $0.062/gallon

October 15, 2014


Questions???

Documents

Design of Raceway Ponds for Algae Biomass Production using ...€¦ · Design of Raceway Ponds for Algae Biomass Production using Produced Water October 15, 2014 Soumya Yadala, Selen