Model Predictive Control for Optimum Algal Growth

271 Pages·2015·3.95 MB·English

by  Ankita Juneja

AN ABSTRACT OF THE DISSERTATION OF

Ankita Juneja for the degree of Doctor of Philosophy in Biological and Ecological
Engineering presented on July 10, 2015.

Title: Model Predictive Control for Optimum Algal Growth

Abstract approved:
______________________________________________________
Ganti S. Murthy

Microalgae has been under careful consideration as a sustainable feedstock for
renewable fuel recently due to its year round production with high energy yields per unit
area, reduced need for arable land, water treatment benefits with nutrient cycling, and
minimal competition with the food industry. Despite of all these advantages,
commercialization of algal biofuels still lacks economic viability, mainly because of
lower productivities and higher cost of harvesting and processing of algae.
Photobioreactors are able to provide high yields of algae but they suffer from limitation
of high initial cost, whereas growth in low-cost open ponds are highly affected by
external factors such as ambient temperature, light availability and contamination with
other micro-organisms. These external factors inhibit a consistent growth, which
consequently reduces the final productivity of algae. There is an imminent need to find a
solution that can take into account the objectives of maximum productivity with
minimum economic and environmental effects. The focus of this dissertation was to
design, implement and validate a model predictive control which can assure optimum
algal growth and productivity, even under the effect of disturbances. The dissertation was
divided into four studies, each of which concentrates on developing different models to
be integrated in the design of the model predictive controller.
In the first study, a compartmentalized genome scale metabolic network was
reconstructed for C. variabilis to offer insight into various metabolic potentials from this
alga. The model iAJ526 was reconstructed with 1455 reactions, metabolites and 526
genes. 21% of the reactions were transport reactions and about 81% of the total reactions
were associated with enzymes. Model was able to simulate experimental batch growth
conditions with fair agreement under three light conditions. The discrepancy in
experimental and model results was attributed to the incapability of the model to capture
kinetics of growth, including substrate inhibition and photoinhibition. Cumulative
wavelengths around 437 nm, 673 nm and 680 nm in the model were observed to be 100%
efficient in their utilization.
The second study evaluated the economic viability and to estimate the energy use
and greenhouse gas (GHG) emissions during life cycle of renewable diesel (RD)
production from algae via hydrothermal liquefaction process. Hydrothermal liquefaction
is one such technology that converts the algae into high heating value bio-oil under
high temperature and pressure. RD yields for algae were estimated 10.19 ML/year unit
price of production as $1.75/L RD. Energy and emissions were calculated per functional
unit which was defined as 1000 MJ of available energy in fuel at the pump. Fossil
energies were calculated as 241.6MJ to produce one functional unit of RD from algae.
The GHG emissions during life cycle of RD production were found to be 6.2 times
less than those produced for 1000MJ of conventional diesel.
In the third project, Monod’s multiplicative kinetic model for Chlorella vulgaris,
one of the most robust algal strains for outdoor growth, was developed with limiting
nitrate and CO . The specific growth rate calculated from the growth profiles was 0.0196
2
hr-1. The values of 𝜇 , 𝑘 , 𝑘 , 𝑘 , E and 𝑘 𝑎 were estimated as 0.23 hr-1, 26.53 mg/l,
𝑚𝑎𝑥 𝑁 𝐶 𝑑 a 𝐿
7.64 mg/l, 0.08hr-1, 3.69 J/mol and 0.24 hr-1. The yield coefficient for nitrate (𝑌 ) and
𝑋⁄
𝑁
CO (𝑌 ) for C. vulgaris were calculated as 2.86 and 1.96 respectively. Validation
2 𝑋⁄
𝐶
experiments proved the kinetic model to be robust under vast range of initial biomass and
nitrate concentrations.
The kinetic model developed, formed the basis of the model predictive control
(MPC) designed for optimum growth of algae, with an objective of maximizing
productivity and minimizing the total cost and GHG emissions. The MPC proved to be an
efficient tool that can help in a steady growth even under natural disturbances. The
growth of algae under the light and temperature disturbances tested was higher in the
reactor with MPC than the other reactor with no MPC. However, due to light limitation,
the growth with low light of 34W/m2 (simulating a cloudy day) in the MPC reactor was
not different form the other one with no MPC. This disturbance was considered outside
the realm of controller as the control variables or the manipulated variables were not able
to overcome light limitation. In absence of any disturbance, the growth in MPC reactor
was not statistically different form the no MPC reactor. This shows the importance of
MPC under conditions deviating from the optimum, which is a common case in real time
outdoor ponds.
©Copyright by Ankita Juneja
July 10, 2015
All Rights Reserved
Model Predictive Control for Optimum Algal Growth

by
Ankita Juneja

A DISSERTATION
submitted to
Oregon State University

in partial fulfillment of
the requirements for the
degree of

Doctor of Philosophy

Presented July 10, 2015
Commencement June 2016
Doctor of Philosophy dissertation of Ankita Juneja presented on July 10, 2015

APPROVED:

Major Professor, representing Biological and Ecological Engineering

Head of the Department of Biological and Ecological Engineering

Dean of the Graduate School

I understand that my dissertation will become part of the permanent collection of Oregon
State University libraries. My signature below authorizes release of my dissertation to
any reader upon request.

Ankita Juneja, Author
ACKNOWLEDGEMENTS
It gives me immense pleasure to express my earnest gratitude and indebtedness to
Dr. Ganti S. Murthy, my PhD advisor, for his judicious guidance, encouragement,
constructive criticism, patience and unlimited support throughout my studies at OSU. I
have benefited immensely under his guidance and I will always carry the knowledge he
has passed on to me.
I would like to thank Dr. Frank Chaplen, Dr. Vincent Remcho, and Dr. Christine
Kelly, for being the best committee ever possible in terms of their understanding and
willingness to help me whenever I needed and motivating me from time to time. Special
acknowledgments are due to my graduate council representative, Dr. Chad Higgins for
his enthusiasm and encouragement every time I met him.
I would also like to acknowledge Dr. Kim Halsey for always trying to help and
letting me use instruments from her lab for my research.
Next is the person whose contribution in my life is beyond words, my husband,
Deepak. He has always been a motivating and an encouraging friend, philosopher and a
mentor. I owe him for his patience with me during challenging personal and professional
times, for handling me delicately during my panic attacks and for encouraging me to
bring out my best in everything. I would like to thank my daughter, Aahana, to give me a
chance to enjoy motherhood and provide me with immense happiness and joy in my life.
I would like to thank my lab-mates friends for their co-operation and
encouragement during the course of study, especially Bill Hohenschuh, who has always
been there for any help I needed in the lab. A special thanks goes to my friend Saurabh
Saxena for always helping me out in the electrical components of my research.
I owe to my parents for being a huge support and source of inspiration for me till
date, and for always trying to keep me positive. Thanks to my brother Rahul Juneja for
always encouraging me to get through the challenging deeds. I would also like to thank
my parents and grand-parents-in-law for their support and motivation, and my brother-in-
law, Kharry for always lightening the stressed environment.
Finally, I express my gratefulness to the Almighty for showing me the path of life
and making me able to achieve whatever I have.
TABLE OF CONTENTS

Page
1. Introduction ........................................................................................................ 1
1.1 Microalgal Biomass Production .................................................................... 3
1.2 Harvesting of Algal Biomass ........................................................................ 5
1.3 Processing of Algae to Crude Oil ................................................................. 6
1.4 Efficient Algal Production System ............................................................... 7
2. Effects of Environmental Factors and Nutrient Availability on the
Biochemical Composition of Algae for Biofuel Production: A
Review. ............................................................................................................. 12
2.1 Abstract ....................................................................................................... 13
2.2 Introduction ................................................................................................. 14
2.2.1 Algae Production, Processing and Use .......................................... 17
2.2.2 Relevance of Individual Algal Cellular Components for
Biofuels Production ......................................................................... 20
2.3 Effect of Environmental Factors ................................................................. 22
2.3.1 Temperature .................................................................................... 23
2.3.2 Light ............................................................................................... 27
2.3.3 pH .................................................................................................... 31
2.3.4 Salinity ............................................................................................ 34
2.3.5 Nutrients ......................................................................................... 35
2.4 Intercations Among Environmental Factors .............................................. 42
2.5 Conclusions ................................................................................................ 45
2.5.1 Algae as a Sustainable Biofuel Source ........................................... 45
2.5.2 Future Outlook ............................................................................... 49
2.6 References .................................................................................................. 50
3. A Genome Scale Metabolic Reconstruction of Chlorella Variabilis
for Biofuel Production ..................................................................................... 68
3.1 Abstract ....................................................................................................... 69
3.2 Introduction ................................................................................................. 70
TABLE OF CONTENTS (Continued)

3.3 Methods ....................................................................................................... 72
3.3.1 Reconstruction Methodology .......................................................... 72
3.3.2 Biomass Equation ............................................................................ 77
3.3.3 Light Sources ................................................................................... 77
3.3.4 Constraint Based Modeling ............................................................. 78
3.3.5 Experimental Validation ................................................................. 79
3.4 Results and Discussion ................................................................................ 80
3.4.1 Genome Scale Metabolic Reconstruction ....................................... 80
3.4.2 Biomass Equation ............................................................................ 86
3.4.3 Systemic Properties of model .......................................................... 88
3.4.4 Phenotypic Phase Planes ................................................................. 91
3.4.5 Flux Balance Analysis (FBA) ......................................................... 91
3.4.6 Growth Experiments ....................................................................... 94
3.5 Conclusion .................................................................................................. 97
3.6 Acknowledgements ..................................................................................... 97
3.7 References ................................................................................................... 97
4. Techno-economic Analysis and Life Cycle Assessment of Renewable
Diesel Production from Microalgae via Hydrothermal Liquefaction
Process ............................................................................................................ 102
4.1 Abstract ..................................................................................................... 103
4.2 Introduction ............................................................................................... 104
4.2.1 Hydrothermal Liquefaction .......................................................... 105
4.2.2 Techno-Economic Analysis and Life Cycle Assessment ............. 106
4.3 Materials and Methods .............................................................................. 107
4.3.1 Algae Strain .................................................................................. 107
4.3.2 Techno-Economic Analysis ......................................................... 107
4.3.2.1 Assumptions for process modeling ........................................ 108
4.3.2.1.1 Technical assumptions ................................................. 108
4.3.2.1.2 Economic assumptions ................................................ 109
TABLE OF CONTENTS (Continued)

4.3.2.2 Algae cultivation .................................................................... 110
4.3.2.3 Algae harvesting ..................................................................... 113
4.3.2.4 Bio-Crude production .............................................................. 114
4.3.2.5 Hydrothermal gasification ...................................................... 115
4.3.2.6 Hydrotreating of HTL biocrude ............................................... 116
4.3.3 Life Cycle Analysis ...................................................................... 117
4.3.3.1 Goal definition and scoping ..................................................... 117
4.3.3.2 Process description ................................................................. 117
4.4 Results and discussion ............................................................................. 119
4.4.1 Process Economics ....................................................................... 119
4.4.1.1 Sensitivity analysis .................................................................. 123
4.4.1.2 Renewable diesel price ............................................................ 125
4.4.2 Life Cycle Energy Use .................................................................. 126
4.4.3 GHG Emissions ............................................................................ 128
4.5 Conclusion ............................................................................................... 130
4.6 References ................................................................................................ 131
5. Modeling the Growth and Nutrient Uptake of Green Microalga
Chlorella Vulgaris ......................................................................................... 135
5.1 Abstract .................................................................................................... 136
5.2 Introduction .............................................................................................. 137
5.3 Materials and Methods ............................................................................. 140
5.3.1 Effect of Temperature on Growth Rate ......................................... 140
5.3.2 Measurement of Mass Transfer Co-efficient (kLa) ....................... 141
5.3.3 Growth Experiments .................................................................... 142
5.3.4 Model Equations .......................................................................... 142
5.3.5 Validation Experiments ................................................................. 144
5.4 Results and Discussion ............................................................................. 144
5.4.1 Temperature Dependent Growth ................................................... 144
5.4.2 Calculation of Mass Transfer Coefficient ..................................... 146