Global optimization for sustainable design and synthesis of algae processing network for CO<sub>2</sub> mitigation and biofuel production using life cycle optimization

Gong, Jian; You, Fengqi

doi:10.1002/aic.14504

Cited by 130 publications

(107 citation statements)

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“…20 Pokoo-Aikins et al concluded algal biodiesel is competitive with food-based plant oil. 21 Additionally, much effort was also made on sustainable design and synthesis of thermochemical conversion system, [22][23][24][25][26][27] offering useful ideas for the integration of energy systems. Even with the above progress, there still lacks 4…”

Section: Introductionmentioning

confidence: 99%

Value-Added Chemicals from Microalgae: Greener, More Economical, or Both?

Gong

You

2014

ACS Sustainable Chem. Eng.

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111

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This paper addresses the sustainable design and synthesis of manufacturing processes for making algal bioproducts. We propose by far the most comprehensive superstructure capable of producing biodiesel, hydrogen, propylene glycol, glycerol-tert-butyl ether, and poly-3-hydroxybutyrate from microalgae. The major processing sections include cultivation, harvesting, lipid extraction, remnant treatment, biogas utilization, biofuel proneduction, and bioproduct manufacturing. Based on the superstructure, we integrate a cradle-to-gate life cycle analysis and techno-economic analysis with multiobjective optimization to simultaneously optimize the environmental and economic performance. We also apply a tailored global optimization algorithm to efficiently solve the problem in reasonable computation times. Results show that the most environmentally sustainable processes reduce life cycle greenhouse gas emissions per kilogram of the algal bioproducts by 5% to 63%, compared with petrochemical counterparts. In addition, the coproduction of value-added bioproducts in the algal glycerol process helps reduce the biodiesel production cost to as low as $2.79 per gasoline-gallon-equivalent. a complete superstructure which not only incorporates existing technologies for the conversion of algal biodiesel, but also takes advantage of the versatile glycerol and converts it on site to environmentally sustainable and value-added bioproducts. Process integration is an important method in sustainable process design to explore the possibilities of improving the overall process efficiency by utilizing waste streams and ultimately reduce the overall expenditure and environmental impacts of the entire process.Bioproduct manufacturing production has the potential for boosting the algal biodiesel performance by utilizing byproducts in transesterification and generating carbon dioxide feed for microalgae growth. The aim of the current work, therefore, is to explore the potential environmental and economic benefits for the production of both biodiesel and value-added bioproducts from microalgae.In order to bridge the research gap, we develop by far the most comprehensive superstructure, which is able to produce biodiesel and four types of bioproducts, including hydrogen, propylene glycol (PG), glycerol-tert-butyl ether (GE), and poly-3-hydroxybutyrate (PHB). In particular, the hydrogen can be produced by either steam reforming, autothermal reforming, or aqueous-phase reforming. The superstructure also includes a methanol synthesis process in the biogas utilization section. Additionally, we simulate the lipid extraction processes using hexane and n-butanol as extractants for data validation.Based on the proposed superstructure, a cradle-to-gate life cycle analysis (LCA) is performed to account for the life cycle greenhouse gas (GHG) emissions associated with three life cycle stages, namely feedstock acquisition, transportation, and algal biodiesel and bioproduct manufacturing. Following a life cycle optimization methodology, we further integrate the...

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Section: Introductionmentioning

confidence: 99%

Value-Added Chemicals from Microalgae: Greener, More Economical, or Both?

Gong

You

2014

ACS Sustainable Chem. Eng.

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111

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“…Compared to the aforementioned methods, multi-objective optimization schemes have a higher potential to obtain the optimal trade-off between conflicting economic and environmental objectives. For example, a global optimization method for sustainable design was developed, in which a large-scale algae processing network was simultaneously optimized in terms of minimizing the unit cost-and global warming potential-associated indicators [9]. Additionally, a multi-objective genetic algorithm was used to solve a single objective mixed integer nonlinear programming problem related to environmental impacts [6].…”

Section: Introductionmentioning

confidence: 99%

“…Many researchers and engineers have contributed in an effort to develop systematic methodologies for sustainable process design, online/offline optimal search for sustainable operating conditions, as well as control strategies with the ability of improving the sustainability performance of chemical processes. In the last two decades, several emerging fields have been proposed in the area of sustainable design and optimization, such as process integration [4], process intensification [5], multi-objective optimization [6][7][8][9] and real-time operation along with sustainable corporate-scale management [10,11]. One common way to incorporate sustainability indicators (environmental and social aspects) into process design and optimization is to treat such indicators as constraints in the problem objective of maximizing profitability or minimizing the cost of the operations.…”

Section: Introductionmentioning

confidence: 99%

Development of Chemical Process Design and Control for Sustainability

Mirlekar

Ruiz-Mercado

et al. 2016

Processes

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This contribution describes a novel process systems engineering framework that couples advanced control with sustainability evaluation for the optimization of process operations to minimize environmental impacts associated with products, materials and energy. The implemented control strategy combines a biologically-inspired method with optimal control concepts for finding more sustainable operating trajectories. The sustainability assessment of process operating points is carried out by using the U.S. EPA's Gauging Reaction Effectiveness for the ENvironmental Sustainability of Chemistries with a multi-Objective Process Evaluator (GREENSCOPE) tool that provides scores for the selected indicators in the economic, material efficiency, environmental and energy areas. The indicator scores describe process performance on a sustainability measurement scale, effectively determining which operating point is more sustainable if there are more than several steady states for one specific product manufacturing. Through comparisons between a representative benchmark and the optimal steady states obtained through the implementation of the proposed controller, a systematic decision can be made in terms of whether the implementation of the controller is moving the process towards a more sustainable operation. The effectiveness of the proposed framework is illustrated through a case study of a continuous fermentation process for fuel production, whose material and energy time variation models are characterized by multiple steady states and oscillatory conditions.

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“…In this work, we first apply the parametric algorithm based on the exact Newton's method to circumvent the computational challenge resulting from the fractional objective function. [47][48][49] As a result, a parameter uc is introduced to replace the fractional objective function with a linear parametric function, and the original SMILFP problem is transformed to a set of stochastic mixed-integer linear programming (SMILP) subproblems targeting on finding the optimal value of uc. To further improve the computational efficiency, the resulting two-stage SMILP subproblem is solved using the L-shaped method.…”

Section: A Novel Optimization Algorithmmentioning

confidence: 99%

Deciphering and handling uncertainty in shale gas supply chain design and optimization: Novel modeling framework and computationally efficient solution algorithm

Gao

You

2015

AIChE Journal

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in Wiley Online Library (wileyonlinelibrary.com) The optimal design and operations of shale gas supply chains under uncertainty of estimated ultimate recovery (EUR) is addressed. A two-stage stochastic mixed-integer linear fractional programming (SMILFP) model is developed to optimize the levelized cost of energy generated from shale gas. In this model, both design and planning decisions are considered with respect to shale well drilling, shale gas production, processing, multiple end-uses, and transportation. To reduce the model size and number of scenarios, we apply a sample average approximation method to generate scenarios based on the real-world EUR data. In addition, a novel solution algorithm integrating the parametric approach and the Lshaped method is proposed for solving the resulting SMILFP problem within a reasonable computational time. The proposed model and algorithm are illustrated through a case study based on the Marcellus shale play, and a deterministic model is considered for comparison. V C 2015 American Institute of Chemical Engineers AIChE J, 61: 3739-3755, 2015 Keywords: shale gas, supply chain, estimated ultimate recovery, uncertainty, stochastic program, stochastic mixedinteger linear fractional programming IntroductionIn recent years, the widespread application of horizontal drilling and hydraulic fracturing has led to a "shale revolution," which further results in the U.S. transitioning from an importer to a net exporter of natural gas.1 As reported by the Annual Energy Outlook 2015 released by the U.S. Energy Information Administration (EIA), 2 natural gas production is expected to grow by an average rate of 1.6% per year from 2012 to 2040, more than double the 0.8% expected annual growth rate of total consumption in the U.S. over the same period. The 56% increase in total natural gas production is mainly due to increased shale gas production, which will grow by more than 10 Trillion Standard Cubic Feet (Tscf). The percentage of the U.S. total natural gas production from shale gas is expected to increase from 40% in 2012 to 53% in 2040.Despite the optimistic forecast of shale gas production given by the EIA, a recent report by Post Carbon Institute unveils the fact that the actual future of shale gas may not be as bright as the EIA suggests.3 From a well-by-well-based calculation of shale gas production throughout the U.S., they conclude that the actual profitability of a shale well can be significantly affected by the uncertainty in the estimated ultimate recovery (EUR) and astounding decline rates of production ranging from 60 to 90% in the first 3 years. Considering the significant influence of the shale gas industry on the overall U.S. energy sector, it is essential to design and operate emerging shale gas supply chains with explicit consideration of EUR uncertainty and actual shale gas production profiles.Supply chain design and optimization under uncertainty has long been known as a challenging problem that is vital to the success of industrial concerns. 4,5 Currently, there a...

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Global optimization for sustainable design and synthesis of algae processing network for CO₂ mitigation and biofuel production using life cycle optimization

Cited by 130 publications

References 56 publications

Value-Added Chemicals from Microalgae: Greener, More Economical, or Both?

Value-Added Chemicals from Microalgae: Greener, More Economical, or Both?

Development of Chemical Process Design and Control for Sustainability

Deciphering and handling uncertainty in shale gas supply chain design and optimization: Novel modeling framework and computationally efficient solution algorithm

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Global optimization for sustainable design and synthesis of algae processing network for CO2 mitigation and biofuel production using life cycle optimization

Cited by 130 publications

References 56 publications

Value-Added Chemicals from Microalgae: Greener, More Economical, or Both?

Value-Added Chemicals from Microalgae: Greener, More Economical, or Both?

Development of Chemical Process Design and Control for Sustainability

Deciphering and handling uncertainty in shale gas supply chain design and optimization: Novel modeling framework and computationally efficient solution algorithm

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Global optimization for sustainable design and synthesis of algae processing network for CO₂ mitigation and biofuel production using life cycle optimization