OpenUCT :: Browsing by Author "Isafiade, Adeniyi J"

Browsing by Author "Isafiade, Adeniyi J"

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Open Access
A review on heat and mass integration techniques for energy and material minimization during CO2 capture
(2019-04-26) Yoro, Kelvin O; Sekoai, Patrick T; Isafiade, Adeniyi J; Daramola, Michael O
Abstract One major challenge confronting absorptive CO2 capture is its high energy requirement, especially during stripping and sorbent regeneration. To proffer solution to this challenge, heat and mass integration which has been identified as a propitious method to minimize energy and material consumption in many industrial applications has been proposed for application during CO2 capture. However, only a few review articles on this important field are available in open literature especially for carbon capture, storage and utilization studies. In this article, a review of recent progress on heat and mass integration for energy and material minimization during CO2 capture which brings to light what has been accomplished till date and the future outlook from an industrial point of view is presented. The review elucidates the potential of heat and mass exchanger networks for energy and resource minimization in CO2 capture tasks. Furthermore, recent developments in research on the use of heat and mass exchanger networks for energy and material minimization are highlighted. Finally, a critical assessment of the current status of research in this area is presented and future research topics are suggested. Information provided in this review could be beneficial to researchers and stakeholders working in the field of energy exploration and exploitation, environmental engineering and resource utilization processes as well as those doing a process synthesis-inclined research.
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Bioenergy supply chain optimisation: the case study of South Africa
(2019) Egieya, Jafaru Musa; Isafiade, Adeniyi J; Lidija, Čuček
This study involves desktop research on the development of a mixed integer linear programming (MILP) model to optimize the multiple timeframe supply chain network production of bioenergy products based on economic, environmental and sustainability objectives. The study also assesses the effects of varied dry matter and methane contents on electricity production from biogas whereby the General Algebraic Modelling System (GAMS) optimisation software with CPLEX solver is utilised. To develop the model, a four-layer supply chain approach is applied which includes raw materials harvesting and acquisition, primary conversion and secondary conversion technologies and distribution to demand zones. It includes additional features such as storages of raw materials, intermediate and final products, recycle and reuse of intermediate and final products, different transportation modes, variations in production (monthly- or hourly-based), model reduction techniques and single- and multi-objective optimisation, among other features. Most of the data used are from the literature while a limited portion is retrieved from semi-formal correspondences with experts. The model has been firstly applied to electricity production from biogas. The results obtained show that for a case study of three locations in the Western Cape province of South Africa, a profit-after-tax of about 3.1 * 106 $/y is obtained with a dominant feedstock selection of poultry manure, wheat silage and triticale silage when biogas is used to generate 999 kW electricity. Subsequently, a profit-after-tax of approximately 10 * 106 $ /y is accrued when the model is extended to incorporate biodiesel production from waste cooking oil and bioethanol generation from corn stover and forestry residues. It is interesting to note that a tri-criteria objective optimisation of the supply chain network generation of electricity from biogas is also considered using the modified goal method approach. The objectives are to maximize profit-after-tax, environmental unburdening, and sustainability profit. The results indicate a maximum profit-after-tax of about 3.1 * 106 $/y like that obtained in the single objective optimisation. Furthermore, the maximum environmental unburdening and maximum sustainability profit are 4.54 * 103 t CO2 eq./y and 1.135 * 106 $/y. The optimally selected feedstocks in all three objectives scenarios are wheat silage and triticale silage. The results show promise which could be used as a decision support tool for policymakers. Hence, the novelty of this study is a model which integrates dry matter and methane content of feedstocks; the spherical law of cosines equation to calculate the distance between coordinate points; maximised trade-offs of economic, environmental and sustainability profits.
Open Access
Enhanced bioethanol fermentation from mixed xylose and glucose using free and immobilized cultures: mathematical model and experimental observation
(2019) Ghods, Nosaibeh Nosrati; Tai, Siew L; Harrison, Susan TL; Isafiade, Adeniyi J
Bioethanol plays a significant role in the world of liquid biofuel. However, majority of bioethanol is produced from edible food crops such as corn and sugarcane that causes an increase in demand for vacant lands for food production and, subsequently, increase in the cost of food manufacturing. Therefore, alternative raw materials for bioethanol production are sought after, such as sugarcane bagasse which is a waste material from the sugar industry. South Africa, a net sugar exporter, has a large potential to produce bioethanol from sugarcane bagasse. This research focuses on the study of the production of bioethanol from glucose and xylose which are the two most abundant sugars in hydrolysed sugarcane bagasse. To date, no suitable wild type organisms can concomitantly ferment both glucose and xylose to ethanol efficiently. Options to address the co-fermentation of glucose and xylose include genetic modification of the selected microorganism to include both pathways - limitation in the understanding of the metabolic pathways regulations - or utilization of two microorganisms in co-culture or sequential culture e.g. Zymomonas mobilis and Pichia stipitis for efficient fermentation of glucose and xylose respectively. In this study, the dual micro-organism route is explored. There are numerous problems associated with co-culturing. Xylose, a non-preferred carbon source is only converted if the glucose concentration is adequately low due to catabolite repression. In order to increase xylose conversion, a low glucose concentration is required. Therefore, two stage sequential fermentation either in one or two reactors was tested. A high inoculum of suspended or immobilized Z. mobilis was inoculated in the first stage to convert the glucose rapidly. Varying reactor configuration, including the continuous fluidized bed, continuous stirred tank reactor (CSTR) and stirred batch reactor were considered. The products and residual substrate from this fermentation was then directed to a second stage, using either a CSTR or stirred batch configuration, with a high inoculum of P. stipitis in suspension culture for conversion of xylose. When immobilized, Z. mobilis was entrapped in calcium alginate beads. On the issue of ethanol tolerance, P. stipitis is generally more easily inhibited by ethanol (threshold ethanol concentration of 35 g L-1) compared to other ethanol producing strains such as Z. mobilis (threshold ethanol concentration of 127 g L-1) and Saccharomyces cerevisiae (threshold ethanol concentration of 118.2 g L-1). In order to overcome this, a continuous bioprocess was investigated to keep ethanol concentrations in Stage II below 35 g L-1 to prevent inhibition of metabolic reactions in P. stipitis. Further, ethanol fermentation by Z. mobilis requires obligate anaerobic conditions while xylose conversion by P. stipitis is optimum under microaerobic conditions. Therefore, oxygen was sparged into the second P. stipitis stage only. The following components were carried out in this project to improve the kinetic model and to find accurate kinetic data in the selected process of the two stage sequential fermentation. Firstly, where kinetic parameters were not available in literature, the kinetic parameter relationships of glucose and xylose utilization between different constructs of the same species were examined, for example, a wild type and engineered strain. This approach was used for glucose conversion using wild type Z. mobilis, owing to the ill-fit of available kinetic parameters with experimental results. In this study, the correction factors on estimated kinetic parameters from linear and non-linear regression when a xylose fermentation route was inserted recombinantly (S. cerevisiae RWB 217) into the native culture (S. cerevisiae CEN.PK 113-7D) were determined. From kinetic parameters of an engineered strain with the xylose-fermenting pathway (Z. mobilis ZM4 (pZB5)) and the correction factors, kinetic parameters of the wild-type Z. mobilis ZM4 were determined. Predicted rates of Z. mobilis ZM4 were then validated with experimental data generated in this study. Then, the optimum initial biomass concentration required to provide a faster volumetric rate of sugar utilisation and ethanol production, as well as the optimum oxygenation level for xylose conversion using P. stipitis achieved through appropriate aeration were investigated through experimental observation and using a MATLAB mathematical model developed through combination of the Andrews and Levenspiel's models, with oxygen, substrate, cell and product terms. Experiments were carried out to validate the kinetic model and data under anaerobic and microaerobic growth conditions in a batch process. The results showed that both increasing the initial biomass concentration (3 g L-1) and operating under optimum oxygenation levels (0.1 vvm) benefitted the ethanol production and yield by P. stipitis from xylose. It was also concluded that the addition of the oxygen effective factors in the developed model allowed for optimization of aeration in the fermentation system. Next, the custom kinetic model for fermentation process of bioethanol production was developed in Aspen Custom Modeller (ACM) and embedded in Aspen Plus. The model includes equations of vapour-liquid equilibrium (VLE), mass balance, and energy balance (e.g. molecular weight, thermodynamic phase equilibria, kinetic equation). The obtained results showed better agreement between industrial data and kinetic model (1% differences) than a stoichiometric model (9% differences). The simulation showed that ACM integrated into Aspen Plus allowed for complex biological processes to be accurately predicted for biomass growth, ethanol production and sugar consumption. Finding suitable microorganisms and process conditions for efficient glucose and xylose conversion is still currently a challenge and requires optimization. Therefore, this research focusses on improving the conversion of glucose and xylose to bioethanol, with specific emphasis on the fermentation systems used to maximize biomass efficiency, and ethanol yields and productivities. Manipulation of process conditions ranging from operation conditions (e.g. batch, fed-batch, continuous), process parameters (aeration, temperature, pH), immobilization technique and type of microorganism initially using kinetic models and thereafter validating with experimental data, therefore, offers a quick and strong foundation in improving bioethanol yields and productivities.
Open Access
Optimization of biogas supply networks considering multiple objectives and auction trading prices of electricity
(2020-01-08) Egieya, Jafaru M; Čuček, Lidija; Zirngast, Klavdija; Isafiade, Adeniyi J; Kravanja, Zdravko
Abstract This contribution presents an hourly-based optimization of a biogas supply network to generate electricity, heat and organic fertilizer while considering multiple objectives and auction trading prices of electricity. The optimization model is formulated as a mixed-integer linear programming (MILP) utilizing a four-layer biogas supply chain. The model accounts for biogas plants based on two capacity levels of methane to produce on average 1 ± 0.1 MW and 5 ± 0.2 MW electricity. Three objectives are put forward: i) maximization of economic profit, ii) maximization of economic profit while considering cost/benefits from greenhouse gas (GHG) emissions (economic+GHG profit) and iii) maximization of sustainability profit. The results show that the economic profit accrued on hourly-based auction trading prices is negative (loss), hence, four additional scenarios are put forward: i) a scenario whereby carbon prices are steadily increased to the prevalent eco-costs/eco-benefits of global warming; ii) a scenario whereby all the electricity auction trading prices are multiplied by certain factors to find the profitability breakeven factor, iii) a scenario whereby shorter time periods are applied, and investment cost of biogas storage is reduced showing a relationship between cost, volume of biogas stored and the variations in electricity production and (iv) a scenario whereby the capacity of the biogas plant is varied from 1 MW and 5 MW as it affects economics of the process. The models are applied to an illustrative case study of agricultural biogas plants in Slovenia where a maximum of three biogas plants could be selected. The results hence present the effects of the simultaneous relationship of economic profit, economic+GHG profit and sustainability profit on the supply and its benefit to decision-making.
Open Access
The synthesis of Combined Heat and Mass Exchange Networks (CHAMENs) with renewables considering environmental impact
(2019) Kim, So-Mang; Isafiade, Adeniyi J
Process synthesis is used to evaluate different potential designs to select the most suitable that fulfils some process goals. There is ever-increasing pressure to reduce operating cost and emission of pollutants as energy prices continue to increase and more regulations are set by government. To address these concerns, optimisation methods based on heuristics, pinch technology and mathematical programming can be adopted. Since the early 90s, mathematical programming has gained significant attention to solve large and complex problems. Extensive studies have been conducted for heat exchange network synthesis (HENS), which was first used to optimise utility usage and operating costs. Many existing mass exchange network synthesis (MENS) methods are derived from HENS techniques since analogies exist between the two networks. Integrating the synthesis of mass and heat exchange networks in what is known as combined heat and mass exchange network synthesis (CHAMENS) can be beneficial because mass transfer is affected by operating temperature. However, very little research has been done in this area of process synthesis due to their complex nature. It is even more challenging to find literature involving the regeneration of multiple recyclable MSAs in a network synthesis context. Furthermore, the few studies that have considered CHAMENS have done the optimisation considering economic performance alone, whereas the consideration of environmental impact as an additional objective can help attain a more sustainable process. This thesis builds on current knowledge of CHAMENs synthesis methods by considering CHAMENs with detailed regeneration networks (RENs) involving multiple recyclable MSAs, multiple regenerating streams, and solar thermal as an alternative energy source, using a multi-period synthesis approach. Simultaneously optimising a combination of these networks is not a trivial task due to the resulting large model size having many binary and non-linear terms and the interactions among them. Stage-wise superstructure (SWS) synthesis approaches for heat and mass exchanger networks are adopted in this thesis for the synthesis of CHAMENs. A new superstructure for RENs, which is equivalent to that of a MEN, is presented in this thesis. The combined superstructure, which involves multiple MSAs, multiple regenerants, and multiple hot and cold process streams, is integrated with solar thermal energy as a renewable energy option. The availability of solar thermal energy is simplified by discretizing into two time periods of daytime and nighttime operations. The proposed CHAMEN model is also extended to handle multi-objective optimisation (MOO) of environmental impact and economic objectives to identify the optimal network configuration. Two examples were solved, and the results obtained showed that the implementation of integrated solar panels and thermal storage tanks could reduce the environmental impact of the combined networks by 76% and 26% for case studies 1 and 2 respectively. However, such eco-friendly infrastructure resulted in increased total annual cost (TAC) values of 36% and 15% respectively for the two case studies. These results indicate that by using the methodologies developed in this thesis, trade-offs can be established between economics and environmental impact as objectives.

Browsing by Author "Isafiade, Adeniyi J"

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