Publications
677 results found
Thaore V, Tsourapas D, Shah N, et al., 2020, Techno-Economic Assessment of Cell-Free Synthesis of Monoclonal Antibodies Using CHO Cell Extracts, PROCESSES, Vol: 8
- Author Web Link
- Cite
- Citations: 5
Khor CS, Akinbola G, Shah N, 2020, A model-based optimization study on greywater reuse as an alternative urban water resource, SUSTAINABLE PRODUCTION AND CONSUMPTION, Vol: 22, Pages: 186-194, ISSN: 2352-5509
- Author Web Link
- Cite
- Citations: 11
Hart MBP, Olympios A, Le Brun N, et al., 2020, Pre-feasibility modelling and market potential analysis of a cloud-based CHP optimiser, 2020 ASHRAE Annual Conference (Virtual), Publisher: ASHRAE, Pages: 300-307
Smart control system technologies for combined heat and power (CHP) units arenot previously reported in literature, and have potential to generate significant savings. Only minimal capital investment is required in infrastructure and software development. A live cloud-based solution has therefore been developed,and installed in a real UK supermarket store, to optimise CHP output based upon predicted price forecasts,and live electricity and head demand data. This has allowed validation of the optimiser price forecasts, and predicted cost savings, anda model of the optimiser has therefore been applied to three case study sites. The model itself has also been validated against the installed optimiser data.The pre-feasibility analysis undertaken indicates cost savings between 2% and 12%.CHP units sized within the feasible operating range, above a part loadlevelof 0.65, generate the greatest percentage savings. This is because the optimiser has the greatest flexibility to control the CHP output. However, larger units, even though less nearly optimal,may actually generate greater overall savings and would therefore be targeted for earlier optimiser implementation. Installation costs are not expected to vary greatly from site-to-site. Some stores, though,show no material improvement over the existing control systems, demonstrating the valueof the pre-feasibility analysis using the model.Though waste heat increases significantly with all strategies, the propensity to sell this heat within the UK is likely to improvein the near future.
Sarabia EJ, Acha Izquierdo S, Le Brun N, et al., 2020, Modelling of a CO2 refrigerant booster system for waste heat recovery applications in retail for space heating provision, 2020 ASHRAE Annual Conference (Virtual), Publisher: ASHRAE
This paper compares and quantifies the energy, environmental and economic benefits of various control strategies for recovering heat from a supermarket’s CO2 booster refrigeration system. There covered heat is used for space heating, with the goal of displacing natural gas fueled boilers. A theoretical model with thermal storage is presentedbased on a previous validated model from an existing refrigeration system in a food-retail building located in the UK. Sixheat recovery strategies are analysed by modifying thermal storage volumes and pressure levels in the gas-cooler/condenser. The model shows that a reduction of 30-40% in natural-gasc onsumption is feasible by the installation of a de-superheater and without any advanced operating strategy, and 40-50% by using a thermal storage tank. However, the CO2 system can fully supply the entire space-heating requirement by adopting alternative control strategies, albeit by penalising the coefficient of performance (COP) of the compressor. Results show that the best energy strategy can reduce total consumption by 35%, while the best economic strategy can reduce costs by 11%. Findings from this work suggest that heat recovery systems can bring substantial benefits to improve the overall efficiency of energy-intensive buildings,although trade-offs need to be carefully considered and further analysed before embarking on such initiatives.
Pantaleo AM, Camporeale S, Sorrentino A, et al., 2020, Hybrid solar-biomass combined Brayton/organic Rankine-cycle plants integrated with thermal storage: Techno-economic feasibility in select Mediterranean areas, Renewable Energy, Vol: 147, Pages: 2913-2931, ISSN: 1879-0682
This paper presents a thermodynamic analysis and techno-economic assessment of a novel hybrid solar-biomass power-generation system configuration composed of an externally fired gas-turbine (EFGT) fuelled by biomass (wood chips) and a bottoming organic Rankine cycle (ORC) plant. The main novelty is related to the heat recovery from the exhaust gases of the EFGT via thermal energy storage (TES), and integration of heat from a parabolic-trough collectors (PTCs) field with molten salts as a heat-transfer fluid (HTF). The presence of a TES between the topping and bottoming cycles facilitates the flexible operation of the system, allows the system to compensate for solar energy input fluctuations, and increases capacity factor and dispatchability. A TES with two molten salt tanks (one cold at 200 °C and one hot at 370 °C) is chosen. The selected bottoming ORC is a superheated recuperative cycle suitable for heat conversion in the operating temperature range of the TES. The whole system is modelled by means of a Python-based software code, and three locations in the Mediterranean area are assumed in order to perform energy-yield analyses: Marseille in France, Priolo Gargallo in Italy and Rabat in Morocco. In each case, the thermal storage that minimizes the levelized cost of energy (LCE) is selected on the basis of the estimated solar radiation and CSP size. The results of the thermodynamic simulations, capital and operational costs assessments and subsidies (feed-in tariffs for biomass and solar electricity available in the Italian framework), allow estimating the global energy conversion efficiency and the investment profitability in the three locations. Sensitivity analyses of the biomass costs, size of PTCs, feed-in tariff and share of cogenerated heat delivered to the load are also performed. The results show that the high investment costs of the CSP section in the proposed size range and hybridization configuration allow investment profitability only in the
Alhajaj A, Shah N, 2020, Multiscale design and analysis of CO<sub>2</sub> networks, INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL, Vol: 94, ISSN: 1750-5836
- Author Web Link
- Cite
- Citations: 4
O'Dwyer E, Chen K, Wang H, et al., 2020, Optimisation of wastewater treatment strategies in eco-industrial parks: technology, location and transport, Chemical Engineering Journal, Vol: 381, Pages: 1-12, ISSN: 1385-8947
The expanding population and rapid urbanisation, in particular in the Global South, areleading to global challenges on resource supply stress and rising waste generation. A transformation to resource-circular systems and sustainable recovery of carbon-containing andnutrient-rich waste offers a way to tackle such challenges. Eco-industrial parks have thepotential to capture symbioses across individual waste producers, leading to more effectivewaste-recovery schemes. With whole-system design, economically attractive approaches canbe achieved, reducing the environmental impacts while increasing the recovery of high-valueresources. In this paper, an optimisation framework is developed to enable such design,allowing for wide ranging treatment options to be considered capturing both technologicaland financial detail. As well as technology selection, the framework also accounts for spatial aspects, with the design of suitable transport networks playing a key role. A range ofscenarios are investigated using the network, highlighting the multi-faceted nature of theproblem. The need to incorporate the impact of resource recovery at the design stage isshown to be of particular importance.
Langshaw L, Ainalis D, Acha Izquierdo S, et al., 2020, Environmental and economic analysis of liquefied natural gas (LNG) for heavy goods vehicles in the UK: A Well-to-Wheel and total cost of ownership evaluation, Energy Policy, Vol: 137, Pages: 1-15, ISSN: 0301-4215
This paper evaluates the environmental and economic performance of liquefied natural gas (LNG) as a transition fuel to replace diesel in heavy goods vehicles (HGVs). A Well-to-Wheel (WTW) assessment based on real-world HGV drive cycles is performed to determine the life-cycle greenhouse gas (GHG) emissions associated with LNG relative to diesel. The analysis is complemented with a probabilistic approach to determine the total cost of ownership (TCO) across a range of scenarios. The methodologies are validated via a case study of vehicles operating in the UK, using data provided by a large food retailer. The spark-ignited LNG vehicles under study were observed to be 18% less energy efficient than their diesel counterparts, leading to a 7% increase in WTW GHG emissions. However, a reduction of up to 13% is feasible if LNG vehicles reach parity efficiency with diesel. Refuelling at publicly available stations enabled a 7% TCO saving in the nominal case, while development of private infrastructure incurred net costs. The findings of this study highlight that GHG emission reductions from LNG HGVs will only be realised if there are vehicle efficiency improvements, while the financial case for operators is positive only if a publicly accessible refuelling network is available.
Bohra M, Shah N, 2020, Optimising the role of solar PV in Qatar's power sector, 6th International Conference on Power and Energy Systems Engineering (CPESE), Publisher: ELSEVIER, Pages: 194-198, ISSN: 2352-4847
- Author Web Link
- Cite
- Citations: 5
Speirs J, Balcombe P, Blomerus P, et al., 2020, Natural gas fuel and greenhouse gas emissions in trucks and ships, Progress in Energy, Vol: 2, Pages: 012002-012002
Kucherenko S, Giamalakis D, Shah N, et al., 2020, Computationally efficient identification of probabilistic design spaces through application of metamodeling and adaptive sampling, Computers & Chemical Engineering, Vol: 132, Pages: 1-9, ISSN: 0098-1354
The design space (DS) is defined as the combination of materials and process conditions which provides assurance of quality for a pharmaceutical product (e.g. purity, potency, uniformity). A model-based approach to identify a probability-based design space requires simulations across the entire process parameter space (certain) and the uncertain model parameter space and material properties space if explicitly considered by the model. This exercise is a demanding task. A novel theoretical and numerical framework for determining probabilistic DS using metamodelling and adaptive sampling is developed. Several approaches were proposed and tested among which the most efficient is a new multi-step adaptive technique based using a metamodel for a probability map as an acceptance-rejection criterion to optimize sampling to identify the DS. It is shown that application of metamodel-based filters can significantly reduce model complexity and computational costs with speed up of two orders of magnitude observed here.
Thaore VB, Armstrong RD, Hutchings GJ, et al., 2020, Sustainable production of glucaric acid from corn stover via glucose oxidation: An assessment of homogeneous and heterogeneous catalytic oxidation production routes, Chemical Engineering Research and Design, Vol: 153, Pages: 337-349, ISSN: 0263-8762
Glucaric acid is being used increasingly as a food additive, corrosion inhibitor, in deicing, and in detergents, and is also a potential starting material for the production of adipic acid, the key monomer for nylon-66. This work describes a techno-economic analysis of a potential bio-based process for the production of pure glucaric acid from corn stover (biomass). Two alternative routes for oxidation of glucose to glucaric acid are considered: via heterogeneous catalytic oxidation with air, and by homogeneous glucose oxidation using nitric acid. Techno-economic and lifecycle assessments (TEA, LCA) are made for both oxidation routes and cover the entire process from biomass to pure crystalline glucaric acid that can be used as a starting material for the production of valuable chemicals. This is the first TEA of pure glucaric acid production incorporating ion exchange and azeotropic evaporation below 50 °C to avoid lactone formation. The developed process models were simulated in Aspen Plus V9. The techno-economic assessment shows that both production routes are economically viable leading to minimum selling prices of glucaric acid of ∼$2.53/kg and ∼$2.91/kg for the heterogeneous catalytic route and the homogeneous glucose oxidation route respectively. It is shown that the heterogeneous catalytic oxidation route is capable of achieving a 22% lower environmental impact than the homogeneous glucose oxidation route. Opportunities for further improvement in sustainable glucaric acid production at industrial scale are identified and discussed.
Iruretagoyena D, Bikane K, Sunny N, et al., 2020, Enhanced selective adsorption desulfurization on CO2 and steam treated activated carbons: Equilibria and kinetics, Chemical Engineering Journal, Vol: 379, Pages: 1-11, ISSN: 1385-8947
Activated carbons (ACs) show great potential for selective adsorption removal of sulfur (SARS) from hydrocarbon fuels but require improvements in uptake and selectivity. Moreover, systematic equilibria and kinetic analyses of ACs for desulfurization are still lacking. This work examines the influence of modifying a commercial-grade activated carbon (AC) by CO2 and steam treatment for the selective adsorption removal of dibenzothiophene (DBT) and 4,6-dimethyldibenzothiophene (4,6-DMDBT) at 323 K. An untreated AC and a charcoal Norit carbon (CN) were used for comparative purposes. Physicochemical characterization of the samples was carried out by combining N2-physisorption, X-ray diffractometry, microscopy, thermogravimetric and infrared analyses. The steam and CO2 treated ACs exhibited higher sulfur uptakes than the untreated AC and CN samples. The steam treated AC appears to be especially effective to remove sulfur, showing a remarkable sulfur uptake (~24 mgS·gads−1 from a mixture of 1500 ppmw of DBT and 1500 ppm 4,6-DMDBT) due to an increased surface area and microporosity. The modified ACs showed similar capacities for both DBT and the sterically hindered 4,6-DMDBT molecules. In addition, they were found to be selective in the presence of sulfur-free aromatics and showed good multicycle stability. Compared to other adsorbents, the modified ACs exhibited relatively high adsorption capacities. The combination of batch and fixed bed measurements revealed that the adsorption sites of the samples are characterized as heterogeneous due to the better fit to the Freundlich isotherm. The kinetic breakthrough profiles were described by the linear driving force (LDF) model.
Liu S, Papageorgiou LG, Shah N, 2020, Optimal design of low-cost supply chain networks on the benefits of new product formulations, Computers & Industrial Engineering, Vol: 139, Pages: 1-17, ISSN: 0360-8352
Formulated products usually comprise a high amount of low-cost ingredients, e.g., water, which could be removed by concentration, and the resulting concentrated products could generate economic advantages, especially in long-distance transportation. This work examines the economic benefits of new product formulations resulted from a new process and product design technology through the optimal design of low-cost formulated product supply chain networks for different product formulations, including traditional formulations and new formulations via concentration. Based on mixed-integer linear programming techniques, an optimisation-based framework is proposed to determine the optimal locations and capacities of plants, warehouses, and distribution centres, as well as the production and distribution planning decisions, by minimising the unit total cost, including raw material, packaging, conversion, inventory, transportation and depreciation costs. In order to deal with the computational complexity, a tailored hierarchical solution approach is developed, in which facility locations and connections are determined by an aggregated static model, and a reduced dynamic model is then solved to determine the facility capacities and the production amounts, distribution flows, and inventory levels in each time period. A case study of a fast-moving consumer goods supply chain is investigated to demonstrate the economic benefits of new product formulations by implementing and comparing different production and distribution structures. The computational results from scenario and sensitivity analysis show that the manufacturing of final products, using a simple concept based on intermediate concentrated formulations produced at a centralised location, results in large supply chain benefits of an economic nature.
Kusumo KP, Gomoescu L, Paulen R, et al., 2020, Nested Sampling Strategy for Bayesian Design Space Characterization, Editors: Pierucci, Manenti, Bozzano, Manca, Publisher: ELSEVIER SCIENCE BV, Pages: 1957-1962
- Author Web Link
- Cite
- Citations: 4
Panteli A, Giarola S, Shah N, 2020, Strategic Biorefining Supply Chain Design for Novel Products in Immature Markets, Editors: Pierucci, Manenti, Bozzano, Manca, Publisher: ELSEVIER SCIENCE BV, Pages: 1579-1584
Soh QY, O'Dwyer E, Acha S, et al., 2020, Optimization and Control of a Rainwater Detention and Harvesting Tank, Editors: Pierucci, Manenti, Bozzano, Manca, Publisher: ELSEVIER SCIENCE BV, Pages: 547-552
- Author Web Link
- Cite
- Citations: 1
Moschou D, Papathanasiou MM, Lakelin M, et al., 2020, Investment Planning in Personalised Medicine, Editors: Pierucci, Manenti, Bozzano, Manca, Publisher: ELSEVIER SCIENCE BV, Pages: 49-54
- Author Web Link
- Cite
- Citations: 2
Sharifzadeh M, Shah N, 2020, Fuel variability and flexible operation of solid oxide fuel cell systems, DESIGN AND OPERATION OF SOLID OXIDE FUEL CELLS: THE SYSTEMS ENGINEERING VISION FOR INDUSTRIAL APPLICATION, Editors: Sharifzadeh, Publisher: ACADEMIC PRESS LTD-ELSEVIER SCIENCE LTD, Pages: 277-295, ISBN: 978-0-12-815253-9
Sharifzadeh M, Chen W, Triulzi G, et al., 2020, Design and operation of solid oxide fuel cell systems: challenges and future research directions, DESIGN AND OPERATION OF SOLID OXIDE FUEL CELLS: THE SYSTEMS ENGINEERING VISION FOR INDUSTRIAL APPLICATION, Editors: Sharifzadeh, Publisher: ACADEMIC PRESS LTD-ELSEVIER SCIENCE LTD, Pages: 445-463, ISBN: 978-0-12-815253-9
- Author Web Link
- Cite
- Citations: 2
Sharifzadeh M, Shah N, 2020, Synthesis, integration, and intensification of solid oxide fuel cell systems: process systems engineering perspective, DESIGN AND OPERATION OF SOLID OXIDE FUEL CELLS: THE SYSTEMS ENGINEERING VISION FOR INDUSTRIAL APPLICATION, Editors: Sharifzadeh, Publisher: ACADEMIC PRESS LTD-ELSEVIER SCIENCE LTD, Pages: 185-215, ISBN: 978-0-12-815253-9
- Author Web Link
- Cite
- Citations: 2
Kong Q, Kuriyan K, Shah N, et al., 2019, Development of a responsive optimisation framework for decision-making in precision agriculture, Computers and Chemical Engineering, Vol: 131, ISSN: 0098-1354
Emerging digital technologies and data advances (e.g. smart machinery, remote sensing) not only enable Agriculture 4.0 to envisage interconnected agro-ecosystems and precision agriculture but also demand responsive decision-making. This study presents a mathematical optimisation model to bring real-time data and information to precision decision-support and to optimise short-term farming operation. To achieve responsive decision-support, we proposed two meta-heuristic algorithms i.e. a tailored genetic algorithm and a hybrid genetic-tabu search algorithm for solving the deterministic optimisation. The developed responsive optimisation framework has been applied to a hypothetical case study to optimise sugarcane harvesting in the KwaZulu Natal region in South Africa. In comparison with the optimal solutions derived from the exact algorithm, the proposed meta-heuristic methods lead to near optimal solutions (less than 5% from optimality) and significantly reduced computational time by over 95%. Our results suggest that the tailored genetic algorithm enables rapid solution searching but the solution quality on sugarcane harvesting cannot compete with the exact method. The hybrid genetic-tabu search algorithm achieved a good trade-off between computational time reduction and solution optimality, demonstrating the potential to enhance responsive decision making in precision sugarcane farming. Our research highlights the development of the responsive optimisation framework combining mixed integer linear programming and hybrid meta-heuristic search algorithms and its applications in real-time decision-making under Agriculture 4.0 vision.
Pozo C, Limleamthong P, Guo Y, et al., 2019, Temporal sustainability efficiency analysis of urban areas via data envelopment analysis and the hypervolume indicator: Application to London boroughs, Journal of Cleaner Production, Vol: 239, Pages: 1-14, ISSN: 0959-6526
Transitioning towards a more sustainable society calls for systematic tools to assess the sustainability performance of urban systems. To perform this task effectively, this work introduces a novel method based on the combined use of Data Envelopment Analysis (DEA) and the hypervolume indicator. In essence, DEA is applied to (i) distinguish between efficient and inefficient urban systems through the identification of best practices; and to (ii) establish improvement targets for the inefficient urban systems that, if attained, would make them efficient. Meanwhile, the hypervolume indicator is employed in conjunction with DEA to evaluate how urban systems evolve with time. The capabilities of this approach are illustrated through its application to the sustainability assessment of London boroughs between 2012–2014. Results reveal that most boroughs tend to perform well in terms of the indicators selected, with 20–25 of the 32 boroughs found efficient depending on the year. Regarding the temporal assessment, a global improvement in sustainability performance was found, with a strong relationship between the boroughs’ performances and their locations. The method proposed opens new pathways of social and environmental research for the application of advanced multi-criteria decision-support tools in the assessment and optimisation of urban systems.
Bahzad H, Katayama K, Boot-Handford ME, et al., 2019, Iron-based chemical-looping technology for decarbonising iron and steel production, INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL, Vol: 91, ISSN: 1750-5836
- Author Web Link
- Cite
- Citations: 9
Acha Izquierdo S, Le Brun N, Shah N, et al., 2019, Assessing the modelling approach and datasets required for fault detection in photovoltaic systems, IEEE Industry Applications Society Annual Meeting, Publisher: IEEE
Reliable monitoring for photovoltaic assets (PVs) is essential to ensuring uptake, long term performance, and maximum return on investment of renewable systems. To this end this paper investigates the input data and machine learning techniques required for day-behind predictions of PV generation, within the scope of conducting informed maintenance of these systems. Five years of PV generation data at hourly intervals were retrieved from four commercial building-mounted PV installations in the UK, as well as weather data retrieved from MIDAS. A support vector machine, random forest and artificial neural network were trained to predict PV power generation. Random forest performed best, achieving an average mean relative error of 2.7%. Irradiance, previous generation and solar position were found to be the most important variables. Overall, this work shows how low-cost data driven analysis of PV systems can be used to support the effective management of such assets.
Kusumo KP, Gomoescu L, Paulen R, et al., 2019, Bayesian approach to probabilistic design space characterization: a nested sampling strategy, Industrial & Engineering Chemistry Research, Vol: 59, Pages: 2396-2408, ISSN: 0888-5885
Quality by design in pharmaceutical manufacturing hinges on computational methods and tools that are capable of accurate quantitative prediction of the design space. This paper investigates Bayesian approaches to design space characterization, which determine a feasibility probability that can be used as a measure of reliability and risk by the practitioner. An adaptation of nested sampling—a Monte Carlo technique introduced to compute Bayesian evidence—is presented. The nested sampling algorithm maintains a given set of live points through regions with increasing probability feasibility until reaching a desired reliability level. It furthermore leverages efficient strategies from Bayesian statistics for generating replacement proposals during the search. Features and advantages of this algorithm are demonstrated by means of a simple numerical example and two industrial case studies. It is shown that nested sampling can outperform conventional Monte Carlo sampling and be competitive with flexibility-based optimization techniques in low-dimensional design space problems. Practical aspects of exploiting the sampled design space to reconstruct a feasibility probability map using machine learning techniques are also discussed and illustrated. Finally, the effectiveness of nested sampling is demonstrated on a higher-dimensional problem, in the presence of a complex dynamic model and significant model uncertainty.
Cooper N, Panteli A, Shah N, 2019, Linear estimators of biomass yield maps for improved biomass supply chain optimisation, APPLIED ENERGY, Vol: 253, ISSN: 0306-2619
- Author Web Link
- Cite
- Citations: 11
Gonzato S, Chimento J, ODwyer E, et al., 2019, Hierarchical price coordination of heat pumps in a building network controlled using model predictive control, Energy and Buildings, Vol: 202, ISSN: 0378-7788
Decarbonisation of the building sector is driving the increased use of heat pumps. As increased electrification of the heating sector leads to stress on the electricity grid, the need for district level coordination of these heat pumps emerges. This paper proposes a novel hierarchical coordination methodology, in which a price coordinator reduces the total instantaneous power demand of a building network below a power supply limit using a price signal. Each building has a model predictive controller (MPC) which maximises thermal comfort and minimises electricity costs. An additional term in the MPC objective function penalises the heat pump power demand quadratically, which when multiplied by a pseudo electricity price allows the price coordinator to reduce the peak power demand of the building network. A 2 building network is studied to analyse the price coordinator algorithm’s behaviour and demonstrate how this approach yields a trade off between comfort, energy consumption and peak demand reduction. A 100 building network case study is then presented as a proof of concept, with the price coordinator approach yielding results similar to that of a centralised controller (less than 0.7% increase in energy consumption per building per year) and a roughly fourfold decrease in computation time.
Escriva EJS, Acha S, LeBrun N, et al., 2019, Modelling of a real CO2 booster installation and evaluation of control strategies for heat recovery applications in supermarkets, International Journal of Refrigeration, Vol: 107, Pages: 288-300, ISSN: 0140-7007
This paper compares and quantifies the energy, environmental and economic benefits of various control strategies recovering heat from a CO2 booster system in a supermarket for space heating with the purpose of understanding its potential for displacing natural gas fuelled boilers. A theoretical steady-state model that simulates the behaviour of the CO2 system is developed and validated against field measurements obtained from an existing refrigeration system in a food-retail building located in the United Kingdom. Five heat recovery strategies are analysed by modifying the mass flows and pressure levels in the condenser. The model shows that a reduction of 48% in natural-gas consumption is feasible by the installation of a de-superheater and without any advanced operating strategy. However, the CO2 system can fully supply the entire space-heating requirement by adopting alternative control strategies, albeit by penalising the coefficient of performance (COP) of the compressor. Results show that the best energy strategy can reduce total consumption by 32%, while the best economic strategy can reduce costs by 6%. Findings from this work suggest that heat recovery systems can bring substantial benefits to improve the overall efficiency of energy-intensive buildings; although trade-offs need to be carefully considered and further analysed before embarking on such initiatives.
Cumicheo C, Mac Dowell N, Shah N, 2019, Natural gas and BECCS: A comparative analysis of alternative configurations for negative emissions power generation, International Journal of Greenhouse Gas Control, Vol: 90, Pages: 1-11, ISSN: 1750-5836
There is a reliance on negative emissions technologies (NETs), primarily in the form of Bioenergy with Carbon Capture and Storage (BECCS) in most Integrated Assessment Model (IAM) scenarios which are capable of limiting the maximum global temperature rise to 1.5–2 °C. Two currently independent features of transition pathways are fuel switching from a coal to gas, and the deployment of BECCS. The former makes natural gas an important transition fuel which at the same time could be combined with biomass to further abate emissions. To date the majority of studies have considered BECCS in the context of a conversion from coal-fired base configuration. There is therefore a pressing need to identify routes for the effective utilization of biomass-derived fuels in the context of gas-fired power generation infrastructure. In this contribution, we study three distinct CCS-based processes which combine natural gas and biomass capable of producing low-, or carbon-negative power. Both fuel supply chains are considered in order to quantify the net overall CO2 emissions. An important insight is the configuration-specific impact of biomass co-combustion on the overall carbon intensity of power generated. We found that an external biomass combustion configuration was the most carbon negative, removing between 0.5–1 ton of CO2 per MWh of power generated. Results revealed a trade-off between carbon negativity and efficiency of the processes. The generation of net carbon negative power is observed to be highly sensitive to the carbon footprint of the biomass supply chain.
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.