Publications
677 results found
Leonzio G, Shah N, 2024, Recent advancements and challenges in carbon capture, utilization and storage, Current Opinion in Green and Sustainable Chemistry, Vol: 46, ISSN: 2452-2236
This short paper suggests a review of the latest developments and current challenges associated with carbon dioxide capture, utilization and storage. Recent research has been conducted to reduce energy consumption, costs, and improve efficiency. In carbon dioxide capture, catalysts have been added to solvents while new membranes and sorbent materials have been investigated. In mineral carbon dioxide storage, studies have been carried out to improve reaction rates. Regarding the utilization path, attention has been focused on the development of sustainable chemicals (mainly based on electrochemical conversion), biochemical routes and power generation. Considering the respective challenges, future efforts should be focused toward the optimization of these systems at all levels, in addition to a public acceptance and new policies and regulations for their spread.
Ibrahim D, Kis Z, Papathanasiou MM, et al., 2024, Strategic Planning of a Joint SARS-CoV-2 and Influenza Vaccination Campaign in the UK, Vaccines, Vol: 12, ISSN: 2076-393X
The simultaneous administration of SARS-CoV-2 and influenza vaccines is being carried out for the first time in the UK and around the globe in order to mitigate the health, economic, and societal impacts of these respiratory tract diseases. However, a systematic approach for planning the vaccine distribution and administration aspects of the vaccination campaigns would be beneficial. This work develops a novel multi-product mixed-integer linear programming (MILP) vaccine supply chain model that can be used to plan and optimise the simultaneous distribution and administration of SARS-CoV-2 and influenza vaccines. The outcomes from this study reveal that the total budget required to successfully accomplish the SARS-CoV-2 and influenza vaccination campaigns is equivalent to USD 7.29 billion, of which the procurement costs of SARS-CoV-2 and influenza vaccines correspond to USD 2.1 billion and USD 0.83 billion, respectively. The logistics cost is equivalent to USD 3.45 billion, and the costs of vaccinating individuals, quality control checks, and vaccine shipper and dry ice correspond to USD 1.66, 0.066, and 0.014, respectively. The analysis of the results shows that the choice of rolling out the SARS-CoV-2 vaccine during the vaccination campaign can have a significant impact not only on the total vaccination cost but also on vaccine wastage rate.
Nyhus AH, Yliruka M, Shah N, et al., 2024, Green ethylene production in the UK by 2035: a techno-economic assessment, Energy and Environmental Science, Vol: 17, Pages: 1931-1949, ISSN: 1754-5692
Olefins production in the UK is the most emission-intensive sector of the chemical industry. Bringing thermocatalytic and electrocatalytic processes together, this paper compares nine process routes for green ethylene production from air-captured CO2 and off-shore wind electricity in order to displace fossil-based ethylene, with a particular focus on technology readiness for near-future deployment. The methanol-mediated thermocatalytic route has the lowest projected levelised cost at £2900 per ton of ethylene by 2035, closely followed by direct and tandem CO2 electroreduction routes in the range £2900-3200. The price of green ethylene at three times or more its current market price is confirmed through a sensitivity analysis varying the levelised cost of electricity, stack cost, and market price of propylene or oxygen simultaneously. While these green ethylene production processes would be carbon negative from a cradle-to-gate viewpoint, displacing a conventional ethane cracker with annual production capacity of 800 kt could consume as much as 46-66 TW h of renewable electricity, which is a major barrier to deployment.
Triantafyllou N, Sarkis M, Krassakopoulou A, et al., 2024, Uncertainty quantification for gene delivery methods: A roadmap for pDNA manufacturing from phase I clinical trials to commercialization., Biotechnol J, Vol: 19
The fast-growing interest in cell and gene therapy (C>) products has led to a growing demand for the production of plasmid DNA (pDNA) and viral vectors for clinical and commercial use. Manufacturers, regulators, and suppliers need to develop strategies for establishing robust and agile supply chains in the otherwise empirical field of C>. A model-based methodology that has great potential to support the wider adoption of C> is presented, by ensuring efficient timelines, scalability, and cost-effectiveness in the production of key raw materials. Specifically, key process and economic parameters are identified for (1) the production of pDNA for the forward-looking scenario of non-viral-based Chimeric Antigen Receptor (CAR) T-cell therapies from clinical (200 doses) to commercial (40,000 doses) scale and (2) the commercial (40,000 doses) production of pDNA and lentiviral vectors for the current state-of-the-art viral vector-based CAR T-cell therapies. By applying a systematic global sensitivity analysis, we quantify uncertainty in the manufacturing process and apportion it to key process and economic parameters, highlighting cost drivers and limitations that steer decision-making. The results underline the cost-efficiency and operational flexibility of non-viral-based therapies in the overall C> supply chain, as well as the importance of economies-of-scale in the production of pDNA.
Wang Z, Acha S, Bird M, et al., 2024, A total cost of ownership analysis of zero emission powertrain solutions for the heavy goods vehicle sector, Journal of Cleaner Production, Vol: 434, ISSN: 0959-6526
Transport-related activities represented 34% of the total carbon emissions in the UK in 2022 and heavy-duty vehicles (HGVs) accounted for one-fifth of the road transport greenhouse gas (GHG) emissions. Currently, battery electric vehicles (BEVs) and hydrogen fuel cell electric vehicles (FCEVs) are considered as suitable replacements for diesel fleets. However, these technologies continue to face techno-economic barriers, creating uncertainty for fleet operators wanting to transition away from diesel-powered internal combustion engine vehicles (ICEVs). This paper assesses the performance and cost competitiveness of BEV and FCEV powertrain solutions in the hard-to-abate HGV sector. The study evaluates the impact of battery degradation and a carbon tax on the cost of owning the vehicles. An integrated total cost of ownership (TCO) model, which includes these factors for the first time, is developed to study a large retailer's HGV fleet operating in the UK. The modelling framework compares the capital expenditures (CAPEX) and operating expenses (OPEX) of alternative technologies against ICEVs. The TCO of BEVs and FCEVs are 11% to 33% and 37% to 78% higher than ICEVs; respectively. Despite these differences, by adopting a longer lifetime for the vehicle it can effectively narrow the cost gap. Alternatively, cost parity with ICEVs could be achieved if BEV battery cost reduces by 56% or if FCEV fuel cell cost reduces by 60%. Besides, the pivot point for hydrogen price is determined at £2.5 per kg. The findings suggest that BEV is closer to market as its TCO value is becoming competitive, whereas FCEV provides a more viable solution than BEV for long-haul applications due to shorter refuelling time and lower load capacity penalties. Furthermore, degradation of performance in lithium-ion batteries is found to have a minor impact on TCO if battery replacement is not required. However, critical component replacement and warranty can influence commercial viability. Given
Leonzio G, Chachuat B, Shah N, 2023, Towards ethylene production from carbon dioxide: Economic and global warming potential assessment, Sustainable Production and Consumption, Vol: 43, Pages: 124-139
Currently, ethylene is the most important chemical with the largest global demand: it is mainly produced by ethane or naphtha cracking but, this is characterized by significant carbon dioxide emissions. For this reason, starting from carbon dioxide and water, different routes for ethylene production have been proposed and investigated in the literature but a complete comparative analysis is missing. In this research, we analyze ethylene production via carbon dioxide electroreduction and methanol-to-olefin process, with methanol obtained in several ways. After the modelling of these systems, economic and environmental (in term of global warming potential) analyses are conducted to develop a comparison among the investigated processes and a conventional one based on naphtha cracking. Results, located in the UK, show that the tandem process could be economically competitive (with the lowest production cost of $ 1.34 per kg of ethylene), while the methanol-to-olefin process with methanol obtained from syngas (produced through carbon dioxide-water co-electrolysis) has the best advantage for carbon dioxide emissions (with the lowest impact of −3.08 kg of CO2eq per kg of ethylene). Moreover, the most preferred energy source for the electricity supply is the nuclear one with a small-scale plant because, economic and greenhouse gas emission advantages are provided while, worse conditions are obtained when solar energy is used. Our main finding is that electrochemical processes are likely to play an important role in the future when performance improvements are realized.
Guo M, Wu C, Chapman S, et al., 2023, Advances in biorenewables-resource-waste systems and modelling, Carbon Capture Science & Technology, Vol: 9
The transformation to a resource-circular bio-economy offers a mechanism to mitigate climate change and environmental degradation. As advanced bioeconomy components, biorenewables derived from terrestrial, aquatic biomass and waste resources are expected to play significant roles over the next decades. This study provides an overview of potential biomass resources ranging from higher plant species to phototrophic microbial cluster, and their fundamental photosynthesis processes as well as biogeochemical carbon cycles involved in ecosystems. The review reflects empirical advances in conversion technologies and processes to manufacture value-added biorenewables from biomass and waste resources. The nexus perspective of resource-biorenewable-waste has been analysed to understand their interdependency and wider interaction with environmental resources and ecosystems. We further discussed the systems perspectives of biorenewables to develop fundamental understanding of resource flows and carbon cycles across biorenewable subsystems and highlight their spatial and temporal variability. Our in-depth review suggested the system challenges of biorenewable, which are subject to nonlinearity, variability and complexity. To unlock such system complexity and address the challenges, a whole systems approach is necessary to develop fundamental understanding, design novel biorenewable solutions. Our review reflects recent advances and prospects of computational methods for biorenewable systems modelling. This covers the development and applications of first principle models, process design, quantitative evaluation of sustainability and ecosystem services and mathematical optimisation to improve design, operation and planning of processes and develop emerging biorenewable systems. Coupling these advanced computational methods, a whole systems approach enables a multi-scale modelling framework to inherently link the processes and subsystems involved in biomass ecosystems and biorenew
Freire Ordóñez D, Ganzer C, Halfdanarson T, et al., 2023, Quantifying global costs of reliable green hydrogen, Energy Advances, Vol: 2, Pages: 2042-2054
The current energy crisis has resulted in natural gas prices at an unprecedented level in many parts of the world, with significant consequences for the price of food and fertiliser. In this context, and with the projected reduction in the costs of renewables and electrolysers, green hydrogen is becoming an increasingly attractive option. In this study, we evaluate the current and future costs of green hydrogen, produced on a reliable schedule, so as to be coherent with industrial demand. Here, we take full account of both inter- and intra-annual variability of renewable energy, using 20 years of hourly resolution wind and solar data from 1140 grid points around the world. We observe that simply using average annual capacity factors will result in a significantly under-sized system that will frequently be unable to meet demand. In order to ensure production targets are met, over-capacity of power generation assets and energy storage assets are required to compensate for inter-annual and intra-annual variations in the availability of wind and solar resources, especially in the time periods known as “dunkelflauten”. Whilst costs vary substantially around the world, contemporary costs of reliable green hydrogen are estimated to be, on average, 18-22 USD per kgH2 with a minimum of 5 USD per kgH2, depending on the ability to monetise “surplus” or “excess” renewable energy. The primary cost driver is renewable energy capacity, with electrolysers and energy storage costs exerting a second-order effect. With cost reduction, future costs are anticipated to be, on average, 8-10 USD per kgH2 with a minimum of 3 USD per kgH2, again as a function of the ability to monetise otherwise curtailed power. Another key factor in future costs is found to be hurdle rates for capital investments. Finally, we observe that continued cost reduction of renewable power is key to reducing overall system costs of green hydrogen production.
Soh QY, ODwyer E, Acha S, et al., 2023, Robust optimisation of combined rainwater harvesting and flood mitigation systems, Water Research, Vol: 245, ISSN: 0043-1354
Combined large-scale rainwater harvesting (RWH) and flood-mitigation systems are promising as a sustainable water management strategy in urban areas. These are multi-purpose infrastructure that not only provide a secondary, localised water resource, but can also reduce discharge and hence loads on any downstream wastewater networks if these are integrated into the wider water network. However, the performance of these systems is dependent on the specific design used for its local catchment which can vary significantly between different implementations. A multitude of design strategies exist, however, there is no universally accepted standard framework. To tackle these issues, this paper presents a two-player optimisation framework which utilises a stochastic design optimisation model and a competing, high intensity rainfall design model to optimise passively operated RWH systems. A customisable tool set is provided, under which optimisation models specific to a given catchment can be built quickly. This reduces the barriers to implementing computationally complex sizing strategies and encouraging more resource-efficient systems to be built. The framework was applied to a densely populated high-rise residential estate, eliminating overflow events from historical rainfall. The optimised configuration resulted in a 32% increase in harvested water yield, but its ability to meet irrigation demands was limited by the operational levels of the treatment pump. Hence, with the inclusion of operational levels in the optimisation model, the framework can provide an efficient large-scale RWH system that is capable of simultaneously meeting water demands and reducing stresses within and beyond its local catchment.
Wong JJ, Iruretagoyena D, Shah N, et al., 2023, A three-interface random pore model: The reduction of iron oxide in chemical looping and green steel technologies, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol: 479, ISSN: 1364-5021
Accurate modelling of the gaseous reduction of porous iron oxide powders or fines is important in industry for (i) reinventing the carbon intensive production of iron and steel and (ii) chemical looping technologies in the sphere of carbon capture and storage. A new three-interface random pore model is derived and applied to the gaseous reduction of hematite (Fe2O3) to iron (Fe). The structural reaction-diffusion model is able to describe three simultaneously reacting oxide layers, Fe2O3, magnetite (Fe3O4) and wustite (FewO). The geometric nature of the model encodes structural information about the particles (porosity, surface area, pore length and size distribution), measured here by experiment. The model is usefully able to separate structural particle properties from individual rates of reaction and product layer diffusion. The results have been compared and fitted to thermogravimetric experiments between 800-1000∘ C and three CO/CO2 gas mixtures. Rate constants for each indvidual reaction have been obtained and fit well to Arrhenius plots. The reduction of Fe2O3-Fe3O4 was controlled by diffusion and reaction kinetics, while the reduction of Fe3O4-FewO and FewO-Fe was limited by reaction kinetics. Metallization rates of the iron oxide powders were rapid, showing promise for both hydrogen-based direct reduced iron and chemical looping processes.
Yliruka M, Moret S, Shah N, 2023, Detail or uncertainty? Applying global sensitivity analysis to strike a balance in energy system models, Computers and Chemical Engineering, Vol: 177, Pages: 1-22, ISSN: 0098-1354
Energy systems modellers often resort to simplified system representations and deterministic model formulations (i.e., not considering uncertainty) to preserve computational tractability. However, reduced levels of detail and neglected uncertainties can both lead to sub-optimal system designs. Herein, we present a novel method that quantitatively compares the impact of detail and uncertainty to guide model development and help prioritisation of the limited computational resources. By considering modelling choices as an additional ‘uncertain’ parameter in a global sensitivity analysis, the method determines their qualitative ranking against conventional input parameters. As a case study, the method is applied to a peer-reviewed heat decarbonisation model for the United Kingdom with the objective of assessing the importance of spatial resolution. The results show that while for the optimal total system cost the impact of spatial resolution is negligible, it is the most important factor determining the capacities of electricity, gas and heat networks.
Bustos-Turu G, van Dam KH, Acha S, et al., 2023, An agent-based decision support framework for a prospective analysis of transport and heat electrification in urban areas, Energies, Vol: 16, ISSN: 1996-1073
One of the main pathways that cities are taking to reduce greenhouse gas emissions is the decarbonisation of the electricity supply in conjunction with the electrification of transport and heat services. Estimating these future electricity demands, greatly influenced by end-users’ behaviour, is key for planning energy systems. In this context, support tools can help decision-makers assess different scenarios and interventions during the design of new planning guidelines, policies, and operational procedures. This paper presents a novel bottom-up decision support framework using an agent-based modelling and simulation approach to evaluate, in an integrated way, transport and heat electrification scenarios in urban areas. In this work, an open-source tool named SmartCityModel is introduced, where agents represent energy users with diverse sociodemographic and technical attributes. Based on agents’ behavioural rules and daily activities, vehicle trips and building occupancy patterns are generated together with electric vehicle charging and building heating demands. A representative case study set in London, UK, is shown in detail, and a summary of more than ten other case studies is presented to highlight the flexibility of the framework to generate high-resolution spatiotemporal energy demand profiles in urban areas, supporting decision-makers in planning low-carbon and sustainable cities.
Hoseinpoori P, Hanna R, Woods J, et al., 2023, Comparing alternative pathways for the future role of the gas grid in a low-carbon heating system, Energy Strategy Reviews, Vol: 49, Pages: 1-25, ISSN: 2211-467X
This paper uses a whole-system approach to examine different strategies related to the future role of the gas grid in alow-carbon heat system. A novel model of integrated gas, electricity and heat systems, HEGIT, is used to investigate fourkey sets of scenarios for the future of the gas grid using the UK as a case study: a) complete electrification of heating; b)conversion of the existing gas grid to deliver hydrogen; c) a hybrid heat pump system; and d) a greener gas grid. Ourresults indicate that although the infrastructure requirements, the fuel or resource mix, and the breakdown of costs varysignificantly over the complete electrification to complete conversion of the gas grid to hydrogen spectrum, the total systemtransition cost is relatively similar. This reduces the significance of total system cost as a guiding factor in policy decisionson the future of the gas grid. Furthermore, we show that determining the roles of low-carbon gases and electrification fordecarbonising heating is better guided by the trade-offs between short- and long-term energy security risks in the system,as well as trade-offs between consumer investment in fuel switching and infrastructure requirements for decarbonisingheating. Our analysis of these trade-offs indicates that although electrification of heating using heat pumps is not thecheapest option to decarbonise heat, it has clear co-benefits as it reduces fuel security risks and dependency on carboncapture and storage infrastructure. Combining different strategies, such as grid integration of heat pumps with increasedthermal storage capacity and installing hybrid heat pumps with gas boilers on the consumer side, are demonstrated toeffectively moderate the infrastructure requirements, consumer costs and reliability risks of widespread electrification.Further reducing demand on the electricity grid can be accomplished by complementary options at the system level, suchas partial carbon offsetting using negative emission technologies
Sarkis M, Shah N, Papathanasiou MM, 2023, Characterization of key manufacturing uncertainties in next generation therapeutics and vaccines across scales, Journal of Advanced Manufacturing and Processing, Vol: 5
Viral vectors are advanced therapy products used as genetic information carriers in vaccine and cell therapy development and manufacturing. Despite the first product receiving market authorization in 2012, viral vector manufacturing has still not reached the level of maturity of biologics and is still highly susceptible to process uncertainties, such as viral titers and chromatography yields. This was exacerbated by the COVID-19 pandemic when viral vector manufacturers were challenged to respond to the global demand in a timely manner. A key reason for this was the lack of a systematic framework and approach to support capacity planning under uncertainty. To address this, we present a methodology for: (i) identification of process cost and volume bottlenecks, (ii) quantification of process uncertainties and their impact on target key performance indicators, and (iii) quantitative analysis of scale-dependent uncertainties. We use global sensitivity analysis as the backbone to evaluate three industrially relevant vector platforms: adeno-associated, lentiviral, and adenoviral vectors. For the first time, we quantify how operating parameters can affect process performance and, critically, the trade-offs among them. Results indicate a strong, direct proportional correlation between volumetric scales and propagation of uncertainties, while we identify viral titer as the most critical scale-up bottleneck across the three platforms. The framework can de-risk investment decisions, primarily related to scale-up and provides a basis for proactive decision-making in manufacturing and distribution of advanced therapeutics.
O'Dwyer E, Kerrigan E, Falugi P, et al., 2023, Data-driven predictive control with improved performance using segmented trajectories, IEEE Transactions on Control Systems Technology, Vol: 31, Pages: 1355-1365, ISSN: 1063-6536
A class of data-driven control methods has recently emerged based on Willems' fundamental lemma. Such methods can ease the modelling burden in control design but can be sensitive to disturbances acting on the system under control. In this paper, we extend these methods to incorporate segmented prediction trajectories. The proposed segmentation enables longer prediction horizons to be used in the presence of unmeasured disturbance. Furthermore, a computation time reduction can be achieved through segmentation by exploiting the problem structure, with computation time scaling linearly with increasing horizon length. The performance characteristics are illustrated in a set-point tracking case study in which the segmented formulation enables more consistent performance over a wide range of prediction horizons. The computation time for the segmented formulation is approximately half that of an unsegmented formulation for a horizon of 100 samples. The method is then applied to a building energy management problem, using a detailed simulation environment, in which we seek to minimise the discomfort and energy of a 6-room apartment. With the segmented formulation, a 72% reduction in discomfort and 5% financial cost reduction is achieved, compared to an unsegmented formulation using a one-day-ahead prediction horizon.
Cooper J, Bird M, Acha S, et al., 2023, The Carbon Footprint of a UK Chemical Engineering Department – The Case of Imperial College London, The 30th CIRP Life Cycle Engineering Conference, Publisher: Elsevier, Pages: 444-449, ISSN: 2212-8271
As the UK strives towards net-zero it is important that all sectors, including Higher Education, take immediate measures to cut their greenhouse gas emissions. The greenhouse gases emitted by different Higher Education institutions are studied and are shown to be large. However, these studies are based on aggregated data, and it is therefore uncertain how effective institute-wide policies to cut emissions are at department level. Herein, we present a generic framework for university departments to calculate their carbon footprint considering Scope 1, 2 and 3 emissions. We estimate the carbon footprint of the Chemical Engineering Department at Imperial College London to be 7,620 and 8,330 tCO2eq in 2018/19 and 2019/20, respectively. Scope 3 emissions account for 54% of the Department's emissions with Scope 1 and 2 accounting for the remaining 46%. Scope 3 emissions are largely driven by purchased goods and travel, while Scope 1 emissions are predominantly from electricity usage.
van de Berg D, Petsagkourakis P, Shah N, et al., 2023, Data-driven coordination of subproblems in enterprise-wide optimization under organizational considerations, AIChE Journal, Vol: 69, Pages: 1-24, ISSN: 0001-1541
While decomposition techniques in mathematical programming are usually designed for numerical efficiency, coordination problems within enterprise-wide optimization are often limited by organizational rather than numerical considerations. We propose a “data-driven” coordination framework which manages to recover the same optimum as the equivalent centralized formulation while allowing coordinating agents to retain autonomy, privacy, and flexibility over their own objectives, constraints, and variables. This approach updates the coordinated, or shared, variables based on derivative-free optimization (DFO) using only coordinated variables to agent-level optimal subproblem evaluation “data.” We compare the performance of our framework using different DFO solvers (CUATRO, Py-BOBYQA, DIRECT-L, GPyOpt) against conventional distributed optimization (ADMM) on three case studies: collaborative learning, facility location, and multiobjective blending. We show that in low-dimensional and nonconvex subproblems, the exploration-exploitation trade-offs of DFO solvers can be leveraged to converge faster and to a better solution than in distributed optimization.
Leonzio G, Mwabonje O, Fennell PS, et al., 2023, Corrigendum to “Environmental performance of different sorbents used for direct air capture” [Sustain. Prod. Consum. 32 (2022) 101–111], Sustainable Production and Consumption, Vol: 36, Pages: 415-415, ISSN: 2352-5509
Lyons B, Bernardi A, Shah N, et al., 2023, Methane-to-X: an economic assessment of methane valorisation options to improve carbon circularity, Computer Aided Chemical Engineering, Pages: 2435-2440
Methane side streams are produced in many different chemical processes and are normally combusted to provide process heat or to generate electricity. However, this practice is becoming less and less attractive as the industry strives towards net-zero targets and increasing the circularity of chemicals. Methane could instead be recovered and used as a valuable feedstock to produce other platform chemicals, such as H2 or ethylene, which could be beneficial both for the economic performance and the carbon circularity of the system. In this work, seven different methane valorisation routes to produce additional chemicals are investigated. The considered routes include: i) five syngas-based routes combined with methanol synthesis and a methanol-to-olefins process; ii) plasma methane pyrolysis; and iii) oxidative coupling of methane. The results suggest that oxidative coupling of methane is the most profitable, with methane pyrolysis, tri-reforming and autothermal reforming also being more profitable in the base case. All routes have lower scope 1 and 2 emissions than the base case, however, dry-reforming and bi-reforming have the lowest emissions thanks to credited CO2 feed streams.
Triantafyllou N, Papaiakovou S, Bernardi A, et al., 2023, Machine learning-based decomposition for complex supply chains, Computer Aided Chemical Engineering, Pages: 1655-1660
Personalised medicine products represent a novel category of therapeutics often characterised by bespoke manufacturing lines and dedicated distribution nodes. An example of such products is Chimeric Antigen Receptor (CAR) T-cells, whose manufacturing poses challenges to volumetric scale-up, leading to increased production and supply chain costs. From a modelling perspective, such networks lead to complex large-scale supply chain models that grow exponentially as the demand increases and more therapies are tracked simultaneously throughout the supply chain. In this work, we present a hybrid model that utilizes the potential of machine learning for strategic planning by forecasting optimal supply chain structures and Mixed Integer Linear Programming (MILP) for detailed scheduling. The proposed model is robust to uncertain demand patterns and can reduce the number of linear constraints and binary variables in the original MILP by more than 64.7%.
Soh QY, O'Dwyer E, Acha S, et al., 2023, Modular stochastic optimization for optimal rainwater harvesting system design, Computer Aided Chemical Engineering, Pages: 697-702
Rainwater Harvesting (RWH) systems can serve a dual functionality as a flood mitigation structure as well as providing local water availability. Optimisation-based design strategies must be transferrable enough to incorporate the influence of the local climate and case-specific catchment area characteristics into the design process, which can be a significant endeavour when required for every individual implementation. To increase the accessibility of optimisation methods in the appropriate sizing of RWH systems, this paper presents a modularised optimisation model, where tank components and dynamics are contained as individual blocks. These blocks can then be pieced together to produce a full system model, allowing optimisation models to be easily built for any combination and design of RWH system. This is implemented with a multi-tank RWH system, where an evaluation of the optimised system configuration showed a good balance between the dual objectives of providing improved flood mitigation and local water reuse, in comparison to an existing system derived through alternative sizing strategies.
Sarkis M, Fung J, Lee MH, et al., 2023, Integrating environmental sustainability in next-generation biopharmaceutical supply chains, Computer Aided Chemical Engineering, Pages: 3405-3410
Maximizing product availability to the public and minimizing costs are primary objectives in the biopharmaceutical sector. Nevertheless, awareness of the environmental sustainability of supply chain operations is becoming increasingly relevant in recent years. To assist decision-makers in balancing financial and environmental sustainability we present an optimization framework which determines candidate supply chain structures network designs and operational plans. Supply chain structures are assessed with respect to total cost and environmental score, with the latter integrating environmental impacts related to climate change, water usage and energy consumption. A Pareto set of candidate solutions is found which provides insights in complex trade-offs between impact categories and cost: centralized manufacturing is selected to lower unit production cost and better use water resources, whilst decentralized manufacturing improves energy usage. Emissions from CO2 are lowered through cost minimization.
Leonzio G, Chachuat B, Shah N, 2023, Enviro-economic analysis of tandem and direct processes for ethylene electrosynthesis, Computer Aided Chemical Engineering, Pages: 2217-2222
Ethylene is the most important organic chemical in terms of global demand and production capacity. Of the sustainable alternatives to conventional ethylene production based on steam cracking of natural gas and naphtha, both direct electrochemical reduction of CO2 as well as a tandem process consisting of CO2 electro-reduction to CO followed by CO electro-reduction to ethylene have attracted attention. This conference paper presents a comparison between the tandem and direct CO2 electro-reduction processes both from an economic and environmental point of view, including a global sensitivity analysis of key process parameters on production cost and climate change impact. The results depict a clear trade-off between the economic and environmental performance of both electrochemical routes, although the tandem process remains more favorable at the current carbon price of the EU emission trading system (ETS).
Bakkaloglu S, Mersch M, Sunny N, et al., 2023, ECOS 2023: How far should the UK go with negative emission technologies?, Pages: 2939-2949
Negative Emissions Technologies (NETs), such as Bioenergy with Carbon Capture and Storage (BECCS) and Direct Air Carbon Capture and Storage (DACCS), are potentially valuable to offset carbon emissions and therefore commonly deployed in global climate change mitigation scenarios. However, they are controversial and sometimes seen as a means of delaying or avoiding emissions reduction efforts. Nonetheless, the UK has set an ambitious target of engineering 57 Mt CO2 per year of removals by 2050 to achieve net zero emissions[1]. This study uses the UK TIMES, technology-rich bottom-up energy system model to investigate the nationwide deployment of NETs in the energy system, while varying model parameters to provide an overview of decarbonisation in line with the UK's net zero ambitions. We investigated DACCS and BECCS NETs technologies with regards to technological uncertainties and sensitivities. We revised the TIMES model structure for NETs implementation to ensure proper integration with industry. Our analysis estimates that the UK can remove 78.5 Mt CO2 by 2050 under the balanced Net Zero Scenario. However, by integrating an updated characterisation of removal technologies, and enabling tighter integration of DACCS into industrial clusters, we can achieve a removal capacity of up to 209 Mt CO2 by 2050 based on our preliminary results. Additionally, a 50% reduction in DACCS cost could further increase the removal capacity to 218 Mt CO2. This study provides valuable insights for policymakers and stakeholders in the UK and beyond, highlighting how NETs can be integrated in industrial strategy.
Bird M, Acha S, Escriva EJS, et al., 2023, Data-driven Modelling of Supermarket Refrigeration Systems for Model Predictive Control Applications, Pages: 761-768
With uncertainty in energy markets, and the effects of climate change looming, reducing energy use and operational cost of existing building systems is more important than ever. To this end, this paper presents a grey-box modelling approach to characterise the behaviour of chilled and frozen and coldrooms using basic system specifications and measured data. An overall energy balance is used to devise a discrete state space model for each cabinet, characterised by unknown empirical parameters relating to heat capacity and heat transfer properties. Historical system data from a UK supermarket are used in combination with a genetic algorithm optimisation to determine the optimal empirical parameters for 10 display cases and 10 coldrooms. The resulting cabinet temperature predictions have a good level of accuracy, achieving a root-mean squared error (RMSE) of 0.37°C to 0.98°C. Overall this data-driven approach is effective and efficient in modelling refrigeration systems, and can be easily generalised to any system where historical data is available. Finally, the use of the proposed approach in cost minimisation or demand response application is presented.
Triantafyllou N, Shah N, Papathanasiou MM, et al., 2023, Combined Bayesian optimization and global sensitivity analysis for the optimization of simulation-based pharmaceutical processes, Computer Aided Chemical Engineering, Pages: 381-386
We propose an efficient framework that employs Bayesian optimization and global sensitivity analysis for the optimization of detailed pharmaceutical flowsheets. Global sensitivity analysis based on quasi-random sampling is utilized to reduce the dimensionality of the problem by identifying critical process and economic parameters that contribute significantly to the variability of Key Performance Indicators (KPIs) such as batch size and OpEx. Then, Bayesian optimization is performed in the previously identified critical input space based on gaussian process surrogate models and a number of different acquisition functions to find the optimal critical operating conditions that minimize the aforementioned KPIs. We apply this framework to the manufacture of plasmid DNA (pDNA), which is a critical raw material for advanced therapeutics, leading to a surge in demand for pDNA for clinical or commercial use. Optimized manufacturing recipes identified with the proposed framework are projected to achieve an up to 170% increase in the batch size and a 34.7% decrease in the OpEx per batch.
van de Berg D, Jimbo RXJ, Shah N, et al., 2023, Tractable Data-driven Solutions to Hierarchical Planning-scheduling-control, Computer Aided Chemical Engineering, Pages: 649-654
Using numerical optimization for the hierarchical integration of decision-making units is crucial to provide feasibility and optimality of all levels. However, realistically modelling hierarchical decision-making calls for multilevel formulations, which are numerically intractable and mathematically difficult. In this work, we show how to leverage two data-driven techniques – derivative-free optimization and optimality surrogates – to decrease the computational burden of multilevel problems. We reformulate a tri-level planning-scheduling-control problem into a single-level black-box problem wherein each evaluation calls a scheduling instance with embedded optimal control surrogates. We show that solving this integrated problem instead of the single-level instance leads to changes in the optimal production planning and scheduling sequence, and discuss trade-offs associated with both techniques.
Hoseinpoori P, Woods J, Shah N, 2023, An integrated framework for optimal infrastructure planning for decarbonising heating, MethodsX, Vol: 10, Pages: 1-18, ISSN: 2215-0161
This paper presents the HEGIT (Heat, Electricity and Gas Infrastructure and Technology) model for optimal infrastructure planning for decarbonising heating in buildings. HEGIT is an optimisation model based on Mixed Integer Linear Programming. The model co-optimises the integrated operation and capacity expansion planning of electricity and gas grids as well as heating technologies on the consumer side while maintaining the security of supply and subject to different environmental, operational and system-wide constraints. The three main features of the HEGIT model are:• It incorporates an integrated unit commitment and capacity expansion problem for coordinated operation and long-term investment planning of the electricity and gas grids.• It incorporates the flexible operation of heating technologies in buildings and demand response in operation and long-term investment planning of gas and electricity grids.• It incorporates a multi-scale techno-economic representation of heating technologies design features into the whole energy system modelling and capacity planning.These features enable the model to quantify the impacts of different policies regarding decarbonising heating in buildings on the operation and long-term planning of electricity and gas grids, identify the cost-optimal use of available resources and technologies and identify strategies for maximising synergies between system planning goals and minimising trade-offs. Moreover, the multi-scale feature of the model allows for multi-scale system engineering analysis of decarbonising heating, including system-informed heating technology design, identifying optimal operational setups at the consumer end, and assessing trade-offs between consumer investment in heating technologies and infrastructure requirements in different heat decarbonisation pathways.
Hofer M, Criscuolo P, Shah N, et al., 2022, Regulatory policy and pharmaceutical innovation in the United Kingdom after Brexit: initial insights, Frontiers in Medicine, Vol: 9, ISSN: 2296-858X
Brexit was presented as an opportunity to promote innovation by breaking free from the European Union regulatory framework. Since the beginning of 2021 the Medicines and Healthcare products Regulatory Agency (MHRA) has operated as the independent regulatory agency for the United Kingdom. The MHRA's regulatory activity in 2021 was analyzed and compared to that of other international regulatory bodies. The MHRA remained reliant on EU regulatory decision-making for novel medicines and there were significant regulatory delays for a small number of novel medicines in the UK, the reasons being so far unclear. In addition, the MHRA introduced innovation initiatives, which show early promise for quicker authorization of innovative medicines for cancer and other areas of unmet need. Longer-term observation and analysis is needed to show the full impact of post-Brexit pharmaceutical regulatory policy.
Baker W, Acha S, Jennings N, et al., 2022, Decarbonisation of buildings: Insights from across Europe, Decarbonisation of buildings: Insights from across Europe, Publisher: The Grantham Institute
This report considers four key challenges facing the UK in reducing carbon emissions from its building stock, and shares insights from across Europe that have the potential to help the UK to decarbonise and increase the energy efficiency of its buildings.
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.