562 results found
Denbow C, Le Brun N, Dowell NM, et al., 2020, The potential impact of Molten Salt Reactors on the UK electricity grid, Journal of Cleaner Production, Vol: 276, Pages: 1-18, ISSN: 0959-6526
The UK electricity grid is expected to supply a growing electricity demand and also to cope with electricity generation variability as the country pursues a low-carbon future. Molten Salt Reactors (MSRs) could offer a solution to meet this demand thanks to their estimated low capital costs, low operational risk, and promise of reliably dispatchable low-carbon electricity. In the published literature, there is little emphasis placed on estimating or modelling the future impact of MSRs on electricity grids. Previous modelling efforts were limited to quantifying the value of renewable energy sources, energy storage and carbon capture technologies. To date, no study has assessed or modelled MSRs as a competing power generation source for meeting decarbonization targets. Given this gap, the main objective of this paper is to explore the cost benefits for policy makers, consumers, and investors when MSRs are deployed between 2020 and 2050 for electricity generation in the UK. This paper presents results from electricity systems optimization (ESO) modelling of the costs associated with the deployment of 1350 MWe MSRs, from 2025 onwards to 2050, and compares this against a UK grid with no MSR deployment. Results illustrate a minimum economic benefit of £1.25 billion for every reactor installed over this time period. Additionally, an investment benefit occurs for a fleet of these reactors which have a combined net present value (NPV) of £22 billion in 2050 with a payback period of 23 years if electricity is sold competitively to consumers at a price of £60/MWh.
Hart M, Austin W, Acha S, et al., 2020, A roadmap investment strategy to reduce carbon intensive refrigerants in the food retail industry, Journal of Cleaner Production, Vol: 275, Pages: 1-17, ISSN: 0959-6526
High global warming potential (GWP) refrigerant leakage is the second-highest source of carbon emissions across UK supermarket retailers and a major concern for commercial organizations. Recent stringent UN and EU regulations promoting lower GWP refrigerants have been ratified to tackle the high carbon footprint of current refrigerants. This paper introduces a data-driven modelling framework for optimal investment strategies supporting the food retail industry to transition from hydrofluorocarbon (HFC) refrigeration systems to lower GWP systems by 2030, in line with EU legislation. Representative data from a UK food retailer is applied in a mixed integer linear model, making simultaneous investment decisions across the property estate. The model considers refrigeration-system age, capacity, refrigerant type, leakage and past-performance relative to peer systems in the rest of the estate. This study proposes two possible actions for high GWP HFC refrigeration systems: a) complying with legislation by retrofitting with an HFO blend (e.g. R449-A) or b) installing a new natural refrigerant system (e.g. R744). Findings indicate that a standard (i.e. business-as-usual) investment level of £6 m/yr drives a retrofitting strategy enabling significant reduction in annual carbon emissions of 71% by the end of 2030 (against the 2018 baseline), along with meeting regulatory compliance. The strategy is also highly effective at reducing emissions in the short term as total emissions during the 12-year programme are 59% lower than would have been experienced if the HFC emissions continued unabated. However, this spending level leaves the business at significant risk of refrigeration system failures as necessary investments in new systems are delayed resulting in an ageing, poorly performing estate. The model is further tested under different budget and policy scenarios and the financial, environmental, and business-risk implications are analysed. For example, under a more agg
ODwyer E, Pan I, Charlesworth R, et al., 2020, Integration of an energy management tool and digital twin for coordination and control of multi-vector smart energy systems, Sustainable Cities and Society, Vol: 62, Pages: 1-14, ISSN: 2210-6707
As Internet of Things (IoT) technologies enable greater communication between energy assets in smart cities, the operational coordination of various energy networks in a city or district becomes more viable. Suitable tools are needed that can harness advanced control and machine learning techniques to achieve environmental, economic and resilience objectives. In this paper, an energy management tool is presented that can offer optimal control, scheduling, forecasting and coordination services to energy assets across a district, enabling optimal decisions under user-defined objectives. The tool presented here can coordinate different sub-systems in a district to avoid the violation of high-level system constraints and is designed in a generic fashion to enable transferable use across different energy sectors. The work demonstrates the potential for a single open-source optimisation framework to be applied across multiple energy vectors, providing local government the opportunity to manage different assets in a coordinated fashion. This is shown through case studies that integrate low-carbon communal heating for social housing with electric vehicle charge-point management to achieve high-level system constraints and local government objectives in the borough of Greenwich, London. The paper illustrates the theoretical methodology, the software architecture and the digital twin-based testing environment underpinning the proposed approach.
Wu N, Zhan X, Zhu X, et al., 2020, Analysis of biomass polygeneration integrated energy system based on a mixed-integer nonlinear programming optimization method, Journal of Cleaner Production, Vol: 271, ISSN: 0959-6526
© 2020 Elsevier Ltd The increase of climate disasters and air pollution has caused an urgent need for the clean and low carbon energy transition. In this background, polygeneration represents an innovative and promising concept. The purpose of this study is to provide a generic modelling and optimization strategy to evaluate the polygeneration systems in urban areas. A biomass polygeneration integrated energy system, providing electricity, heating and cooling as well as chemical product, is proposed and evaluated in this work. The feasibility of biomass polygeneration integrated energy system in different regions is also investigated by case study. A mixed-integer nonlinear programming approach has been formulated in General Algebraic Modeling System to address the following issues: a) selection of technologies, types and numbers of equipment to match the energy demand of end users; b) strategic planning and process designing from both economic and environmental perspectives; c) representation of the relationships and trade-offs between the trigeneration and chemical conversion steps; d) operation strategies for biomass polygeneration integrated energy system with time dependent process and boundary conditions. Moreover, the proposed biomass polygeneration integrated energy system is compared to the conventional natural gas-based combined cooling heating and power system as the reference.
Aunedi M, Pantaleo AM, Kuriyan K, et al., 2020, Modelling of national and local interactions between heat and electricity networks in low-carbon energy systems, Applied Energy, Vol: 276, Pages: 1-18, ISSN: 0306-2619
Decarbonisation of the heating and cooling sector is critical for achieving long-term energy and climate change objectives. Closer integration between heating/cooling and electricity systems can provide additional flexibility required to support the integration of variable renewables and other low-carbon energy sources. This paper proposes a framework for identifying cost-efficient solutions for supplying district heating systems within both operation and investment timescales, while considering local and national-level interactions between heat and electricity infrastructures. The proposed optimisation model minimises the levelised cost of a portfolio of heating technologies, and in particular Combined Heat and Power (CHP) and polygeneration systems, centralised heat pumps (HPs), centralised boilers and thermal energy storage (TES). A number of illustrative case studies are presented, quantifying the impact of renewable penetration, electricity price volatility, local grid constraints and local emission targets on optimal planning and operation of heat production assets. The sensitivity analysis demonstrates that the cost-optimal TES capacity could increase by 41–134% in order to manage a constraint in the local electricity grid, while in systems with higher RES penetration reflected in higher electricity price volatility it may be optimal to increase the TES capacity by 50–66% compared to constant prices, allowing centralised electric HP technologies to divert excess electricity produced by intermittent renewable generators to the heating sector. This confirms the importance of reflecting the whole-system value of heating technologies in the underlying cost-benefit analysis of heat networks.
Cremi MR, Pantaleo AM, van Dam KH, et al., 2020, Optimal design and operation of an urban energy system applied to the Fiera Del Levante exhibition centre, Applied Energy, Vol: 275, Pages: 1-22, ISSN: 0306-2619
To move from centralised fossil fuel-based energy systems, synergies between distributed renewable generation, storage and demand-side strategies can be exploited to lower environmental impact and costs. This paper proposes an optimisation model for the techno-economic assessment of energy management strategies with a short-term investment horizon aimed at business managers and decision-makers in the commercial sector. The main novelty is the selection of a combination of on-site technologies and peak shaving strategies to minimise energy costs under time-of-use electricity tariffs, and the adaptation of a general methodology for a specific socio-technical context under seasonal loads. The “Fiera del Levante” exhibition centre in the city of Bari is selected due to the high seasonality of its electricity demand. The optimal solution uses a combined system with photovoltaics, diesel-fired and gas-fired combined-heat-and-power, including part-load operation and electric storage. The cost minimisation scenario reports up to 20% cost savings and 35% carbon emission savings with a 1MWp photovoltaic plant, compared to the baseline. This presents a five-year return on investment of 75%, and levelized cost of energy of €0.14 kWh−1. When coupled with a lithium-ion battery, solar energy brings up to 60% carbon emission savings through load shifting strategies, though this reduces the five-year return on investment by 9%. This hybrid setup is not financially competitive in the Italian retail market, but a hypothetical 25% rise of the grid import prices would make it economically viable. The proposed model is flexible and can be adapted to commercial end-users, providing decision-support in urban energy systems under local conditions.
Le Brun N, Simpson M, Acha S, et al., 2020, Techno-economic potential of low-temperature, jacket-water heat recovery from stationary internal combustion engines with organic Rankine cycles: A cross-sector food-retail study, Applied Energy, Vol: 274, Pages: 1-14, ISSN: 0306-2619
We examine the opportunities and challenges of deploying integrated organic Rankine cycle (ORC) engines to recover heat from low-temperature jacket-water cooling circuits of small-scale gas-fired internal combustion engines (ICEs), for the supply of combined heat and power (CHP) to supermarkets. Based on data for commercially-available ICE and ORC engines, a techno-economic model is developed and applied to simulate system performance in real buildings. Under current market trends and for the specific (low-temperature) ICE + ORC CHP configuration investigated here, results show that the ICE determines most economic savings, while the ORC engine does not significantly impact the integrated CHP system performance. The ORC engines have long payback times (4–9 years) in this application, because: (1) they do not displace high-value electricity, as the value of exporting electricity to the grid is low, and (2) it is more profitable to use the heat from the ICEs for space heating rather than for electricity conversion. Commercial ORC engines are most viable (payback ≈ 4 years) in buildings with high electrical demands and low heat-to-power ratios. The influence of factors such as the ORC engine efficiency, capital cost and energy prices is also evaluated, highlighting performance gaps and identifying promising areas for future research.
Acha Izquierdo S, Le Brun N, Damaskou M, et al., 2020, Fuel cells as combined heat and power systems in commercial buildings: A case study in the food-retail sector, Energy, Vol: 206, Pages: 1-13, ISSN: 0360-5442
This work investigates the viability of fuel cells (FC) as combined heat and power (CHP) prime movers in commercial buildings with a specific focus on supermarkets. Up-to-date technical data from a FC manufacturing company was obtained and applied to evaluate their viability in an existing food-retail building. A detailed optimisation model for enhancing distributed energy system management described in previous work is expanded upon to optimise the techno-economic performance of FC-CHP systems. The optimisations employ comprehensive techno-economic datasets that reflect current market trends. Outputs highlight the key factors influencing the economics of FC-CHP projects. Furthermore, a comparative analysis against a competing internal combustion engine (ICE) CHP system is performed to understand the relative techno-economic characterisitcs of each system. Results indicate that FCs are becoming financially competitive although ICEs are still a more attractive option. For supermarkets, the payback period for installing a FC system is 4.7–5.9 years vs. 4.0–5.6 years for ICEs when policies are considered. If incentives are removed, FC-CHP systems have paybacks in the range 6–10 years vs. 5–8.5 years for ICE-based systems. A sensitivity analysis under different market and policy scenarios is performed, offering insights into the performance gap fuel cells face before becoming more competitive.
Kis Z, Kontoravdi K, Dey AK, et al., 2020, Rapid development and deployment of high-volumevaccines for pandemic response, Journal of Advanced Manufacturing and Processing, Vol: 2, Pages: 1-10, ISSN: 2637-403X
Overcoming pandemics, such as the current Covid‐19 outbreak, requires the manufacture of several billion doses of vaccines within months. This is an extremely challenging task given the constraints in small‐scale manufacturing for clinical trials, clinical testing timelines involving multiple phases and large‐scale drug substance and drug product manufacturing. To tackle these challenges, regulatory processes are fast‐tracked, and rapid‐response manufacturing platform technologies are used. Here, we evaluate the current progress, challenges ahead and potential solutions for providing vaccines for pandemic response at an unprecedented scale and rate. Emerging rapid‐response vaccine platform technologies, especially RNA platforms, offer a high productivity estimated at over 1 billion doses per year with a small manufacturing footprint and low capital cost facilities. The self‐amplifying RNA (saRNA) drug product cost is estimated at below 1 USD/dose. These manufacturing processes and facilities can be decentralized to facilitate production, distribution, but also raw material supply. The RNA platform technology can be complemented by an a priori Quality by Design analysis aided by computational modeling in order to assure product quality and further speed up the regulatory approval processes when these platforms are used for epidemic or pandemic response in the future.
Olympios AV, Le Brun N, Acha S, et al., 2020, Stochastic real-time operation control of a combined heat and power (CHP) system under uncertainty, Energy Conversion and Management, Vol: 216, Pages: 1-17, ISSN: 0196-8904
In this paper we present an effort to design and apply a multi-objective real-time operation controller to a combined heat and power (CHP) system, while considering explicitly the risk-return trade-offs arising from the uncertainty in the price of exported electricity. Although extensive research has been performed on theoretically optimizing the design, sizing and operation of CHP systems, less effort has been devoted to an understanding of the practical challenges and the effects of uncertainty in implementing advanced algorithms in real-world applications. In this work, a two-stage control architecture is proposed which applies an optimization framework to a real CHP operation application involving intelligent communication between two controllers to monitor and control the engine continuously. Since deterministic approaches that involve no measure of uncertainty provide limited insight to decision-makers, the methodology then proceeds to develop a stochastic optimization technique which considers risk within the optimization problem. The uncertainty in the forecasted electricity price is quantified by using the forecasting model’s residuals to generate prediction intervals around each forecasted electricity price. The novelty of the proposed tool lies in the use of these prediction intervals to formulate a bi-objective function that represents a compromise between maximizing the expected savings and minimizing the associated risk, while satisfying specified environmental objectives. This allows decision-makers to operate CHP systems according to the risk they are willing to take. The actual operation costs during a 40–day trial period resulting from the installation of the dynamic controller on an existing CHP engine that provides electricity and heat to a supermarket are presented. Results demonstrate that the forecasted electricity price almost always falls within the developed prediction intervals, achieving savings of 23% on energy costs against
Jing R, Kuriyan K, Lin J, et al., 2020, Quantifying the contribution of individual technologies in integrated urban energy systems – A system value approach, Applied Energy, Vol: 266, ISSN: 0306-2619
Integrated urban energy systems satisfy energy demands in a cost-effective manner by efficiently combining diverse technologies and energy saving strategies. However, the contribution of an individual technology within a complex system is difficult to quantify. This study introduces a generalized “system value” approach to quantify the contribution of an individual design decision towards improving the system design (e.g., achieving a lower cost design). It measures the contribution of an individual technology to the whole system in the range between two benchmarks that respectively represent complete exclusion of the technology and the optimal penetration level. The method is based on a technology-rich Mixed Integer Linear Programming (MILP) model for optimal design of urban energy systems. The model considers multi-energy supply technologies, networks, storage technologies and various energy saving strategies. A stochastic formulation is further developed to quantify uncertainties of the system value. The system values of nine kinds of energy supply technologies and three categories of energy-saving strategies are quantified via a case study, which illustrates the variation in the system values for individual technologies with different levels of penetration, and multi-energy supply technologies can have a large impact in integrated systems.
Lyons B, O'Dwyer E, Shah N, 2020, Model reduction for Model Predictive Control of district and communal heating systems within cooperative energy systems, Energy, Vol: 197, Pages: 1-10, ISSN: 0360-5442
The benefits of applying advanced control approaches such as Model Predictive Control to the building energy domain are well understood. Furthermore, to facilitate the decarbonisation of the sector, district heating, communal heating and heat pumps are set to become more common, leading to a greater need to employ advanced approaches to enable flexible integration with the power grid whereby buildings can provide flexibility services to mitigate grid stress. The development of models that are complex enough to capture the behaviour of large numbers of buildings without introducing excessive computational effort remains a challenge. In this paper, an approach is proposed in which model reduction techniques based on Hankel Singular Value Decomposition are applied in cooperation with state-of-the-art building energy modelling tools to produce models of large numbers of buildings that remain tractable within an MPC framework. The approach is demonstrated using a case study in which a MPC is developed for a 95-flat communal heating system. Centralised and decentralised approaches are considered, particularly in their respective ability to incorporate externally imposed constraints on the supply.
Guo M, van Dam KH, Touhami NO, et al., 2020, Multi-level system modelling of the resource-food-bioenergy nexus in the global south, Energy, Vol: 197, Pages: 1-12, ISSN: 0360-5442
To meet the demands for resources, food and energy, especially in fast developing countries in the Global South, new infrastructure investments, technologies and supply chains are required. It is essential to manage a transition that minimises the impacts on global environmental degradation while benefits local socio-economic development. Food-bioenergy integration optimising natural capital resources and considering wider environmental and socio-economic sustainability offers a way forward. This study presents an integrative approach enabling whole systems modelling to address the interlinkage and interaction of resource-food-bioenergy systems and optimise supply chains considering poly-centric decision spaces. Life cycle sustainability assessment, optimisation, agent-based modelling and simulation were coupled to build an integrated systems modelling framework applicable to the resource-food-bioenergy nexus. The model building blocks are described before their applications in three case studies addressing agricultural residues and macro-fungi in the Philippines, sugar cane biorefineries in South Africa, and Nipa palm biofuel in Thailand. Our case studies revealed the great potential of untapped biomass including agricultural waste and non-food biomass grown on marginal lands. Two value chain integration case studies – i.e. straw-fungi-energy in Philippines and sugar-energy in Africa – have been suggested as sustainable solutions to recover waste as value-added products to meet food and energy security. Case studies highlight how an integrative modelling framework can be applied to address multi-level questions, taking into account decision-making at different levels, which contribute to an overall sustainability goal.
Georgios M, Emilio Jose S, Acha Izquierdo S, et al., 2020, CO2 refrigeration system heat recovery and thermal storage modelling for space heating provision in supermarkets: An integrated approach, Applied Energy, Vol: 264, ISSN: 0306-2619
The large amount of recoverable heat from CO2 refrigeration systems has led UK food retailers to examine the prospect of using refrigeration integrated heating and cooling systems to provide both the space heating and cooling to food cabinets in supermarkets. This study assesses the performance of a refrigeration integrated heating and cooling system installation with thermal storage in a UK supermarket. This is achieved by developing a thermal storage model and integrating it into a pre-existing CO2 booster refrigeration model. Five scenarios involving different configurations and operation strategies are assessed to understand the techo-economic implications. The results indicate that the integrated heating and cooling system with thermal storage has the potential to reduce energy consumption by 17–18% and GHG emissions by 12–13% compared to conventional systems using a gas boiler for space heating. These reductions are achieved despite a marginal increase of 2–3% in annual operating costs. The maximum amount of heat that can be stored and utilised is constrained by the refrigeration system compressor capacity. These findings suggest that refrigeration integrated heating and cooling systems with thermal storage are a viable heating and cooling strategy that can significantly reduce the environmental footprint of supermarket space heating provision and under the adequate circumstances can forsake the use of conventional fossil-fuel (natural gas) boiler systems in food-retail buildings.
Bascone D, Galvanin F, Shah N, et al., 2020, Hybrid mechanistic-empirical approach to the modeling of twin screw feeders for continuous tablet manufacturing, Industrial and Engineering Chemistry Research, Vol: 59, Pages: 6650-6661, ISSN: 0888-5885
Nowadays, screw feeders are popular equipment in the pharmaceutical industry. However, despite the increasing research in the last decade in the manufacturing of powder-based products, there is still a lack of knowledge on the physics governing the dynamic behavior of these systems. As a result, data-driven models have often been used to address process design, optimization, and control applications. In this paper, a methodology for the modeling of twin screw feeders has been suggested. A first order plus dead time model has been developed, where a hybrid mechanistic-empirical approach has been used. Different powders and two screw feeder geometries have been investigated. The model predictions are in good agreement with the experimental measurements when the 35 mm diameter screws are employed. When the 20 mm diameter screws are used, the validity range of the model is limited for the least cohesive powders, suggesting that their screw speed-dependent resistance to flow in small screws requires further investigations.
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
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
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.
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
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.
Alhajaj A, Shah N, 2020, Multiscale design and analysis of CO2 networks, INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL, Vol: 94, ISSN: 1750-5836
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
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.
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
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.
Papathanasiou MM, Stamatis C, Lakelin M, et al., 2020, Autologous CAR T-cell therapies supply chain: challenges and opportunities?, Cancer Gene Therapy, ISSN: 0929-1903
Chimeric antigen receptor (CAR) T cells are considered a potentially disruptive cancer therapy, showing highly promisingresults. Their recent success and regulatory approval (both in the USA and Europe) are likely to generate a rapidly increasingdemand and a need for the design of robust and scalable manufacturing and distribution models that will ensure timely andcost-effective delivery of the therapy to the patient. However, there are challenging tasks as these therapies are accompaniedby a series of constraints and particularities that need to be taken into consideration in the decision-making process. Here, wepresent an overview of the current state of the art in the CAR T cell market and present novel concepts that can debottleneckkey elements of the current supply chain model and, we believe, help this technology achieve its long-term potential.
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.
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.
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.
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.
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.
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