Imperial College London

ProfessorNilayShah

Faculty of EngineeringDepartment of Chemical Engineering

Head of Department of Chemical Engineering
 
 
 
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Contact

 

+44 (0)20 7594 6621n.shah

 
 
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Assistant

 

Miss Nazma Mojid +44 (0)20 7594 3918

 
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Location

 

ACEX 304/5ACE ExtensionSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
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571 results found

Al-Qahtani A, Parkinson B, Hellgardt K, Shah N, Guillen-Gosalbez Get al., 2021, Uncovering the true cost of hydrogen production routes using life cycle monetisation, Applied Energy, Vol: 281, Pages: 115958-115958, ISSN: 0306-2619

Hydrogen has been identified as a potential energy vector to decarbonise the transport and chemical sectors and achieve global greenhouse gas reduction targets. Despite ongoing efforts, hydrogen technologies are often assessed focusing on their global warming potential while overlooking other impacts, or at most including additional metrics that are not easily interpretable. Herein, a wide range of alternative technologies have been assessed to determine the total cost of hydrogen production by coupling life-cycle assessments with an economic evaluation of the environmental externalities of production. By including monetised values of environmental impacts on human health, ecosystem quality, and resources on top of the levelised cost of hydrogen production, an estimation of the “real” total cost of hydrogen was obtained to transparently rank the alternative technologies. The study herein covers steam methane reforming (SMR), coal and biomass gasification, methane pyrolysis, and electrolysis from renewable and nuclear technologies. Monetised externalities are found to represent a significant percentage of the total cost, ultimately altering the standard ranking of technologies. SMR coupled with carbon capture and storage emerges as the cheapest option, followed by methane pyrolysis, and water electrolysis from wind and nuclear. The obtained results identify the “real” ranges for the cost of hydrogen compared to SMR (business as usual) by including environmental externalities, thereby helping to pinpoint critical barriers for emerging and competing technologies to SMR.

Journal article

Denbow C, Le Brun N, Dowell NM, Shah N, Markides CNet 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.

Journal article

Hart M, Austin W, Acha S, Le Brun N, Markides CN, Shah Net 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

Journal article

ODwyer E, Pan I, Charlesworth R, Butler S, Shah Net 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.

Journal article

Wu N, Zhan X, Zhu X, Zhang Z, Lin J, Xie S, Meng C, Cao L, Wang X, Shah N, Zheng X, Zhao Yet 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

Journal article

Aunedi M, Pantaleo AM, Kuriyan K, Strbac G, Shah Net 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.

Journal article

Cremi MR, Pantaleo AM, van Dam KH, Shah Net 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.

Journal article

Ayoub AN, Gaigneux A, Le Brun N, Acha S, Shah Net al., 2020, The development of a low-carbon roadmap investment strategy to reach Science Based Targets for commercial organisations with multi-site properties, Building and Environment, Vol: 186, Pages: 1-17, ISSN: 0360-1323

The Paris Climate Agreement has motivated commercial organisations to set and work towards Science Based Targets, a realignment of greenhouse gas emissions in line with climate science. This work presents a modelling framework to develop cost-effective decarbonisation investment programs that address electricity and heat carbon emissions in organisations with multiple properties. The case study takes a set of 60 supermarkets in the UK and evaluates the techno-economic viability of installing biomethane combined heat and power engines and photovoltaic panels to make them zero carbon buildings. Simulation results from the batch of buildings offer the financial and environmental benefits at each site and generates a set of regression coefficients which are then applied into an optimisation problem. Solving the optimisation yields the decarbonisation investment strategy for the estate up to 2050; indicating the preferred sequence of investments the company needs to undertake to embark upon an effective low-carbon roadmap. A sensitivity analysis compliments the study to understand how market and policy externalities may influence roadmaps. Results suggest a CAPEX ranging from £57-£80 million is required to deliver an ambitious decarbonisation plan, while OPEX and carbon savings benefits range between £197 and £683 million and 461–715 ktCO2e; respectively. The case study highlights that although carbon targets can be achieved by 2030, the 2050 targets are more challenging to meet; suggesting additional technologies and policies should be considered and implemented. The framework serves as a blueprint of how modelling can assist decision-makers in reducing their carbon footprint cost-effectively to reach Science Based Targets.

Journal article

Le Brun N, Simpson M, Acha S, Shah N, Markides CNet 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.

Journal article

Acha Izquierdo S, Le Brun N, Damaskou M, Fubara TC, Mulgundmath V, Markides C, Shah Net 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.

Journal article

Kis Z, Kontoravdi K, Dey AK, Shattock R, Shah Net 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.

Journal article

Olympios AV, Le Brun N, Acha S, Shah N, Markides CNet 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

Journal article

Jing R, Kuriyan K, Lin J, Shah N, Zhao Yet 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.

Journal article

Guo M, van Dam KH, Touhami NO, Nguyen R, Delval F, Jamieson C, Shah Net 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.

Journal article

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.

Journal article

Georgios M, Emilio Jose S, Acha Izquierdo S, Shah N, Markides Cet 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.

Journal article

Bascone D, Galvanin F, Shah N, Garcia-Munoz Set 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.

Journal article

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

Journal article

Thaore V, Tsourapas D, Shah N, Kontoravdi Cet al., 2020, Techno-Economic Assessment of Cell-Free Synthesis of Monoclonal Antibodies Using CHO Cell Extracts, PROCESSES, Vol: 8

Journal article

Sarabia EJ, Acha Izquierdo S, Le Brun N, Soto V, Jose Manuel P, Shah N, Markides Cet 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.

Conference paper

Hart MBP, Olympios A, Le Brun N, Shah N, Markides C, Acha Izquierdo Set 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.

Conference paper

Alhajaj A, Shah N, 2020, Multiscale design and analysis of CO2 networks, INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL, Vol: 94, ISSN: 1750-5836

Journal article

Pantaleo AM, Camporeale S, Sorrentino A, Miliozzi A, Shah N, Markides Cet 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

Journal article

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

Conference paper

O'Dwyer E, Chen K, Wang H, Wang A, Shah N, Guo Met 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.

Journal article

Langshaw L, Ainalis D, Acha Izquierdo S, Shah N, Stettler Met 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.

Journal article

Papathanasiou MM, Stamatis C, Lakelin M, Farid S, Titchener-Hooker N, Shah Net 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.

Journal article

Kucherenko S, Giamalakis D, Shah N, García-Muñoz Set 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.

Journal article

Thaore VB, Armstrong RD, Hutchings GJ, Knight DW, Chadwick D, Shah Net 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.

Journal article

Moschou D, Papathanasiou MM, Lakelin M, Shah Net al., 2020, Investment Planning in Personalised Medicine, Computer Aided Chemical Engineering, Pages: 49-54

© 2020 Elsevier B.V. Personalised cancer therapies are gaining increasing attention due to their demonstrated clinical potential. Nonetheless, such patient-centric, 1:1 business models encompass significant manufacturing and distribution challenges that are directly associated with the patient schedule. In this work we focus on the development and solution of a mixed-integer optimisation problem to suggest cost-efficient candidate networks that guarantee responsiveness and successful delivery of the therapy. The developed model is tested under two demand scenarios, incorporating economies of scale elements.

Book chapter

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