422 results found
Acha S, Mariaud A, Shah N, et al., 2018, Optimal design and operation of distributed low-carbon energy technologies in commercial buildings, Energy, Vol: 142, Pages: 578-591, ISSN: 0360-5442
© 2017 The Authors Commercial buildings are large energy consumers and opportunities exist to improve the way they produce and consume electricity, heating and cooling. If energy system integration is feasible, this can lead to significant reductions in energy consumption and emissions. In this context, this work expands on an existing integrated Technology Selection and Operation (TSO) optimisation model for distributed energy systems (DES). The model considers combined heat and power (CHP) and organic Rankine cycle (ORC) engines, absorption chillers, photovoltaic panels and batteries with the aim of guiding decision makers in making attractive investments that are technically feasible and environmentally sound. A retrofit case study of a UK food distribution centre is presented to showcase the benefits and trade-offs that integrated energy systems present by contrasting outcomes when different technologies are considered. Results show that the preferred investment options select a CHP coupled either to an ORC unit or to an absorption chiller. These solutions provide appealing internal rates of return of 28–30% with paybacks within 3.5–3.7 years, while also decarbonising the building by 95–96% (if green gas is used to power the site). Overall, the TSO model provides valuable insights allowing stakeholders to make well-informed decisions when evaluating complex integrated energy systems.
Bieber N, Ker JH, Wang X, et al., 2018, Sustainable planning of the energy-water-food nexus using decision making tools, ENERGY POLICY, Vol: 113, Pages: 584-607, ISSN: 0301-4215
Heuberger CF, Rubin ES, Staffell I, et al., 2018, Corrigendum to "Power capacity expansion planning considering endogenous technology cost learning" [Appl. Energy 204 (2017) 831-845], Applied Energy, ISSN: 0306-2619
Quek V, Shah N, Chachuat B, 2018, Modeling for design and operation of high-pressure membrane contactors in natural gas sweetening, Chemical Engineering Research and Design, ISSN: 1744-3598
Over the past decade, membrane contactors (MBC) for CO2 absorption have been widely recognized for their large intensification potential compared to conventional absorption towers. MBC technology uses microporous hollow-fiber membranes to enable effective gas and liquid mass transfer, without the two phases dispersing into each other. The main contribution of this paper is the development and verification of a predictive mathematical model of high-pressure MBC for natural gas sweetening applications, based on which model-based parametric analysis and optimization can be conducted. The model builds upon insight from previous modeling studies by combining 1-d and 2-d mass-balance equations to predict the CO2 absorption flux, whereby the degree of membrane wetting itself is calculated from the knowledge of the membrane pore-size distribution. The predictive capability of the model is tested for both lab-scale and pilot-scale MBC modules, showing a close agreement of the predictions with measured CO2 absorption fluxes at various gas and liquid flowrates, subject to a temperature correction to account for the heat of reaction in the liquid phase. The results of a model-based analysis confirm the advantages of pressurized MBC operation in terms of CO2 removal efficiency. Finally, a comparison between vertical and horizontal modes of operation shows that the CO2 removal efficiency in the latter can be vastly superior as it is not subject to the liquid static head and remediation strategies are discussed.
Triantafyllidis CP, Koppelaar RHEM, Wang X, et al., 2018, An integrated optimisation platform for sustainable resource and infrastructure planning, Environmental Modelling and Software, Vol: 101, Pages: 146-168, ISSN: 1364-8152
© 2017 The Authors It is crucial for sustainable planning to consider broad environmental and social dimensions and systemic implications of new infrastructure to build more resilient societies, reduce poverty, improve human well-being, mitigate climate change and address other global change processes. This article presents resilience.io, 2 a platform to evaluate new infrastructure projects by assessing their design and effectiveness in meeting growing resource demands, simulated using Agent-Based Modelling due to socio-economic population changes. We then use Mixed-Integer Linear Programming to optimise a multi-objective function to find cost-optimal solutions, inclusive of environmental metrics such as greenhouse gas emissions. The solutions in space and time provide planning guidance for conventional and novel technology selection, changes in network topology, system costs, and can incorporate any material, waste, energy, labour or emissions flow. As an application, a use case is provided for the Water, Sanitation and Hygiene (WASH) sector for a four million people city-region in Ghana.
Wang X, Guo M, Koppelaar RHEM, et al., 2018, A nexus approach for sustainable urban Energy-Water-Waste systems planning and operation., Environ Sci Technol
Energy, water and waste systems analyzed at a nexus level is key to move towards more sustainable cities. In this paper, the "resilience.io" platform is developed and applied to emphasize on waste-to-energy pathways, along with the water and energy sectors, aiming to develop waste treatment capacity and energy recovery with the lowest economic and environmental cost. Three categories of waste including wastewater (WW), municipal solid waste (MSW) and agriculture waste are tested as the feedstock for thermochemical treatment via incineration, gasification or pyrolysis for combined heat and power generation, or biological treatment such as anaerobic digestion (AD) and aerobic treatment. A case study is presented for Ghana in Sub-Saharan Africa, considering a combination of waste treatment technologies and infrastructure, depending on local characteristics for supply and demand. The results indicate that the biogas generated from waste treatment turns out to be a promising renewable energy source in the analyzed region, while more distributed energy resources can be integrated. A series of scenarios including the business-as-usual, base case, natural constrained, policy interventions and environmental and climate change impacts demonstrate how simulation with optimization models can provide new insights in the design of sustainable value chains, with particular emphasis on whole-system analysis and integration.
Zheng X, Wu G, Qiu Y, et al., 2018, A MINLP multi-objective optimization model for operational planning of a case study CCHP system in urban China, APPLIED ENERGY, Vol: 210, Pages: 1126-1140, ISSN: 0306-2619
del Rio-Chanona EA, Liu J, Wagner JL, et al., 2018, Dynamic modeling of green algae cultivation in a photobioreactor for sustainable biodiesel production, BIOTECHNOLOGY AND BIOENGINEERING, Vol: 115, Pages: 359-370, ISSN: 0006-3592
del Rio-Chanona EA, Zhang D, Shah N, 2018, Sustainable biopolymer synthesis via superstructure and multiobjective optimization, AICHE JOURNAL, Vol: 64, Pages: 91-103, ISSN: 0001-1541
Al-Ansari T, Korre A, Nie Z, et al., 2017, Integration of greenhouse gas control technologies within the energy, water and food nexus to enhance the environmental performance of food production systems, JOURNAL OF CLEANER PRODUCTION, Vol: 162, Pages: 1592-1606, ISSN: 0959-6526
Bhave A, Taylor RHS, Fennell P, et al., 2017, Screening and techno-economic assessment of biomass-based power generation with CCS technologies to meet 2050 CO2 targets, APPLIED ENERGY, Vol: 190, Pages: 481-489, ISSN: 0306-2619
Borello D, Pantaleo AM, Caucci M, et al., 2017, Modeling and Experimental Study of a Small Scale Olive Pomace Gasifier for Cogeneration: Energy and Profitability Analysis, ENERGIES, Vol: 10, ISSN: 1996-1073
Cardenas-Fernandez M, Bawn M, Hamley-Bennett C, et al., 2017, An integrated biorefinery concept for conversion of sugar beet pulp into value-added chemicals and pharmaceutical intermediates, FARADAY DISCUSSIONS, Vol: 202, Pages: 415-431, ISSN: 1359-6640
Chen W, Sharifzadeh M, Shah N, et al., 2017, Implication of Side Reactions in Iterative Biopolymer Synthesis: The Case of Membrane Enhanced Peptide Synthesis, INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, Vol: 56, Pages: 6796-6804, ISSN: 0888-5885
Crémel S, Guo M, Bustos-Turu G, et al., 2017, Optimal design of urban energy systems with demand side management and distributed generation, Pages: 2371-2376, ISSN: 1570-7946
© 2017 Elsevier B.V. To tackle prominent societal challenges such as increasing energy demands and climate change due to greenhouse gas (GHGs) emissions demand side management (DSM) and distributed generation (DG) have been proposed as effective solutions particularly for urban areas with high energy densities and diverse types of energy demands. However, urban energy systems are complex, involving supply-demand interconnections, interaction of whole system level with various stakeholders (e.g. end-users, centralised suppliers) and regulation effects of policy instruments. The potential roles of integrated DSM and DG for the climate change mitigation under the urban energy system context haven been yet well understood. Our research aims to advance the understanding of such promising urban energy solutions and generate new insights via modelling framework development. In this study, an optimisation model is developed to simulate the combined effects of DSM and DG strategies in the optimal design of urban energy systems, and investigate the trade-offs between environmental and economic targets. The results of our case study on a hypothetical urban area suggest that the effects of just DSM on climate change mitigation are relatively low whereas urban system would benefit significantly from the introduction of more carbon efficient and economically competitive DG technologies. The set of Pareto optimal solutions derived from the model provide insights into the trade-offs between conflicting GHG and economic objectives: the environmentally optimal solutions with up to 39-43% of the GHG reduction are derived at the expenses of a cost increase by 73-87%; relatively cost efficient systems with marginal increase in economic profiles (4-5%) but significant GHG reductions (32-33%) are achievable. This study demonstrates the insights such model could provide for the decision-making and paradigm shifts towards sustainable urban energy systems and smart operational strategie
Delangle A, Lambert RSC, Shah N, et al., 2017, Modelling and optimising the marginal expansion of an existing district heating network, ENERGY, Vol: 140, Pages: 209-223, ISSN: 0360-5442
Elahi N, Shah N, Korre A, et al., 2017, Multi-stage stochastic optimisation of a CO2 transport and geological storage in the UK, 13th International Conference on Greenhouse Gas Control Technologies (GHGT), Publisher: ELSEVIER SCIENCE BV, Pages: 6514-6525, ISSN: 1876-6102
Farzad S, Mandegari MA, Guo M, et al., 2017, Multi-product biorefineries from lignocelluloses: a pathway to revitalisation of the sugar industry?, BIOTECHNOLOGY FOR BIOFUELS, Vol: 10, ISSN: 1754-6834
Foster E, Contestabile M, Blazquez J, et al., 2017, The unstudied barriers to widespread renewable energy deployment: Fossil fuel price responses, ENERGY POLICY, Vol: 103, Pages: 258-264, ISSN: 0301-4215
Georgiou S, Acha S, Shah N, et al., 2017, Assessing, Benchmarking and Analyzing Heating and Cooling Requirements for Glasshouse Food Production: A Design and Operation Modelling Framework, Pages: 164-172, ISSN: 1876-6102
© 2017 The Authors. Published by Elsevier Ltd. Growing populations, increase in food demand, society's expectations for out of season products and the dependency of the food system on fossil fuels stress resources due to the requirements for national production and from importation of products from remote origins. Quantifying the use of resources in food production and their environmental impacts is key to identifying distinctive measures which can develop pathways towards low carbon food systems. In this paper, a modelling approach is presented which can quantify the energy requirements of heated glasshouse food production. Based on the outputs from the model, benchmarking and comparison among different glasshouse types and growers is possible. Additionally, the effect of spatial and annual weather trends on the heating and cooling requirements of glasshouses are quantified. Case study results indicate that a reduction in heating requirements of about 50%, and therefore an equivalent carbon footprint reduction, can be achieved by replacing a single glass sealed cover with a double glass sealed cover.
Hankin A, Shah N, 2017, Process exploration and assessment for the production of methanol and dimethyl ether from carbon dioxide and water, SUSTAINABLE ENERGY & FUELS, Vol: 1, Pages: 1541-1556, ISSN: 2398-4902
Heuberger CF, Rubin ES, Staffell I, et al., 2017, Power Generation Expansion Considering Endogenous Technology Cost Learning, Pages: 2401-2406, ISSN: 1570-7946
© 2017 Elsevier B.V. We present a mixed-integer linear formulation of a long-term power generation capacity expansion problem including endogenous learning of technology investment cost. We consider a national-scale power system composed of up to 2000 units of 15 different power supply technologies, including international interconnectors for electricity import and export, and grid-level energy storage. We reformulate the non-convex learning curve model into a piecewise linear representation of the cumulative investment cost as a function of cumulative installed capacity. The model is applied to a power system representative of Great Britain for the years 2015 to 2050. We find that the consideration of technology cost learning rate influences the optimal capacity expansion and has systemic implications on the profitability of the power units.
Heuberger CF, Rubin ES, Staffell I, et al., 2017, Power capacity expansion planning considering endogenous technology cost learning, APPLIED ENERGY, Vol: 204, Pages: 831-845, ISSN: 0306-2619
Heuberger CF, Staffell I, Shah N, et al., 2017, A systems approach to quantifying the value of power generation and energy storage technologies in future electricity networks, COMPUTERS & CHEMICAL ENGINEERING, Vol: 107, Pages: 247-256, ISSN: 0098-1354
Heuberger CF, Staffell I, Shah N, et al., 2017, The changing costs of technology and the optimal investment timing in the power sector
Heuberger CF, Staffell I, Shah N, et al., 2017, What is the Value of CCS in the Future Energy System?, 13th International Conference on Greenhouse Gas Control Technologies (GHGT), Publisher: ELSEVIER SCIENCE BV, Pages: 7564-7572, ISSN: 1876-6102
Heuberger CF, Staffell I, Shah N, et al., 2017, An MILP modeling approach to systemic energy technology valuation in the 21st century energy system, 13th International Conference on Greenhouse Gas Control Technologies (GHGT), Publisher: ELSEVIER SCIENCE BV, Pages: 6358-6365, ISSN: 1876-6102
Karatayev M, Rivotti P, Mourao ZS, et al., 2017, The water-energy-food nexus in Kazakhstan: challenges and opportunities, General Assembly of European-Geosciences-Union-Energy-Resources-and-Environment-Division, Publisher: ELSEVIER SCIENCE BV, Pages: 63-70, ISSN: 1876-6102
Khor CS, Elkamel A, Shah N, 2017, Optimization methods for petroleum fields development and production systems: a review, OPTIMIZATION AND ENGINEERING, Vol: 18, Pages: 907-941, ISSN: 1389-4420
Klymenko OV, Kucherenko S, Shah N, 2017, Constrained Global Sensitivity Analysis: Sobol' indices for problems in non-rectangular domains, 27th European Symposium on Computer-Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 151-156, ISSN: 1570-7946
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