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1.
SYNTHESIS OF PROCESSES AND PROCESS SUBSYSTEMS FOR ENTIRE LIFETIME
Andreja Nemet, 2015, doctoral dissertation

Abstract: Economically viable process designs should be, in addition to other criteria, profitable over their entire process lifetimes not only at the present time. An improved process design can be achieved by establishing an appropriate trade-off between product income, raw material, operating costs, and investment. The full lifetime of the processes and future prices have to be considered rather than optimising them on a yearly basis using current prices. Single-period optimisation and synthesis models for processes reflects current prices only. The prices can fluctuate rather quickly and the optimal solution may be very different from one year to the another. Therefore, the traditional superstructural synthesis approach applying a mixed-integer nonlinear programming model was upgraded: i) over time, by considering an entire lifetime, which can be described by a multi-period model and ii) the whole field of variation regarding uncertain future prices. A stochastic approach considering the statistical distribution of price projections over an entire lifetime was used on different case studies instead of the traditional deterministic approach accounting for nominal future price projection. The objective was the maximisation of the expected net present value of a process or the expected incremental net present value of different process subsystem. The heat exchanger network has been one of the subsystem, which can significantly contribute to operating costs due to savings of external utility consumption. For this subsystem a deterministic and stochastic multi-period mixed-integer nonlinear programming (MINLP) synthesis models have been developed in order to account for future price projections. Considering higher energy prices gives rise to larger initial investments compared to solutions obtained with current prices. However, due to the uncertainties of utility prices' forecasts, retrofitting using an extension of HEN during future years of the lifespan might be a better strategy. The objective is to identify a design that is the most suitable for effective future extensions and preferably with the lowest sensitivity to energy price fluctuations, as there can be various designs featuring similar initial investment. The results supports that it is economically beneficial to consider future utility prices as the incremental investment is not only paid-off but additional savings are achieved. Process-to-process Heat Integration can also significantly affect the trade-off between investment and operating cost. The aim of Total Site (TS) HEN synthesis was to develop a model synthesis for the TS that, besides many other important features, would also consider future utility prices. Two strategies for TS synthesis have been developed: i) sequential, when HI is performed within a process during the first step and then after a process-to-process HI has been performed, and ii) simultaneous, where the HI is performed within and between processes simultaneously. The second strategy can reveal additional opportunities for heat recovery that might not be identified when applying the first strategy. Comparison of the results obtained at consideration of current utility prices and forecasted utility prices indicates that is worth to account for future utility prices. The separation processes also consume a significant amount of energy. The synthesis of a distillation column sequence integrated within its heat exchanger network was used as a case study for the separation of a multi-component stream into pure component products by considering future utility prices. This analysis has been performed in order to evaluate the magnitude of the influence of forecasted utility prices. It can be concluded that forecasted utility prices can be beneficial, however, the technical limits of the systems should be carefully observed. The price fluctuation can also be observed for other prices not only utility prices, e.g. raw material cost, product price, etc
Keywords: future prices, forecasted prices, stochastic optimisation, mathematical programming, Heat Exchanger Network, Total Site, distillation column sequence, methanol production
Published: 04.05.2015; Views: 1223; Downloads: 104
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2.
Multi-criteria optimization in a methanol process
Anita Kovač Kralj, Peter Glavič, 2009, original scientific article

Abstract: Opportunities for additional profit in retrofits depend very much on the existing plant structure, its parameters and energy system. Combined production of heat flow rate, power and chemical products can improve process efficiency. This paper presents an application of the nonlinear programming (NLP) optimization techniques, including increased chemical product output, heat integration and electricity cogeneration by changing amount flow ratios of raw material, and modifying the separation and reaction systems. The existing NLP model has been extended with basic chemical kinetics, including the effects of changing raw material flow rate ratios on product yield. A case studied methanol plant was optimized using the NLP model developed earlier by including an additional flow rate of hydrogen (H2), decreasing flowrate of high-pressure steam in crude methanol recycling, and increasing methanol production by 2.5%. The potential additional profit from the cogeneration and additional methanol production was estimated to be 2.51 MEUR/a.
Keywords: chemical processes, methanol, simultaneous optimization, NLP, cogeneration, flow rate ratios
Published: 01.06.2012; Views: 1461; Downloads: 83
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3.
H2 separation and use in fuel cells and CO2 separation and reuse as a reactant in the existing methanol process
Anita Kovač Kralj, Peter Glavič, 2007, original scientific article

Abstract: Fuel-cell efficiencies yield substantial reductions in the emissions of climate-change gases and promise an end to exclusive reliance on carbon fuels for energy. Fuel cells, CO2 reuse, process heat integration, and open gas turbine electricity cogeneration can be optimized simultaneously, using a nonlinear programming (NLP) algorithm. The simplified NLP model contains equations of structural and parametric optimization. This NLP model is used tooptimize complex and energy-intensive continuous processes. This procedure does not guarantee a global cost optimum, but it does lead to good, perhaps near-optimum, designs. The plant, which produces methanol, has a surplus of hydrogen (H2) and CO2 flow rates in purge gas. H2 is separated from the purge gas by an existing pressure swing adsorption (PSA) column. Pure H2 can be usedas fuel in fuel cells. CO2 can be separated from the outlet stream (purge gas) by a membrane or absorption system (absorber and regenerator) or an adsorption system and reused as a reactant in a reactor system. Therefore, theproduct yield can be increased and CO2 emissions can be reduced, simultaneously. CO2 emissions can then be reduced at the source. The retrofitted process can be operated within existing parameters. Using a methanol process as a case study, the CO2 emission flow rate can be reduced by4800 t/a. The additional electricity cogeneration in the gas turbine and in fuel cells and additional flow rates of the raw material could generate an additional profit of 2.54 MEUR/a.
Keywords: chemical processing, methanol production, optimization, nonlinear programming, CO2 reuse, fuel cells, heat integration, energy cogeneration
Published: 31.05.2012; Views: 1920; Downloads: 70
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4.
CO2 separation from purge gas and flue gas in the methanol process, using NLP model optimization
Anita Kovač Kralj, Peter Glavič, 2007, original scientific article

Abstract: The concentration of CO2 in the atmosphere has to be stabilized, requiring a reduction in current emission rates in existing plants. This will be done by reducing the environmental burden imposed in such areas as materials input andCO2 emission reduction and using cleaner production, resources, and energy recycling. Any opportunities for emission reduction and CO2 reuse largely depend on existing plant and energy systems. CO2 can be separated from the outlet stream (purge gas) and from flue gas by a membrane or absorption system(absorber and regenerator) or adsorption system and reused as a reactantin a reactor system. Therefore, product yield can be increased and CO2emissions reduced, simultaneously. CO2 emissions can be reduced at the source. The authors of this paper studied CO2 reuse in a methanol process, in which electricity can be generated using an open gas turbine, followed by a separator. Simultaneous optimization of a process structure and its parametersusing simplified nonlinear programming (NLP) ensures an additional annual profit, influenced by reusing the flow rate of CO2. The additional electricity cogeneration and additional flow rates of the raw material could generate an additional profit of 2.79 MEUR/a.
Keywords: chemical processing, methanol production, optimization, nonlinear programming, CO2 emissions, CO2 reuse
Published: 31.05.2012; Views: 1515; Downloads: 71
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5.
Optimization of a gas turbine in the methanol process, using the NLP model
Anita Kovač Kralj, Peter Glavič, 2007, original scientific article

Abstract: Heat and power integration can reduce fuel usage, CO2 and SO2 emissions and, thereby, pollution. In the simultaneous heat and power integration approach and including additional production, the optimization problem is formulated using a simplified process superstructure. Nonlinear programming (NLP) contains equations which enable structural heat and power integration and parametric optimization. In the present work, the NLP model is formulated as an optimum energy target of process integration and electricity generation using a gas turbine with a separator. The reactor acts as a combustion chamber of the gas turbine plant, producing high temperature. The simultaneous NLP approach can account for capital cost, integration of combined heat and power, process modification, and additional production trade-offs accurately, and can thus yield a better solution. It gives better results than non-simultaneous methods. The NLP model does not guarantee a global cost optimum, but it does lead to good, perhaps near optimum designs. This approach is illustrated by an existing, complex methanol production process. The objective function generates a possible increase in annual profit of 1.7 M EUR/a.
Keywords: chemical processes, methanol, simultaneous optimization, NLP, cogeneration, gas turbine
Published: 31.05.2012; Views: 1639; Downloads: 77
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6.
Energy saving and modifications in the methanol process, using the NLP model optimization
Anita Kovač Kralj, Peter Glavič, 2006, published scientific conference contribution

Abstract: The opportunities for additional profit depend very much on the existing plant and energy system. Heat and power integration can reduce fuel usage in chemical processes. Nonlinear programming contains equations which enable structural and parametric optimization. The NLP model is formulated using an optimum energy target of process integration and electricity generation using a gas turbine with separator. The reactor acts as a combustion chamber of the gas turbine plant, producing a lot of energy. The simultaneous NLP approach can account for capital cost, integration of combined heat and power, process modification and additional production of trade-offs, and can thus yield a better solution. The combined production of electricity, heat and chemical products can lead to better process efficiency. The methanol plant was optimized using a mathematical nonlinear programming model by including an additional flowrate of hydrogen in crude methanol recycle and increasing the methanol production by 2,5%. The electricity can be generated in methanol recycle using a gas turbine. The total additional profit is 2,5 MEUR/a.
Keywords: chemical engineering, methanol production, simultaneous process optimization, nonlinear programming, cogeneration, product increase
Published: 30.05.2012; Views: 1867; Downloads: 25
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