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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 in DKUM: 04.05.2015; Views: 1682; Downloads: 141
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Abstract: This paper provides an overview of software tools based on long experience andapplications in the area of process integration, modelling and optimisation. The first part reviews the current design practice and the development of supporting software tools. Those are categorised as: (1) process integration and retrofit analysis tools, (2) general mathematical modelling suites with optimisation libraries, (3) flowsheeting simulation and (4) graph-based process optimisation tools. The second part covers an assessment of tools which enable the generation of new sustainable alternatives to adapt to the future needs. They deal with waste, environment, energy consumption, resources depletion and production cost constrains. The emphasis of the sustainable process design tools is largely on the evaluation of process viability under sustainable economic conditions, synthesis of sustainable process and supply chain process maintenance and life cycle analysis. Major software tools development and the potential of the research-based tools for sustainable process design task are overviewed in theconcluding part.
Keywords: software tools, process integration, process modelling, process optimisation, energy saving
Published in DKUM: 01.06.2012; Views: 1866; Downloads: 118
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Abstract: This thesis presents two different approaches to the synthesis of regional networks for biomass and biofuel production and supply: Mathematical Programming and Graph Theoretic approach. The optimisation criterion for both approaches is the maximisation of profit. The first approach is based on a generic optimisation model of biomass production and supply networks. This superstructure approach is based on a flexible number of network layers: plantation, collection using a pre-treatment, process, and consumption. A Mixed Integer Linear Programming (MILP) model has been successfully developed during this work. However, the solution of this biomass production network model is very challenging due to the large sizes of the networks and the number of interconnections. The huge number of redundant variables reduces model efficiency (time taken to solve the model and the interpretation of the results). This model when representing very large size networks cannot be solved over a reasonable time even by professional mathematical programming software tools. Several model-size reduction techniques are therefore proposed for the solution of large-scale networks. In particular, methods are proposed for (i) reducing the connectivity within a biomass supply chain network by setting the maximum allowable distance between the supply zones to the collection centres, (ii) eliminating unnecessary variables and constrains to reduce the zero-flows in the full model, and (iii) aggregating the network and hence the synthesis process by merging the collection centres. The network synthesis is also carried out by P-graph (Process Graph) tools. P-graph is a directed bipartite graph, having two types of vertices — one for operating units and another for those objects representing material or energy flows/quantities. In this procedure, firstly a maximum feasible superstructure for biomass production network is generated from which the optimal structure is then selected by the Branch and Bound method. This graph-based method clearly shows where, how, and what kind of material and energy carriers will be transferred from one supply chain layer to another. In order to test the efficiency of the model, a small regional renewable network problem was solved using both methods. Their performances were tested and the results confirmed the applicability on a regional scale. The proposed model-size reduction techniques were also tested. A large-scale regional case study was created to demonstrate these techniques. The results are very positive and some suggestions for future work are given in the conclusion.
Keywords: Biomass and bioenergy network synthesis, Model-size reduction techniques, Mathematical Programming, MILP, P-Graph
Published in DKUM: 06.01.2011; Views: 3304; Downloads: 120
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