pin
pm
pset (a)Scheme of the input stream
pressure adjustment. ∆p=pset−pin(bar) padj = pm − pin (bar) -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 0 0.1 0.2 0.3 0.4 0.5 0.6 parity line pm=pin pm =p set
(b)Graph representing the development of the intermediate pressure between compressor and pressure release valve in dependence of the desired pressure difference.
FIGURE2.8:Example of a flexible and generally applicable input stream pressure adjustment for subsys- tems in a superstructure based process design model.
Both new features increase the flexibility of the applied superstructure while avoiding the introduction of new integer decision variables. Keeping the number of integer decision vari- ables low, reduces the number of evaluations during the evolutionary optimisation approach because less integer variables have to be combined with each other. It also reduces the risk of attaining ill-conditioned process designs which would have to be rejected in a final step.
2.4 Conclusions
This chapter gave an introduction to the process design & optimisation methodology applied and developed at EPFL. Further, the Wood-to-SNG process was presented which stakes out the frame in which this thesis has been developed. A sound basis of a process design model was presented for a case study investigating the integration of a rate based model (fluidised bed methanation reactor model). The experimental experiences and the developed methanation kinetics as well as the fluidised bed methanation reactor model at PSI emphasise the need to further improve the representation of the methanation model embedded in the existing process design model. Larger deviations at low temperature between the results of thermody- namic equilibrium and the developed rate based model further indicate this need. A revision of the process design model has been conducted to allow the later integration of the rate based model into the process design model and required adaptations were made. These were the consideration of ethane in the process flows and the necessary adaptations to the SNG upgrad-
ing system to be able to deal with this compound. Furthermore, with the goal in mind of using the final process design model with integrated rate based model in an optimisation procedure, two new modelling solutions for pressure adjustments in process streams were presented. The two modelling solutions are a 3-lane compressor system and a compressor valve combination with sophisticated transition functions to allow smooth transitions between different states.
With these adaptations of the original process design model, a foundation is set to begin a comparison of the process design characteristics and performances of the solution with inte- grated rate based model and with thermodynamic equilibrium under controlled conditions. The next necessary steps are the revision of the rate based model to make it applicable to the process design & optimisation procedure, the development of its surrogate model, and the integration of the surrogate model into the process design & optimisation methodology, respectively to the process design model.
3
The Rate Based Model
This chapter is based on the manuscript of
Sinan L Teske, Jan Kopyscinski, Tilman J Schildhauer, Simon Maurer, and Serge M A Biollaz. “Validating a Rate Based Model of a Fluidised Bed Methanation Reactor”. In:Manuscript in
preparation(2013)
J. Kopyscinski contributed by identifying the parameters for the new kinetics 3m and by contributing to the discussions about the measured concentration profiles in the lab-scale fluidised bed experiments. S. Maurer contributed by supporting the experiments on the bubble hold-up described in section 3.2.2 and providing figures 3.2a and 3.2b.
This chapter describes the rate based model of the bubbling fluidised bed reactor, which is the object of later surrogate modelling and incorporation into the process design & optimisation tool. It describes the original model and the adaptations and implementations which are necessary for its later implementation.
3.1 Introduction
Catalytic fluidised beds are extensively used in gas-solid applications in which large heat and mass transfer rates are required. The methanation of syngas with a high CO partial pressure is an example of a fast and highly exothermic reaction eq. (3.1). It has been shown that a catalytic fluidised bed reactor is well suited for the conversion of biomass derived producer gas to synthetic natural gas - SNG [63, 89]. Fluidised bed reactors allow for an isothermal one-step operation combining the methanation eq. (3.1) and water gas shift eq. (3.2) reaction. In addition, the movement of the catalyst particles through the bed enables long catalyst stability due to internal regeneration [61].
CO+3 H2−−)−−*CH4+H2O ∆H0R= −206 kJ
mol (3.1)
CO+H2O−−)−−*CO2+H2 ∆H0R= −41 kJ
mol (3.2)
A common approach for engineers in process systems engineering to describe process steps with little or no information is to state the assumption of chemical equilibrium. Thus, maxi- mum theoretical efficiencies and trends (e.g., influence of temperature) can be predicted, how- ever, economic calculation including reactor design might lead to over-optimistic estimates. Especially in multiphase reactors such as fluidised beds, aspects of kinetics, hydrodynamics, and mass transfer influence the reactor performance, reactant conversion, and product selec- tivity [62]. Therefore, a detailed rate based reactor model is desired for application in process modelling and optimisation methodologies as described in chapter 2.
The aim of the work described in this chapter is to check the performance of the rate based model in predicting real world experiments in fluidised bed methanation reactors as they were conducted in earlier stages of the fluidised bed methanation development. In the experimental runs, the partial pressure of the reactants, the volume flow, the catalyst hold-up, and the catalyst dilution were changed. Furthermore, challenges of using axial gas profiles to judge prediction performance of the rate based model are discussed.