The development of large?scale syngas networks in the Rotterdam harbour area with agent?based modelling: A comparison between black?box and grey?box modelling

The development of large?scale syngas networks in the Rotterdam harbour area with agent?based modelling: A comparison between black?box and grey?box modelling

Goosens, F.J.

Nikolic, I. (mentor)
Stikkelman, R.M. (mentor)
Grievink, J. (mentor)

Applied Sciences

Product and Process Engineering

Chemical Engineering

2010-06-28

The thesis research was conducted at the section E&I (energy and industry) of the faculty of Technology, Policy and Management. The world around us is complex and this complexity is only expected to increase as technological development spurs on. This complexity arises from social and technical parts that interact with each other and co?evolve over time, resulting in emergent system behaviour and structure. Today’s industrial systems are interesting examples of socio?technical systems that contain large aggregates of technical components and actors that make economic and strategic decisions, which shape the physical world. It is impossible to predict or steer future developments of these systems because of the non?linear interaction and feedback loops between the different social and technical components. However, insight about the fundamental behavioural modes and possible evolutionary pathways can be gained by building a computer model. In this thesis agent?based modelling (ABM) was used; in ABM, an agent represents an independent socio?technical component in the system. It has a state that represents the physical and economic assets and a behavioural component in which reasoning and decision?making takes place which in turn influence the state of the agent and interactions with the outside world. Maasvlakte II, the new extension of the Rotterdam harbour area that is currently under construction is an ideal case study to expand experience with ABM; the ambition of the Port of Rotterdam is to realise sustainable chemical facilities, like a synthesis gas cluster that uses different types of feedstock to produce a variety of clean end products, like fuels and value?added chemicals. The problem with previously built ABMs is that the technical detail represented is too limited to apply it to syngas networks; the technical part of the agents is currently modelled as a black box and generic facilities are taken as a starting point. The question is whether this lack of detail makes a significant difference for the structure of the syngas cluster that evolves and the agent decision?making. The main question of the research was therefore: “What is the added value of Agent based modelling of large scale syngas networks at Maasvlakte II with ‘grey?box’ models representing syngas technologies instead of black?box models?” The research method consisted of a literature study of the different syngas technologies and building the agent?based model. Developing the ABM entails conceptualisation and formalisation of the syngas technologies in an ontology (the system decomposition method), making a storyboard of the agent’s behaviour and transcribing this to (pseudo?)code. There was unfortunately not enough time left for full implementation and running of the model. The main added detail that was proposed is a description of the composition of the gasifier feedstock and syngas, and a more detailed description of technologies that may influence this composition; i.e. treatment units and reactors are described separately, and descriptions of reactors are diversified to several reactors that produce low or high quality syngas. The general conclusion from the research is that the expected added value of adding technical detail to the black box descriptions of syngas technologies is related to the increased realism of network connections, while unfeasible connections are ruled out by the constraints that are imposed by adding technical detail in describing different reactor types and including the syngas composition. The description of treatment units and impurities in the composition of streams also make it better possible to evaluate the sustainability of the system and economic viability of routes from feedstock to end product. The amount of work that should is involved in adding technical detail to the agentbased model is however considerable, and the added value is partly offset by the problems that were found during the research. The three main problems are: There is a myriad of different syngas technologies, and it is very easy to get lost in the details, while it is hard to conceptualise them and formalise them. This is because all detail levels are somehow connected. The major problem of this class was to decide how the mass balances should be dealt with; the optimal solutions lies in between using a few standard input and output compositions without calculating anything, or detailed calculation of the composition as is done with flowsheeting programs like ASPEN. The second main problem was that the technical detail added does also imply that agents will have to reason about the design criteria that are added, which means that the more technical detail is added, the more (pseuco?)code has to be written to capture agent reasoning and decision?making. The final main problem was that in some cases this reasoning and decision?making is so complex that it can hardly be captured in (pseudo?)code, for example strategic behaviour and contract negotiation. The largest danger is falling in the trap of (having the intention of) adding too much detail. The main recommendation is thus to define the level of detail per case study, and at a level relevant for the context of that case study; it is better to have a partial model than no model at all. For the research of syngas network evolution over time one should focus on the interface between syngas producing and syngas consuming technologies, which means including the composition of syngas and factors that influence this composition, like different reactor types and gas treatment technology. When evaluating the sustainability of a syngas network, one should also include pre?treatment of gasifier feedstock. A second recommendation is to conduct a parameter sweep for certain variables of which it is unsure how they influence the decision?making of the agents or when the behaviour of the agents is too complex to capture with simple (pseudo?)code. The final recommendation to be made when conducting agent?based modelling is to be aware of the fragile balance between too much and too few detail; the system should be defined in such an extent that the behaviour of the agents is restricted in a realistic way while leaving enough degrees of freedom for the system to exhibit complex and emergent phenomena. Future research should focus on solving the problems with mass balance calculations by taking a chemical engineering point of view and learning from how flowsheeting programs have tackled these problems previously, and figure out what the breath and depth of the interplay is between technological details, social decision?making, and economic aspects of the model.

agent-based modelling
syngas networks
Maasvlakte II
synthesis gas

http://resolver.tudelft.nl/uuid:bb190508-8b9e-4e56-a28e-9a9a25070a1c

2010-07-01

Student theses

master thesis

(c) 2010 Goosens, F.J.