Enhancing sustainability of chemical plant operations through dual objective holistic optimisation - the case of an integrated ammonia and nitrogen-derivatives production facility
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Date
2009-01-05T07:47:54Z
Authors
Cole, Barrie Michael
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Abstract
In recent years, there has been much improvement in the theory and
application of mathematical optimisation. Optimisation techniques have now
been developed for conditions of uncertainty (fuzzy) and probability
(stochastic) and together with existing methodologies, such as linear
programming and multiple objectivity, a very powerful set of tools is now
available to enable the determination of the ‘best’ solution for most operational
scenarios under a variety of uncertain operating conditions.
Optimisation techniques are currently available for most scenarios involving
conditions of uncertainty, e.g. Fuzzy Optimisation, Stochastic Optimisation
and Multi-Objective Optimisation. However, very few techniques exist for
combinatorial optimisation scenarios, e.g. Stochastic Fuzzy Optimisation and
Multi-Objective Fuzzy Optimisation and only one optimisation technique was
discovered that covered three different conditions of uncertainty, i.e. Multisub-
objective Stochastic Fuzzy Optimisation.
However, in the chemical industry, quite a few production operations exist that
would greatly benefit if an optimisation methodology existed that covered four
different simultaneous conditions of uncertainty, i.e. Multiple Objectivity,
Fuzziness, Stochastics and Minmax (simultaneous maximum and minimum
solution). A case in point is the interrelated production of ammonia (NH3) and
its downstream nitrogen-derivatives such as nitric acid (HNO3), ammonium
nitrate solution (NH4NO3.H2O), ammonium nitrate (NH4NO3) and limestone
ammonium nitrate. Such an operation is characterised by conditions of
Fuzziness (uncertainty in product demand), Stochastics (probability
distribution of hydrogen in coal, one of the ammonia production raw
materials), Multi-objectives (e.g. the need to simultaneously maximise
production in a number of different plants) and Minmax (e.g. the need to
maximise production while simultaneously minimising effluent discharge)
In this research project, a 4 – Way (Multi-sub-objective, Stochastic, Fuzzy,
and Minmax) Optimisation methodology was successfully derived, based on
existing singular optimisation methodologies, and successfully applied to the
interrelated ammonia and downstream nitrogen-derivatives production facility.
The Holistic Optimisation methodology derived could be easily applied to a
wide variety of chemical and operational scenarios.