Enhancing sustainability of chemical plant operations through dual objective holistic optimisation - the case of an integrated ammonia and nitrogen-derivatives production facility - Cole, Barrie Michael (My University, 2009)
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.