Energy Efficiency and Integration in the Refining and Petrochemical Industries
Industrial sites and their associated energy systems are estimated to be responsible for 31% of worldwide energy consumption. Improving their energy efficiencies has the potential to reduce production costs of industrial sites and contribute towards the 2050 CO2 emission targets. Energy efficiency and integration studies in industrial sites aim to reduce the import of energy from external sources and maximise the use of internal energy sources, thereby reducing overall losses. As refineries and petrochemical sites are major energy consumers and are often located close to each other, they offer substantial potential for synergies and Energy Integration solutions. This thesis explores the energy requirements of these two industries and the elaboration of methodologies to identify energy efficiency solutions tailored to them. Data collection, reconciliation and preparation make up the first three chapters of this work. Typical refining and petrochemical clusters are described in detail revealing significant data issues. Data reconciliation methods are adapted to the specificities of these industries to close mass and energy balances and calculate unknowns including losses. To facilitate complex engineering studies, a methodology to identify scenarios from large data sets is proposed. Two complementary methodologies for the generation and evaluation of Energy Integration solutions are developed in the final two chapters. Firstly Total Site Analysis is adapted to the target industries, allowing for minimal data collection through a dual representation of utility and process requirements, process stream modelling and results generation. A mathematical formulation for optimised operations of steam networks is augmented to include load shedding when operating reserves are low. This is included into a simulation of boiler failures to establish the resiliency of steam network configurations. The data preparation methodologies, Total Site Analysis and steam network optimisation and simulation are applied to a typical refining and petrochemical cluster case study to establish energy efficiency solutions resulting in significant reduction in energy consumption.
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