PRODUCT DESCRIPTION
by Hans Aalto (Author)
Real-time optimisation of natural gas pipelines in transient conditions is a challenging problem. Many pipeline systems are, however, only mildly non- linear even in large transients such as compressor station (CS) shutdown or startup. A dynamic, receding horizon optimisation problem is defined, where the free response prediction of the pipeline is obtained from a pipeline simulator and the optimal values of the decision variables are obtained solving an approximate Quadratic Programming (QP)problem where the cost function is the energy consumption of the CSs. The problem is extended with discrete decision variables, the shutdown/start-up commands of CSs. A Mixed Logical Dynamical (MLD) system is defined, but the resulting Mixed Integer QP problem is shown to be very high- dimensional. Instead, a sequence of QP problems is defined resulting in an optimisation problem with considerably smaller dimension. The receding horizon optimisation is tested in a simulation environment and comparison with data from a true natural gas pipeline shows 5 to 8 % savings in compressor energy consumption.
