Abstract Across the hydrocarbon processing industry today, energy and utility costs are often the largest operating expense after the purchase of raw materials. Performance of the plant fuel gas systems heavily impacts variable fuel costs, environmental emissions (like SOx and NOx release), overall complex performance and throughput. Controlling fuel gas header pressure and quality introduces the complexities of non-linear dynamics, significant self-propagating interaction and insufficient degrees of freedom to solve the combined control and optimization problem. Chevron has installed a system to manage these complexities on their 90 000 bpd refinery in Cape Town, South Africa. The system, designed and installed by BluESP, performs plant-wide optimisation across three vaporisers in different parts of the plant and four boilers in the utilities section. The solution uses linear model predictive control with gain scheduling and an LP optimiser to operate against sulphur dioxide emission limits as well as hydraulic constraints. This paper discusses the challenges in controlling the system, the use of model predictive control to address these challenges, as well as the benefits achieved.