Closed Loop Dynamic Optimization of a Petroleum Refinery Process

Aho, M.; Bergman, Samuli; Hammarström, Leif; Yli-Opas, K.; Pelkola, Antti; Sourander, M.

doi:10.3182/20090506-3-sf-4003.00048

Cited by 3 publications

(1 citation statement)

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“…Another approach on process optimization uses appropriate selection of control structure along with RTO (without MPC) to achieve maximum process profitability, this has been well discussed by Engell (2007). Currently, there is important interest on MPC and RTO integration, either as a whole dynamic RTO (Aho et al, 2009) or as an economic MPC (Amrit et al, 2013;Ellis et al, 2014;Ellis and Christofides, 2015), or separately with focus on robust and stable integration (Alvarez and Odloak, 2010;De Souza et al, 2010). Ideas of the incorporation of economic objective functions into the MPC formulation emerged in the 90s as nonlinear MPC flourished in the research community.…”

Section: C122 About Real-time Optimizationmentioning

confidence: 99%

Simulation and optimization methods as decision support tools for operation of oil refinery hydrogen networks.

Prado¹,

Santiago²

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The process industry has been at the forefront of manufacturing technology advances, systematically aiming for sustainable process improvements. Generally, improvements come as a result of decision-making processes which may be backed on information from various sources. In fact, decision making in manufacturing operations is indeed complex, as it accounts for different scopes and timescales depending on the aimed activities ranging from strategic business management decisions (long term decisions) to basic regulatory control of the process (automatic actions). Despite that, actual deployment of integrated decision support systems remains atypical in process industries, which constraints the potential of optimal operation of assets. This thesis focuses primarily on advanced and supervisory control tools, which typically translates into plant-wide decisions at timescales from minutes (advanced control) to hours (supervisory control).

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