Trajectory optimization of an oscillating industrial two-stage evaporator utilizing a Python-Aspen Plus Dynamics toolchain

• Evaporators are integral parts of many separation processes across production industries, and they need to be well understood in order to be operated well, thereby enabling high resource-efficiency and productivity. In a previous investigation, the effects of disturbing oscillations in a two-stage evaporator system were quantified. In the current study, these oscillations were reduced through trajectory optimization using steam consumption as a temporally discretized decision variable, taking advantage of a dynamic process flowsheet model in Aspen Plus Dynamics (APD) employed as if it were a black-box model. The optimization was performed utilizing a Python-APD toolchain with the SciPy implementation of COBYLA. The optimal trajectory was able to successfully reduce the objective function value (including the product stream mass flow variance and a bang-bang penalty on the trajectory itself) to slightly less than 0.3 % of that of the nominal case, in which a time-invariant steam consumption was employed. This in turn grants opportunities to increase throughput of the process, leading to significant financial gains.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Kemiteknik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Chemical Engineering (hsv//eng)

TEKNIK OCH TEKNOLOGIER  -- Kemiteknik -- Kemiska processer (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Chemical Engineering -- Chemical Process Engineering (hsv//eng)

Nyckelord

derivative-free optimization

dynamic optimization

Aspen Plus Dynamics

oscillations

evaporator system

python

Aspen Plus Dynamics

Derivative-free optimization

Dynamic optimization

Evaporator system

Oscillations

Python

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art (ämneskategori)

ref (ämneskategori)