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Abstract
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A
study on the optimal real -time management of hydrogen H 2 networks in oil
refineries has been carried out , with reference to the Petronor oil
refinery , belonging to Repsol group and located in Muskiz (Vizcaya) . The
thesis work is an application of well- known and established techniques as
process modeling and optimization to a currently interesting subject, H 2
networks in oil refineries. Coherent and robust results have been achieved,
and the solution is ready to be applied in the indu strial practice.
Firstly,
a simplified dynamic model of an industrial diesel hydrodesul ph urization
plant , one of the most important H 2 consumer plants in the network, was
developed with the aim of gaining insight into process operation, influencing
inputs and parameters, as well as variable sensitivities. The model is based
on first -principles balances and constitutive equations , combined with
black -box neural networks to model the kinetic coefficients f or the
reactions proposed . The feasibility of the approach was proved; d espite the
lack of on -line measurements for feedstock composition and sulfur content,
model predictions for H 2 consumption resulted even better than expected.
Additionally , the developed model was used to study the implementation of o
ptimal policies as control strategies according to the self- optimizing
technique (Skogestad, 200 0), again with the p urpose of H 2 optimal
management but only considering the aforementioned consumer plant isolated
from the whole network. The resulting contro l structure is simple, easy to
implement (feedback control with PI controllers) and assures the global
optimum in nearly all cases, although an upper RTO layer will be needed to
guarantee the operation in the adequate region, with no t frequent updates.
Onl y in one scenario , very uncommon , a trade -off arises regarding the
unconstrained degrees of freedom, and a self- optimizing control variable
must be looked for to assure close to optimal operation avoiding more complex
on -line optimization techniques. Secondly, a real -time optimization RTO
approach was followed for th e purpose of real- time optimal operation of the
global refinery H 2 network . In order to estimate the plant state while
taking advantage of redundancy in measurements, a data reconciliation step is
performed previous ly to the RTO. Both problems are solved by optimization
techniques, by minimization of two defined cost function s, based on the same
process model and subject to certain process constraints in each case . A
simplified model based on first principles has been proposed for the network
aimed at the optimal H 2 management ; model complexity corresponds with the
availability o f on -line measurements and the model aims ; parameters were
limited according to the normal operating ranges and the sensitivities for
important variables were analyzed . Modeling assumptions are justified based
on historical data from laboratory quality mea surements and the contribution
of the different terms to the total H 2 production. Off -line validation has
been performed, and the model robustness and flexibility verified . The data
reconciliation problem for an accurate plant state estimation is a challen
ging problem due to uncertainty , which is caused by several reasons ; the
main uncertainties regarding data reconciliation were identified and dealt
with . Practical implementation problems have also been tackled, in
particular the automatic detection of wrong measurements with simple rules
based on the measured standard deviations , as well as the management of
linear constraints to guarantee model convergence in the search region . The
data reconciliation results were validated off- line according to trends in
raw measurements and valve openings, in addition to process knowledge.
Regarding the optimal H 2 redistribution , solutions could be easily parameterized
corresponding to the logical optimal operation ; t rade -offs were identified
in certain cases, although the margin in those cases was not significant. An
analysis of solutions showed that: a) regarding high pressure (HP) purges,
the solution is the logical one, that is, to purge Low Purity Header LPH
excess , if any , at the network scope through the HP purge at lower H 2
purity until it gets saturated, following an increasing order of H 2 purity
to purge in consumer plants; b) regarding trade -offs arising in
redistribution from producer plants (high purit y, expensive) and LPH (low
purity, cheap) to consumer plants, there is margin for profit although small;
nevertheless the RTO approach can prove advantageous due to frequent changes
in scenarios , aiding the operators to save time in the identification and
implementation of the optimal policy . Furthermore, the analysis can also be
valuable to reveal economic -technical trade -offs, where non -linear
behaviours arise. The optimal operation of H 2 networks in oil refineries has
already been addressed from a design perspective by other research groups, in
particular by the Manchester University with the pinch technology. To the
best of my knowledge, reactor model accounts for the same phenomena; however
although more rigorous and accurate model s for the thermodynami c eq
uilibrium relations are used in this case, plant model flexibility is reduced
according to the design purpose, i.e. operating conditions are fixed
regarding reactor inlet and outlet H 2 purities, in such a way that
equilibrium relations in the separator s hold. Very recently, the subject has
also been addressed from an on -line operational view point by companies
providing services, like Inprocess based in Barcelona that takes advantage
of Hysys commercially available process simulator and its optimizatio n
capabilities to determine the optimal operation. To the best of my knowledge,
a lthough the same rigorous and systematic approach is shared regarding
optimization techniq ues, important assumptions and process constraints,
nevertheless a flexible and easily updated model calibration is worthwhile,
which can be enhanced with an intended model as the one developed. The H 2
network simulation is available in the EcosimPro modeling environment, as
well as the implementations f or the two optimizations problems t o solve the
data reconciliation and the optimal redistribution , using Snopt as NLP
solver based on a SQP algorithm . A library with components modeling each of
the units of the H 2 network has also been developed in the EcosimPro
environment, together with functions for the automatic generation of the code
needed to implement both optimization problems .
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