A study on modelling, data reconciliation and optimal operation of hydrogen networks in oil refineries

CATEGORY: HYDROGEN NETWORKS 
A study on modelling, data reconciliation and optimal operation of hydrogen networks in oil refineries

Type	Thesis
Author	Gómez Sayalero
Author	Elena María
URL	Free Full Text Source:  http://uvadoc.uva.es:80/handle/10324/16637
Date	2016
University	Universidad de Valladolid
Abstract	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 .