OPTIMIZATION OF A REFINERY CRUDE DISTILLATION UNIT IN THE CONTEXT OF TOTAL ENERGY REQUIREMENT - PowerPoint PPT Presentation

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OPTIMIZATION OF A REFINERY CRUDE DISTILLATION UNIT IN THE CONTEXT OF TOTAL ENERGY REQUIREMENT

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Title: OPTIMIZATION OF A REFINERY CRUDE DISTILLATION UNIT IN THE CONTEXT OF TOTAL ENERGY REQUIREMENT


1
OPTIMIZATION OF A REFINERY CRUDE DISTILLATION
UNIT IN THE CONTEXT OF TOTAL ENERGY REQUIREMENT
  • E. O. Okeke A. A. Osakwe-Akofe
  • NNPC RD Division, Port Harcourt, Nigeria
  • APACT03, York, 28 30, April, 2003

2
INTRODUCTION
  • The Nigerian National Petroleum Corporation, has
    4 refineries, in its downstream operations,
  • The primary goal of this refiner is to achieve
    and maintain high gasoline production,
  • Hence, the main objective of this study is to
    optimize gasoline production in all the
    refineries,
  • The strategy being to first target the CDUs in
    these refineries. Maximizing the yield of
    gasoline and its intermediates will directly
    impact positively on total pool gasoline
    production,

3
PROGRAMME FOR MAXIMIZING GASOLINE PRODUCTION
  • Maximizing gasoline and its intermediates
    production from the refinries has been planned to
    be accomplished in phases, viz-
  • Phase I CDU 1 (the first refinerys CDU)
  • Phase II CDU 2,3,4, 5 (the other 3 refineries),
  • Phase III Catalytic plants - CRU, FCC HF Alky
  • Phase I began with CDU 1 as a basis to ascertain
    plant suitability to process different crude oil.

4
CDU 1 FEED MAIN COLUMN SUBSYSTEM
  • The CDU 1 of the first of these refineries, the
    object of our presentation, was installed in the
    1960s to process naphthenic crude of API 40.3 at
    first and another of API 35.4 afterward,
  • It has a main fractionator with 44 trays and 4
    side strippers, and a stabilizer column.

5
CDU 1 DISTILLATES
  • The intermediate distillates are as in
    conventional CDUs,
  • Unstabilized gasoline from the main fractionator
    is further processed in the stabilizer column,
  • Straight run naphtha and other distillates from
    the main fractionator are routed further
    downstream for processing and upgrading,
  • Stabilizer produces an intermediate gasoline as
    bottoms and LPG as overhead

6
CDU 1 MAIN DESIGN HARDWARE FEATURES
  • Licensed by SHELL and designed as a conventional
    crude distillation unit,
  • Crude oil characteristics and product
    requirements as applicable in establishing
    hardware design,
  • Hardware performance evaluation, maintenance and
    upgrading of facility undertaken periodically.

7
MAIN FOCUS AREAS TO ACHIEVE MAXIMUM GASOLINE IN
CDU 1
  • Main areas are
  • efficient operation of the CDU,
  • review of configuration of CDU to determine
    opportunity for further increase in gasoline
    yield,

8
GENERALIZED STRUCTURE OF THE CDU 1
  • The CDU can be decomposed in stages as follows
  • Stage 1, the main fractionator producing feed for
    Stage 2 (i.e. the stabilizer)
  • Achievement and sustenance of increase yield must
    be progressive from Stage 1 through Stage 2

9
METHODOLOGY STEADY STATE SIMULATION TO
OPTIMIZATION
  • The main stages are as follows
  • Compare the crude assays for the two naphthenic
    crudes,
  • Configure, specification and steady state
    simulation of the CDU using HYSYS.Plant,
  • Match HYSYS.Plant simulation results with
    original design requirements,
  • Carry out optimization of the CDU
  • Results obtained showed good opportunity.

10
COMPARISION OF THE TWO CRUDES
11
COMPARISION OF PRODUCTS DERIVED FROM ON THE TWO
CRUDES
12
INCREASING GASOLINE YIELD
  • For a given CDU, yield of gasoline derivatives
    depends on,
  • Feed characteristics,
  • Process requirements/operating conditions.
  • From the above therefore, since feed is
    constant, optimizing gasoline yield will depend
    on process requirements/operating conditions.

13
FRONT-END CDU 1 EVALUATION FOR HYSYS
IMPLEMENTATION
  • The evaluation of the CDU is as follows
  • Establish a reliable CDU configuration, determine
    process conditions using HYSYS and match these
    with the original plant design basis and
    requirements,
  • Properly decompose the structure of the CDU and
    determine boundary conditions for optimization,
  • Achieve a reliable process optimization in the
    context of total energy requirements.

14
OPTIMIZATION PARAMETERS
  • The parameters for optimization are derived from
    process/hardware environments, viz,
  • The main fractionator and the stabilizer are
    linked together stabilizer feed comes from the
    main fractionator,
  • The other gasoline blending stock, SRN, a
    derivative from the main fractionator is routed
    for further processing,
  • Four side strippers in the main fractionator,
  • The stabilizer has a condenser and a reboiler

15
PLANT ARRANGEMENT FOR OPTIMIZATION
16
HEAT LOAD DISTRIBUTION
  • CDU has an integrated heat exchanger network for
    heat recovery which shares loads, viz, Q1,,Q7,
    where Q4 and Q5 are utilities,
  • Heat loads in the network are assumed to be
    efficiently shared,
  • Heat supplied through the crude charge and for
    the various steam stripping supplies are
    constant.

17
HYSYS FLOWSHETET CONFIGURATION Overall CDU
18
HYSYS FLOWSHEET CONFIGURATION Main Column
Subsystem
19
MODELLING PROCEDURE
  • Stage-wise approach was adopted, viz,
  • Evaluate CDU configuration and steady state
    simulation data to determine opportunity for
    optimization,
  • Based on the structure of CDU process and
    hardware requirements, evolve an optimization
    algorithm and define boundary conditions to be
    solved by HYSYS.Plant,
  • Define steady state parameters from HYSYS.Plant
    simulation as first level data, and referenced as
    base or design values,
  • Optimize the overall gasoline yield in the
    context of total energy requirement.

20
OPPORTUNITIES FOR OPTIMIZING GASOLINE YIELD
  • We observed the following
  • The columns are linked in sequential arrangement,
  • Possibility of enhanced recoveries of gasoline
    in the nearest distillates below and above SRG,
    ie SRK and LPG, and in the stabilizer overhead,
  • To maintain high quality gasoline to meet base or
    design specification, the path to solution must
    be constrained,
  • Problem is non-linear.
  • Based on these conditions an algorithm was
    developed

21
THE ALGORITHM Heat Loads
  • Heat load differential at steady state
  • ?Qibase Q1base Q2base Q7base 1
  • Heat load at any level of optimization
  • ?Qiopt Q1opt Q2opt Q7opt 2
  • And the differential
  • ?Qdifferential ?Qiopt - ?Qibase 3

22
THE ALGORITHM Gasoline Yields
  • Gasoline yield at steady state
  • ?yibase y1base y2base y7base 4
  • Gasoline yield at any level of optimization
  • ?yiopt y1opt y2opt y7opt 5
  • And the differential
  • ?ydifferential ?yiopt ?yibase 6

23
THE ALGORITHM Objective Function
  • Incorporating the various energy and gasoline
    costs, the resultant differential becomes,
  • INB ?ydifferential - ?Qdifferential 7
  • The objective function becomes
  • Max f(X1,X2,X3) ?ydifferential-Qdifferential
    8
  • Where,
  • ?ydifferential ?Qdifferential are gasoline
    and energy costs,
  • X1, main column naphtha stripper reboiler return
    temp,
  • X2, main column kero stripper reboiler return
    temp,
  • X3, stabilizer reboiler return temp,
  • Subject to RON and RVP of gasoline being within
    base or design values.

24
HYSYS OPTMIZER
  • Primary variables (X1, X2, X3) are manipulated to
    maximize INB. Primary variables must have upper
    lower limits, and these are used to normalize the
    primary variables, viz,
  • Xinorm (Xi Xilower)/(Xiupper Xilower).
    Where Xi X1, X2, X3
  • Objective function as defined by INB,
  • Constraints as defined for RON RVP,

25
OPTIMIZATION BY SEQUENTIAL QUADRATIC PROGRAMMING
  • Sequential Quadratic Programming (SQP) was
    applied for solution.
  • SQP minimizes a quadratic approximation of the
    Lagrangian function subject to linear
    approximations of the constraints. The second
    derivative matrix of the Lagrangian function is
    estimated automatically. A line search procedure
    utilizing the watchdog technique (Chamberlain
    Powel) is used.

26
PROBLEM SOLUTION
  • Sequential quadratic programming was found to be
    ideal for solution,
  • Solution was found for all cases studied,
  • General increase in yield of stabilizer feed and
    SRN from the main column,
  • Gasoline yield was increased by 8

27
BASE OPTIMIZED VALUES
28
TESTING ALGORITHM ROBUSTNESS RELATIONSHIP OF
KEY PARAMETERS
  • Some optimization test runs were done using same
    HYSYS.Plant to
  • Test the robustness and reliability of the
    algorithm at achieving early convergence,
  • Determine the variation of key parameters, that
    impact on the structure of the CDU and the
    interaction of the main fractionator and the
    stabilizer. These parameters are the naphtha
    stripper reboiler return temp, the kero stripper
    reboiler return temp, and the stabilizer gasoline.

29
VARIATION OF GASOLINE WITH NAPHTHA STRIPPER
REBOILER RETURN TEMP
30
VARIATION OF GASOLINE WITH KERO STRIPPER REBOILER
RETRUN TEMP
31
VARIATION OF GASOLINE WITH STABILIZER REBOILER
RETRUN TEMP
32
OBSERVATIONS FROM THE OPTIMIZATION
  • The optimization based on this algorithm achieves
    early convergence,
  • As expected, the naphtha stripper (X1) and kero
    stripper reboiler (X2) temperatures have indirect
    impact on the stabilizer gasoline, while the
    stabilizer reboiler (X3) temperature has a direct
    impact on the same gasoline yield,
  • The 3 parameters X1, X2 X3 are manipulated
    as appropriate to optimize the gasoline produced.

33
CONCLUSION
  • Sequential quadratic programme technique ideal
    for solution,
  • Solution of the algorithm is reliable, achieving
    early convergence in the cases studied,
  • Objective of obtaining increased gasoline yield
    in the context of reduced energy requirement
    achieved,
  • Since the configuration of the refinery CDUs are
    similar, this algorithm can be applied to
    optimize the CDU 2,3,4,5 in the other 3 refineries

34
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