refinery planning & scheduling

WIPRO TECHNOLOGIES

By Sowmya Santhanam

Refinery Planning & Scheduling - Plan the Act. Act the Plan.

EXECUTIVE SUMMARY

Due to the record high and fluctuating crude prices, refineries are under extreme pressure to cut down

operating costs. This has led to a great focus on the downstream supply chain management processes and

tools, which when effectively used, result in significant benefits for the refinery. This paper talks about the

best practices that are followed while modelling the planning and scheduling tools. The planning tools are

used with the single objective of maximising the margins from the refinery. The scheduling tools help in

implementing the plan on a day to day level.

Currently, complete automation of scheduling tools has still not been achieved. This paper also talks about

the future improvements that refiners are looking forward to. This paper attempts to give some thoughts

and ideas that could be followed in developing general heuristics which are a step forward in the direction of

complete automation of scheduling tools.

TABLE OF CONTENTS

Introduction to the Refinery Supply Chain...................................................................4

Refinery Planning and Scheduling in the Supply Chain................................................4

Current Practices and Tool Modeling Basics.................................................................4

Planning Tool Modeling Basics.............................................................................................4

Need for a Scheduling Tool and Scheduling Tool Modeling Basics.......................................................5

Scheduling in the Future.............................................................................................. 5

Crude Scheduling............................................................................................................6

Product Scheduling..........................................................................................................7

Monitoring of Schedulers Performance........................................................................8

Data Consistency across Models..................................................................................8

Conclusion....................................................................................................................9

Appendix...................................................................................................................... 9

About the Author...........................................................................................................9

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Introduction to the Refinery Supply Chain Supply chain optimization is an important margin driver for a refinery. The

complexity, with which a refinery is built, provides the flexibility to optimize

operations, thereby maximizing margins. Supply chain managers need to

analyze a very complex set of choices before taking decisions. Best in class

Supply Chain Management (SCM) tools and practices will be required to give

forward visibility to supply chain operations.

The principles necessary for an operationally effective and successful

downstream supply chain, includes a requirement for integrated planning,

information flowing in all directions, efficient execution, and visibility to

performance across the organization.

Hence, one cannot underestimate the importance of an integrated

architecture in the complete supply chain.

WIPRO TECHNOLOGIES

Refinery Planning and Scheduling - Plan the Act. Act the Plan.

Wikipedia Says...

Supply Chain Optimization is the

application of processes and tools

to ensure the optimal operation of a

manufacturing and distribution

supply chain. This includes the

optimal placement of inventory

within the supply chain, minimizing

operating costs. This often involves

the application of mathematical

model l ing techniques us ing

computer software.

Refinery Planning and Scheduling in the Supply ChainThe objective and scope of each tool in the supply chain should be well defined.

Planning tools -> Plan the act! To maximize the margins from the refinery complex

Scheduling -> Act the plan!

The manufacturing plants follow the guidelines as defined by the planning and scheduling tools, for optimized refinery

operations. A well-defined feedback mechanism should be part of the process, so as to analyze and identify any gaps in the

plan, schedule, and operations and continually improve and tune the process.

The refinery planning tool is generally being used for different purposes like financial forecasting, feedstock valuation, crude

run and refinery unit optimization, stock forecasting, etc with the single objective of maximizing Gross Refining Margins

(GRM).

The planning tool serves as an important medium for aligning the midstream planning with the downstream marketing. It

captures the refinery as a whole; and the key is optimization of the various constraints with the single objective of margin

maximization. Hence, it is very important that we do not land up with local optima problems with this tool. Non-linear

solvers have an inherent problem of local optima, so all efforts should be made to keep all constraints in the tool as much

linear as possible. The basic idea is to compromise on small inaccuracies caused because of linearization without losing any

focus on the single main objective of the planning tool, i.e. maximizing GRM by optimization.

Current Practices and Tool Modeling Basics

Planning Tool Modeling Basics

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Planning is typically done for a month, so we have a monthly average as the Linear Programming (LP) model output i.e.

we have:

?An average crude blend to be fed to the crude distillers ?An average product mix, which is to be produced during the entire month

In complex refineries, where different crudes are blended to produce a cocktail which is ultimately fed to the crude unit,

the crude diet to the unit changes almost every day. It is generally difficult to implement this “average” schedule on a

day-to-day basis, because of several issues like non-availability of crudes as planned during the LP model run, the tank-

pump hardware constraints in the field, etc which are generally not configured in the LP in an effort to keep the

constraints linear.

Hence, it is very important to have a scheduling tool, in which all the constraints are modeled in great detail, to check the

feasibility of plan implementation. The primary goal of a scheduling tool is to have a feasible schedule, meeting all

targets identified from plan. Once, all targets are met, the schedule is already optimal i.e. the schedule drives towards

maximizing the GRM of the refinery.

The process units behave in a highly non-linear fashion and many a product specification blend in a non-linear way. The

emphasis on the solution provided by the tool is on its practical implement ability, so the scheduling tool should provide

very accurate results. Hence, we need to use Mixed Integer Nonlinear Programming (MINLP) solvers when solving

problems of this type. Local optima problems, which are inherent problems with MINLP solvers, are no longer a concern,

since optimization is not the primary objective. We are more bothered with the accuracy of the results for its day-to-day

implementation; hence these complex solvers best suit refinery schedulers’ requirements.

It is essential to have a high-fidelity scheduling tool for

scheduling decisions that are accurate and enables the

scheduler to quickly respond to changing business scenarios

like emergency shutdown of a unit or purchase decision of a

distress sale crude cargo. The scheduling team has to quickly

act on such situations advising the traders the best possible

solution; else the refinery loses out on that opportunity. Not

only is it important to have a good tool, it is essential to have a

good team of people working on these tools.

The current scheduling tools and processes have allowed the refinery planner and scheduler close the gap between LP

plan and schedule to a fair extent. However, the preparation of the schedule is still largely person-dependent. Even with

a fairly robust model and an experienced scheduler, it typically takes a couple of hours to prepare a months’ schedule for

a complex refinery. The dream of the refiner is to move from a “person-dependent regime” to a “process dependent

regime”. In other words, the idea is to have generic heuristics built into the tool so as to make it “intelligent” to handle all

Need for a Scheduling Tool and Scheduling Tool Modeling Basics

Tools today help us to move from a “finding

a solution” scenario to an “analysis of

schedules” scenario i.e. with the availability

of a good tool, schedulers will now spend

more time on analyzing the various possible

schedules and decide which one is the most

effective in terms of maximizing GRM.

Scheduling in the Future



Crude Scheduling

kinds of scenarios, so that the schedule will be the same irrespective of the person preparing the schedule. The

challenge today for the tool developer is to have a “recursion” feature developed in the tool so that it has the capability

to go back and forth in time to make the overall schedule feasible or find the “best schedule”.

The preparation of the crude blend itself has been automated in most tools to a large extent, however it is the receipt of

crudes in various tanks that is present in the refinery is mostly manual. The receipt largely dictates the feasibility of

crude blends from thereon. A “wrong” receipt could cause infeasibility even a couple of weeks forward in the schedule.

The dilemma is to specify to the optimizer the time period it should go back and rework the schedule, just like a

scheduler would, so as to make the blends over the entire horizon feasible.

Typically, the following challenges are faced when developing a general heuristic:

Whether to make a blend or take receipt of the crude into tanks at any point in time?1

If there are multiple crudes present in the ship/ scheduled to be received through the

pipeline, which crude to be received first?2

If there is a problem with blend feasibility, then can some property be relaxed in the

crude blend window to make blend feasible? If multiple properties can be relaxed then

the order of preference of relaxation?3

Incase of complete infeasibility, how many days’ schedule to be deleted and readjusted

so that we make the complete schedule feasible?4

Even with recursion features the challenge is to have a generic algorithm which will

decide how long should we go back in time and rework the blends inorder to make the

schedule feasible.5

Demurrage vs. blend quality6



It is also seen that, in a refinery which processes multiple crudes in a blend, the trick is to store crudes as diverse in quality as

possible in order to make blends feasible. This problem, by itself, is a mathematical challenge, as it is analogous to finding

the maximum distance between two points. However, it is possible to develop a practically implementable solution, if the

scheduler is able to diversify categories of crudes to different tanks based on his experience.

Such clues along with clear answers to above situations will help a scheduler develop general heuristics for the tool, which

will lead to feasible blends in most cases. These procedures will help the scheduler a lot in running sensitivity cases, with

small changes in crude cargo types, cargo arrival dates etc. The user still has to manually take receipt into the tanks and do

one complete schedule to identify the problem areas, so that he can give the right kind of inputs to run the tool in “auto”

mode while carrying out sensitivity analyses. We are going one step further in trying to avoid repetitive work for the crude

scheduler

Product Scheduling

Product Schedule

The output crude schedule is one of the primary inputs of the product scheduling tool. Apart from this, the primary unit

throughputs, the feedstock and product prices and production targets are inputs that are taken from the LP. The grade-wise

dispatch schedule of products is taken from marketing. All these inputs are automated, with the help of a common database

which helps in data transfer between tools.

Primary unit

throughputs, feedstock,

product prices,

production targets

Grade-wise disptatch

schedule of products

The output crude

schedule



Once all the required inputs are given, with just a click of a button, we should have the complete product schedule ready.

The tool should provide a good analysis of the component production, component usage in each grade, component and

product tanks usage, economic analysis, etc which helps the user analyze the solution. In case of infeasibilities, the tool

should be capable of providing clues to infeasibility breakers so that the scheduler is not lost in the vast amount of data that

is presented to him.

These are typically decisions which vary with time. The challenge is to have a senior scheduler formulate a generic algorithm

which would work in most of the situations. The goal is to have a full months’ schedule prepared by the tool without any user

intervention in-between.

All the above initiatives will help refinery planning and scheduling professionals to go one step ahead in automation of

scheduling tools. While we are still far from making the process completely automated, it is a step in the right direction.

Monitoring of Schedulers PerformanceTo reap the full benefits of a tool implementation, the performance of the schedulers should also be monitored with

quantifiable objectives. Some of the objectives for the product schedulers could be predicted grade-wise production

numbers vs. actual, Quality Give Away in cents/bbl against a target, no of product/batch failures, etc. Similarly for the crude

scheduler it could be the comparison of crude consumption as suggested by the LP model vs. actual consumed. These serve as important checks to continually make sure that the scheduler is completely in sync with the plan goals and

objectives, and working as per the schedule suggested by the tool.

Data Consistency across ModelsThe data that is present in the planning and scheduling models should be accurate and tuned to represent the current

conditions of the plant. There should be a person/team of people who are given the responsibility of having consistent data

across all models used in planning and scheduling. There should be a good business process for the model update. Changes

in yields/quality in a plant for a small duration of time are generally not updated in the planning model, as it has greater

ramifications including influencing decisions on crude valuations and buying. Hence, only consistent shifts in yields and

qualities of streams are updated in the planning model with due explanation. However, these small changes could be

updated in the process models present in the scheduling tool to capture the variations in production that it might cause in

the immediate future.



Appendix

About the Author

Sowmya Santhanam, Lead Consultant, Refining Practice of Wipro Technologies, is a Chemical Engineer with a degree in

Mathematics from BITS, Pilani. She has earlier worked with the Planning & Scheduling department of Reliance Industries

Ltd for over 6 yrs on various scheduling desks, and has implemented supply chain tools for the 1.2 kbpsd refinery.

Conclusion

In this paper, we discussed on the important things that are to be taken care of while modelling planning and scheduling

tools. One should not lose focus on the primary objectives of running these tools. The planning tool acts as a bible - it is the

single most important tool from which directions are to be taken. The scheduling tool should primarily enact the plan, but

with all adjustments required because of the non-linear nature of refinery processes. With these thoughts, schedulers

move one step higher in scheduling automation. However, to make the tools more person independent, the senior

schedulers themselves have to identify general guidelines which work in their refinery in most situations. The effectiveness

of a robust “recursion” feature is very essential for working towards this goal and more studies need to be done in this

direction.


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