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

Transcription

1 Refinery Planning & Scheduling - Plan the Act. Act the Plan. By Sowmya Santhanam

2 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.

3 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

4 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. 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 modelling techniques using computer software. Refinery Planning and Scheduling in the Supply Chain The 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. Current Practices and Tool Modeling Basics Planning Tool Modeling Basics 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. 4

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

6 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. Crude Scheduling 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: 1 Whether to make a blend or take receipt of the crude into tanks at any point in time? 2 If there are multiple crudes present in the ship/ scheduled to be received through the pipeline, which crude to be received first? 3 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? 4 Incase of complete infeasibility, how many days schedule to be deleted and readjusted so that we make the complete schedule feasible? 5 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. 6 Demurrage vs. blend quality 6

7 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 The output crude schedule Primary unit throughputs, feedstock, product prices, production targets Grade-wise disptatch schedule of products 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. 7

8 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 Performance To 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 Models The 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. 8

9 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. 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. 9

10 ABOUT Wipro is the first PCMM Level 5 and SEI CMMi Level 5 certified IT Services Company globally. Wipro provides comprehensive IT solutions and services (including systems integration, IS outsourcing, package implementation, software application development and maintenance) and Research & Development services (hardware and software design, development and implementation) to corporations globally. Wipro's unique value proposition is further delivered through our pioneering Offshore Outsourcing Model and stringent Quality Processes of SEI and Six Sigma. WIPRO IN ENERGY & UTILITIES The Energy and Utility division of Wipro Technologies is one among the Top 10 IT solution providers to the E & U industry across the globe. The Energy & Utilities business unit has worked with over 75 top Energy and Utility companies across North America and Europe in regulated as well as deregulated markets providing solutions in areas such as Customer Care, Billing and Settlement, Work and Asset Management and Grid Operations covering all industry sectors --- Electricity, Gas, Oil and Water. The cumulative experience of over 5,500 person years spans IT Consulting, Systems Integration, Business Process Outsourcing, Application Development and Application Management services. 10