An optimization model for refinery production scheduling

https://doi.org/10.1016/S0925-5273(00)00162-6Get rights and content

Abstract

In this paper we describe a production planning and scheduling problem in an oil refinery company. The problem concerns the planning and the utilization of a production process consisting of one distillation unit and two hydro-treatment units. In the process crude oil is transformed to bitumen and naphthenic special oils. The aim of the scheduling is to decide which mode of operation to use in each processing unit at each point in time, in order to satisfy the demand while minimizing the production cost and taking storage capacities into account. The production cost includes costs for changing mode and for holding inventory. We formulate a mixed integer linear programming model for the scheduling problem. The model can be regarded as a generalized lot-sizing problem, where inventory capacities are considered and more than one product is obtained for some modes of operation. A number of modifications and extensions of the model are also discussed. It is shown how the optimization model can be used as a viable tool for supporting production planning and scheduling at the refinery, and that it is possible to analyze scheduling scenarios of realistic sizes. It is also shown that the model can support shipment planning and strategic decisions concerning new products and investments in storage capacity.

Introduction

We consider production planning at the Nynäs oil refinery in Nynäshamn, Sweden. The production plant consists of one crude distillation unit and two hydro-treatment units, where crude oil is distillated and further processed and/or blended into various oil products, such as bitumen, naphthenic special oils and fuels. The production planning includes the aggregated production planning deciding where and when production should occur, the shipment planning where customer demand is transformed to schedules for the tankers transporting the products, the scheduling of the processing units, and finally the realization of the plans and the schedules with respect to the utilization of tanks and pipes. In this paper we focus on the process scheduling problem, i.e. on the question of how to utilize the processing units in an optimal manner given a specified demand. The scheduling is strongly related to the planning at the other levels, and it affects many types of decisions in the company. The ability to efficiently construct high-quality (low-cost) schedules is therefore crucial for the refinery in order to be competitive.

The scheduling problem concerns the question of which mode of operation to use in each processing unit at each point of time, in order to satisfy the demand for a given set of products. A main characteristic of refinery scheduling is that a set of processing units concurrently produce multiple products, and a product obtained as output from one processing unit can be used as input to another processing unit. A mode of operation for a processing unit is specified by the combination of products consumed and produced in the process, and by the yield levels for each of the products. Changeovers between modes of operation cause disturbances and extra costs to the production process. Hence, long sequences of the same mode of operation (few changeovers) are preferred. Long sequences imply, however, larger inventory levels for some products and an increased need for storage capacities (tanks) with associated larger holding and capital costs.

We formulate a mixed integer linear programming model for the refinery scheduling problem. The planning horizon is divided into a set of discrete time periods, and the model concerns decisions about which mode of operation to use in each of these time periods for all processing units. The objective is to minimize costs of changing modes and costs of keeping inventories, given demands for a set of products, storage capacities, and safety stock levels. The optimization model can be regarded as a generalized lot-sizing problem, where more than one product is obtained for some modes of operation and where inventory capacities are considered.

Not very much is reported in the literature regarding the scheduling of operation modes in refineries using optimization models. One example is given by [1], who used a mixed-integer linear programming model to minimize the number of changeovers between operation modes. In areas related to scheduling of operation modes, optimization models have been more frequently used. Linear programming models have, for example, been used for long-term aggregate production planning (see [2], [3]), and optimization models have also been used for blending problems (see, for example [3], [4], [5]). Other work related to the scheduling of operation modes concern unloading and blending of crude oil, feed management, and to some extent tank and pipe management (see [6], [7]). An extensive review of problems and models within the area of refinery planning and scheduling is given in [8].

The contribution of this paper is to show how a refinery scheduling problem can be formulated using an optimization model, and that it is possible to solve and analyze scheduling scenarios of realistic sizes. We show that the optimization model can be used as a viable tool for supporting production scheduling at the refinery, and also to support the shipment planning and strategic decisions concerning new products and investments in storage capacity.

In Section 2 we describe the production process, and in Section 3 we describe the production planning and scheduling situation at the refinery. Then, in Section 4, the optimization model for the scheduling problem is presented. Section 5 includes a number of extensions of the model, and in Section 6 we describe the implementation of the model at the company. Finally, Section 7 includes examples of analysis that can be performed by the use of the model.

Section snippets

The production process

The production process at the Nynäs refinery consists of three processing units; the crude distillation unit (CDU) which transforms crude oil into naphtha, distillates and bitumen, and two hydro-treatment processes which transform distillates into naphthenic special oils. The production process is illustrated in Fig. 1. The CDU concurrently produces one bitumen product, four different distillates, and some naphtha by using approximately 4500tons of crude oil each day (24hours). Since the CDU is

Production planning and scheduling

The planning and scheduling of the production process at the Nynäs refineries is carried out sequentially, as illustrated in Fig. 2.

At the top level, we have the aggregated production planning. Based on forecasted aggregated demand at depots and customer areas, the aim of the planning is to decide which products should be produced where and when. In this planning step the transportation flows, the inventory levels, and the quantities of crude oil to be bought, are also considered.

For the

Model formulation

In this section we present the mathematical formulation of the production scheduling problem at the Nynäs refinery. We will formulate the model using general notation, which shows on the possibility of using the model for general refinery production scheduling.

We make a time-discretization of the planning period, and denote the set of time periods by T. In the Nynäs case the length of one period is 24 hours, and the planning period (number of time periods) is 31 days (in some cases 60 days).

Extensions of the model

The proposed production scheduling model [SCH] can be extended to possibly better describe the production problem. In this section we formulate a number of modifications of the basic model.

Implementation and use of the model

In this section we present a number of computational tests and analyses of the proposed scheduling model [SCH]. The computational tests are made on a set of scenarios representing real life scheduling situations at Nynäs. The purpose of the tests is to show that it is possible to use the model in practical planning situations, and to illustrate what kind of analyses are possible to make with the model. In the following, we first describe the scenarios, the solution methods used, and the

Conclusions and future research

We have studied the production planning and scheduling at a refinery. An optimization model for the production scheduling was formulated, and it was illustrated how this model, as well as some extensions of the model, can support decision making at both strategic/tactical and operational planning levels. A prototype scheduling tool has been developed based on a tabu search heuristic to solve the model, and the schedules obtained have been analyzed by experienced planners to properly reflect the

Acknowledgements

This research was performed within the International Graduate School of Management and Industrial Engineering (IMIE) with support from the Swedish Foundation for Strategic Research, the Swedish National Board for Industrial and Technical Development (NUTEK), and the Center for Industrial Information Technology (CENIIT) at Linköping University.

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