Ind. Eng. Chem. Res. 2009, 48, 2721–2727
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A Synchronized Feed Scheduling of Petrochemical Industries Simultaneously Considering Vessel Scheduling and Storage Tank Management Taeyeong Lee, Jun-hyung Ryu,* and In-Beum Lee Department of Chemical Engineering, POSTECH, Pohang 790-784, Republic of Korea
Ho-kyung Lee LG Chemistry Research Park, Yusong, Taejon 305-380, Republic of Korea
This paper proposes a decision-supporting framework for a feeding problem in the petrochemical industry. The problem is concerned with delivering materials from suppliers to plants, unloading and storing in storage tanks, and mixing the materials before directly feeding into main processes. Most of the previous works in the literature have addressed these concepts, based on the assumption that the delivery of raw materials is given and fixed. From a joint investigation with industry partners, we have determined that the purchase of feedstock and its delivery also are critical issues in the feed scheduling problem of real-world plants. Thereafter, this paper takes into account previously addressed issues separately and simultaneously, to increase the overall efficiency. The corresponding decision-making problem is mathematically transformed to a mixed-integer nonlinear programming (MINLP) problem. The solution of the problem is computed using the iterative framework between that of a relaxed mixed-integer linear programming (MILP) problem and that of a nonlinear programming (NLP) problem, to prevent compositional discrepancy. An industry-coworked example of the naphtha case is presented, to illustrate the applicability of the proposed framework. Introduction Competition in the petroleum and petrochemical industries currently is unprecedented, for many reasons (the appearance of new competitors from oil-producing countries, narrowing profit margins that are due to rapidly increasing prices of raw materials, etc.). To survive under such challenges, significant attention has been given to short-term scheduling problems for feedstock management in the PSE community. Some previous works1-8 have focused on the unloading and storing in storage tanks, and the mixing the materials, before directly feeding the feedstock into the main processes. Because the purchase and delivery of raw materials are often assumed to be given and fixed, they cannot exploit the opportunities that are related to the two processes. On the other hand, other works9,10 have addressed the selection of the types of contracts related to the purchase of raw material or the supply of products to maximize the net profit or minimize the procurement cost. Especially, the work described by Park et al.9 considered both the purchase and sales contracts of the chemical process system, which is simply described as linear balance equations. Their works either oversimplified the real chemical operations or even omitted them. It is possible that the properties of feedstock obtained through the contract could not satisfy the operational conditions. From the joint investigation with industry partners, we determined that the purchase of feedstock and its delivery also are critical issues in the feeding scheduling problem of realworld plants. Thus, this paper takes into account storage tank management as well as vessel delivery and unloading schedules simultaneously, to increase the overall efficiency. The information, such as selecting from alternative raw materials (in terms of amount and properties), their delivery times or transportation types (such as vessel capacities, etc.), are also critical decision variables in the feeding scheduling problem of real-world plants. * To whom correspondence should be addressed. E-mail address:
[email protected].
This claim is due to the fact that feedstock cost comprises more than 50% of the total production cost and incorrect delivery schedules result in the immobilization of plants of huge capital value. There may be room for the further increase of operation efficiency and potential savings/profit. Therefore, this paper expands the previous works by proposing a mathematical model for an integrated feeding framework that simultaneously considers vessel scheduling and storage tank management. The proposed framework will be introduced for the case of the ethylene-manufacturing naphtha cracking center (NCC) process, which is one of the typical petrochemical processes used for other starting petrochemicals, such as ethylene, benzene/toluene/xylene (BTX), etc. Problem Statement As can be seen in Figure 1, naphtha feeding processes for ethylene plants are composed of naphtha suppliers, storage tanks, a charging tank, furnaces, etc. There are several types of naphtha in the market, and the purchased naphtha is delivered to the port where ethylene plants are located mostly by vessels, which have different volume capacities. After being delivered to the processes, naphtha are stored and blended in storage tanks. The properties of naphtha in the charging tank should be checked,
Figure 1. Schematic diagram of the naphtha feeding framework.
10.1021/ie800741m CCC: $40.75 2009 American Chemical Society Published on Web 02/02/2009
2722 Ind. Eng. Chem. Res., Vol. 48, No. 5, 2009
to determine whether or not they meet the operational conditions, before it is fed into furnaces. The basic assumption of this paper is as follows. The price of naphtha supplied from each supplier does not vary over the scheduling time horizon, because purchase decisions have been implemented beforehand, using contracts with suppliers. The demand for naphtha in furnaces is assumed to be constant. Because more than one vessel per day does not arrive and less than one day is required to unload naphtha from a vessel and transfer it from vessels to tanks, the uniform time interval of the time horizon considered in this problem is set as one day. Although using a time interval of less than one day results in more accurate scheduling, it causes an unnecessary increase in problem size. Ultimately, the measurement of the quantity of naphtha is based on weight, and the properties of naphtha are measured on a weight percent basis and are linearly additive. From the result of the problem, we intend to answer questions such as the following: (a) How much of each type of naphtha should be purchased? (b) When is the best time to deliver naphtha to the ethylene plant? (c) How should the tanks that use the naphtha in the plant be operated? Mathematical Formulation The proposed decision-making model is mathematically formulated as follows. Objective Function. The goal of this feed scheduling is to optimize the related overall processes by synchronizing the purchasing and delivery processes with the tank operation processes. To archive this goal, the objective function is to minimize the total cost, which consists of the purchase and unloading of naphtha and its transfer to tanks. The most significant component of this objective function is the purchase cost of naphtha, whereas other components comprise
