Plant-wide utility disturbance management in the process industry

Abstract

Utilities, such as steam and cooling water, are often shared between production areas at large-scale sites. A disturbance in the supply of a utility is therefore likely to affect a large part of a site, and cause great loss of revenue. This study focuses on identifying disturbances in utilities and estimating the economical effects of such disturbances. A general method for reducing the loss of revenue due to utility disturbances, the utility disturbance management (UDM) method, is presented. Modeling of the effects of utility disturbances on production is needed to complete all steps of the method. In this paper, a simple on/off modeling approach is suggested to quickly obtain key performance indicators that may be used for decision support for proactive disturbance management. A matrix representation of a site and its utilities is introduced to simplify the computations. The UDM method is applied to an industrial case at Perstorp, Sweden.

Introduction

In the chemical process industry, companies must continuously improve their operational efficiency and profitability to remain competitive (Bakhrankova, 2010, Bansal et al., 2005). This means it is of great importance to minimize losses in revenues due to e.g. disturbances in operation. Plant-wide disturbances cause considerable revenue losses at industrial sites (Bauer et al., 2007, Thornhill et al., 2002). Some of these plant-wide disturbances are caused by utilities, such as steam or cooling water, which are used at most industrial large-scale production sites. At a disturbance in the supply of a utility, the production in all areas that use the utility is affected. Furthermore, areas are often connected by the product flow at the site, which makes the consequences of utility disturbances hard to predict. Two examples of utility disturbances at an industrial site are given in Fig. 1, Fig. 2. Both figures show a pressure drop in the middle-pressure steam net and the production in four areas that all require middle-pressure steam during the same time-period. The dashed line shows the ideal steam pressure of 14 bar.

In Fig. 1 it can be seen that the production of product 1 is not affected by the disturbance, whereas mainly the production of product 4 has to handle the variations. The reason that the production of product 4 is reduced already before the pressure drop is detected is that the steam boiler fails before the pressure drops, and thus the operators can start to react to the disturbance before it is visible in the measurement data of the pressure. In Fig. 2, the operators at the site handled the disturbance by starting to reduce the production of product 1 immediately as the pressure in the steam net drops. In this case, the production of products 3 and 4 is back to normal shortly after the disturbance, whereas the production of products 1 and 2 is reduced for a longer time. Consequently, the same type of disturbance is not handled using the same product flow control strategy each time. Furthermore, since utilities are shared by production areas, it is not evident which utility that causes the greatest economical loss. This motivates the need for a method that orders utilities according to the loss of revenue they cause, and suggests strategies for handling utility disturbances so that the loss of revenue is minimized. Economical loss is a useful measure, since it is a measure that is easily understandable by the managers at a site.