Advanced Process Control and Performance Monitoring

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The aim of advanced process control (APC) is to move the operating parameters to the best process conditions and to keep them regardless of disturbances, while satisfying process constraints and production goals. Therefore, APC offers considerable potential for reducing energy requirements and operating costs.

Advanced process control consists of control structures that go beyond ordinary control strategies like PID controllers. It incorporates for instance cascade controllers, feed forward control, as well as model predictive control and online optimization-based on process models. Model-predictive multivariable control technology was introduced into industry about 25 years ago and was primarily used in refineries. Nowadays APC is a welLestablished technology in the chemical industry. It can be applied to a single unit operation or to a whole plant. In addition, APC reduces process variability. Therefore, the processes can be operated closer to their optimum operating conditions. An example of APC for distillation is give in Section 7.4.2.6.

Increasing number of companies in the chemical industry recognize the significance of information as an important factor for optimizing their production. Beside classical automation technology, modern operating systems delivering realtime information about the actual status of the process attract more and more attention. Performance monitoring, based on the monitoring of selected variables in the process, so-called KPI (key performance indicators), plays a dominant role in increasing productivity and reduction of energy costs [36].

Energy efficiency improvements can be achieved by optimized design of the equipment or the entire process as well as by optimized operation. Optimized operation is achieved by improved automation and process control or directly by better manual operation.

What can often be observed is that processes are operated at a comfort zone. The energytnfluencing operating parameters are not challenged and not load) dependent. After a failure the process often remains in a ) safe) operating point. Examples are distillation columns with too high reflux flows (see Section 7.4.2) or reactors, operated with an excess of solvent or reactant leading to large circulation flows in the purifying section. Furthermore, the product specification of a separation is often slightly higher than the required specification for further processing. In addition, the specific energy consumption is frequently load dependent and shows fluctuations.

The basic principle of performance monitoring is continuous data logging of physical data (process monitoring) and technical condition of the plant (condition monitoring). An example of the first is the definition of reaction relevant data, such as activity of catalyst, selectivity and yield. The example of the latter is the definition of equipment- relevant data, for example fouling of heat exchangers, control and measuring equipment [36]. Performance monitoring answers the questions [36]: At what state is the process currently? How far is the process from optimum or from a pre-defined benchmark? What are the reasons for deviations from the set points? How fast can the critical point of the plant be achieved and what are the measures to prevent this from happening?

The goal of compressing the information is usually to extract from the vast amount of process data only data with highest importance to the system (KPI).

7.7 7 Advanced Process Control and Performance Monitoring

The KPIs, diagnosis information and improvement proposals are visualized in an appropriate form, for example, trends or tables [36].

A pivotal condition for performance monitoring is the real-time processing and interpretation of process data with respective process know-how and process control knowledge. The technical conditions are therefore created through implementation of modern process database (PIMS, process information management system) and process operating system on the MES level (manufacturing execution systems).

By a potential analysis with respect to the energy consumption for the typical chemical plant, the situation pictured on the Figure 7.28 can often be observed. The graph represents specific energy consumption plotted over the range of plant

Usually, the plant operates at higher energy efficiency at higher plant loads. Therefore, operation of the plant at high output levels represents an important measure for improving energy efficiency. If required production levels are significantly lower than capacity, then a variety of operating strategies, including campaign operation, should be considered.

Often fluctuations in energy consumption can be observed that contribute to much higher energy consumption compared with the best practice level as shown in Figure 7.28. The reasons for that happening can range from for example, non-optimal process operation by manual operation, fluctuating purities of raw materials, changing ambient conditions or fouling of the equipment. Therefore, identification of the correct energy-influencing operating parameters by process analysis is important for proper performance monitoring. Once the calculated relationship is presented in a graphical form, the fluctuations can be clearly load.

Best Practice Level

Figure 7.28 Specific steam consumption versus the load of a production process.

Best Practice Level

Losses

Figure 7.28 Specific steam consumption versus the load of a production process.

observed and the assessment of energy efficiency can be carried out very quickly. In addition, it is possible, for instance, to estimate the intensity of fouling and its effect on specific energy consumption by on-line simulation and to visualize them in a clear way [36, 37]. Based on this, it is possible to achieve improved operating conditions of the plant, and consequently reduce the energy consumption. Performance monitoring delivers information about wanted and unwanted variances at an early stage and provides reasons -not only 'gut feeling'-for necessary decisions concerning how to operate the process. The system can also be used as a supervisory control system, for example, by changing set points on programmable controllers.

By creating transparency with performance monitoring the operator only gets the ability to improve. The crucial point to achieve energy efficiency is the regular evaluation of the monitoring, diagnosis and guidance information that should become a daily routine in the production workflow. Differences between actual and expected status should act as a motivation for the operators to undertake appropriate action. In order to achieve sustainable improvements, it is necessary that experts accept and implement the proposed improvements. This can by facilitated by a change program.

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