Plant performance, analysis

MacDonald, R.J. and C.S. Howat, Data Reconciliation and Parameter Estimation in Plant Performance Analysis, AlChE Journal, 34(1), 1988, 1-8. (Parameter estimation)... 

The goal of plant-performance analysis is to develop an accurate understanding of plant operations. This understanding can be used to ... 

The results of plant-performance analysis ultimately lead to a more efficient, safe, profitable operation. 

Historical Definition Plant-performance analysis has been defined as the reconcihation, rec tification, and interpretation of plant... 

Plant-Performance Triangle This view of plant-performance analysis is depicted in Fig. 30-1 as a plant-performance triangle. Figure 30-2 provides a key to the symbols used. 

Extended Plant-Performance Triangle The historical representation of plant-performance analysis in Fig. 30-1 misses one of the principal a ects identification. Identification establishes troubleshooting hypotheses and measurements that will support the level of confidence required in the resultant model (i.e., which measurements will be most beneficial). Unfortunately, the relative impact of the measurements on the desired end use of the analysis is frequently overlooked. The most important technical step in the analysis procedures is to identify which measurements should be made. This is one of the roles of the plant-performance engineer. Figure 30-3 includes identification in the plant-performance triangle. 

Unit layout as installed is the next step of preparation. This may take some effort if analysts have not been involvea with the unit prior to the plant-performance analysis. The equipment in the plant should correspond to that shown on the PFDs and P IDs. Wmere differences are found, analysts must seek explanations. While a hne-by-line trace is not required, details of the equipment installation and condition must be understood. It is particularly useful to correlate the sample and measurement locations and the bypasses shown on the P IDs to those ac tuaUy piped in the unit. Gas vents and liquid (particularly water-phase) discharges may have been added to the unit based on operating experience out not shown on the P IDs. While these flows may ultimately be small within the context of plant-performance an ysis, they may have sufficient impact to alter conclusions regarding trace component flows, particularly those that have a tendency to build in a process. 

These potential sampling problems must be solved in advance of the unit test. The conclusions drawn from any unit test are strongly affected by the accuracy of the sampling methods and the resultant analyses. Methods should be discussed and practiced before the actual unit test. Analysts should use the trial measurements in prehm-inary plant-performance analysis to ensure that the results will be use-bil during the actual unit test. 

Consider Fig. 30-10. This is a single unit process with one input and two output streams. The goal for plant-performance analysis is to understand accurately the operation of this unit. 

Plant-performance analysis reqmres the proper analysis of limited, uncertain plant measurements to develop a model of plant operations for troubleshooting, design, and control. 

The purpose of the plant-performance analysis is to operate on the set of measurements obtained, subject to the equipment constraints to troubleshoot to develop models or to estimate values for model parameters. 

Measurement Selection The identification of which measurements to make is an often overlooked aspect of plant-performance analysis. The end use of the data interpretation must be understood (i.e., the purpose for which the data, the parameters, or the resultant model will be used). For example, building a mathematical model of the process to explore other regions of operation is an end use. Another is to use the data to troubleshoot an operating problem. The level of data accuracy, the amount of data, and the sophistication of the interpretation depends upon the accuracy with which the result of the analysis needs to oe known. Daily measurements to a great extent and special plant measurements to a lesser extent are rarelv planned with the end use in mind. The result is typically too little data of too low accuracy or an inordinate amount with the resultant misuse in resources. 

Pal, P., Ahammad, Z. and Bhattacharya, P. (2007) ARSEPPA a visual basic software tool for arsenic separation plant performance analysis. Chemical Engineering Journal, 129(1-3), 113-22. 

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