Plant performance

The next t5 ical catalyst bed in a hydrogen plant is the desulfiirizer bed. The desulfiirizer removes the H2S from the feed gas. The desulfiirizer catalyst bed design is based on the loading of the sulfur compounds. Therefore, the exiting gas from the desulfiirizer bed should be checked to ensure that the sulfur levels are below 0.1 ppmv. If the original design life of the catalyst bed is known, then periodic feedstock analysis can be used to forecast when the bed may require change out. 

The examination of the high temperature shift eatalyst is similar to that of the reforming catalyst. The eatalyst life for the high temperature shift catalyst is approximately 5 years. Pressure drop readings should be taken to cheek for possible catalyst attrition. The outlet composition should be validated with the expected composition with the design approach to equilibrium eonditions. 

The reformer tubes are one of the most important pieces of equipment in a hydrogen plant. These tubes are built from micro-alloyed materials in order to handle the extreme environment in which they are exposed to. The industry standard for reformer tube design is for 100,000 hour life. To ensure that the tubes will last the designed 100,000 hour life, the reformer tubewall 

Tmt is Measured Tube Temperature, °R Tmb is Measured Background Temperature, °R e is Average furnace emissivity (t3q)ical = 0.82) 

The maximum allowable tube stress will need to be calculated in order to calculate the actual reformer tube life. This is accomplished by using the Mean Diameter Formula given below. 

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The UOP Sarex process has been used since 1978 for the separation of high purity fmctose from a mixture of fmctose, glucose, and polysaccharides (87,88). The pilot-plant performance of fmctose—glucose separation is given in Table 6. 

The basic seed processing plant design is based on 70% removal of the sulfur contained in the coal used (Montana Rosebud), which satisfies NSPS requirements. Virtually complete sulfur removal appears to be feasible and can be considered as a design alternative to minimize potential corrosion problems related to sulfur in the gas. The estimated reduction in plant performance for complete removal is on the order of 1/4 percentage point. The size of the seed processing plant would have to be increased by roughly 40% but the corresponding additional cost appears tolerable. The constmction time for the 500 MW plant is estimated to be ca five years. 

Colin S. Howat, Ph.D., P.E., John E. Winfred E. Sharp Professor, Department of Chemical and Petroleum Engineering, University of Kansas Member, American Institute of Chemical Engineers Member, American Society of Engineering Education (Section 30, Analysis of Plant Performance)... 

Since the control calculations are based on optimizing control system performance, MFC can be readily integrated with on-line optimization strategies to optimize plant performance. 

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. 

Rectification accounts for systematic measurement error. During rectification, measurements that are systematically in error are identified and discarded. Rectification can be done either cyclically or simultaneously with reconciliation, and either intuitively or algorithmically. Simple methods such as data validation and complicated methods using various statistical tests can be used to identify the presence of large systematic (gross) errors in the measurements. Coupled with successive elimination and addition, the measurements with the errors can be identified and discarded. No method is completely reliable. Plant-performance analysts must recognize that rectification is approximate, at best. Frequently, systematic errors go unnoticed, and some bias is likely in the adjusted measurements. 

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. 

Because the technical barriers previously outhned increase uncertainty in the data, plant-performance analysts must approach the data analysis with an unprejudiced eye. Significant technical judgment is required to evaluate each measurement and its uncertainty with respec t to the intended purpose, the model development, and the conclusions. If there is any bias on the analysts part, it is likely that this bias will be built into the subsequent model and parameter estimates. Since engineers rely upon the model to extrapolate from current operation, the bias can be amplified and lead to decisions that are inaccurate, unwarranted, and potentially dangerous. 

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