Real-time optimization applications

Fatora III, F. C. Gochenour, G. B. and Kelly, D. N., "Modeling Ethylene Plants for Real-Time Optimization Applications", Paper Presented at the National AIChE Meeting (April 1992). 

The use of online data together with steady-state models, as in Real Time Optimization applications, requires the identification of steady-state regimes in a process and the detection of the presence of gross errors. In this paper a method is proposed which makes use of polynomial interpolation on time windows. The method is simple because the parameters in which it is based are easy to tune as they are rather intuitive. In order to assess the performance of the method, a comparison based on Monte-Carlo simulations was performed, comparing the proposed method to three methods extracted from literature, for different noise to signal ratios and autocorrelations. 

Some recent applications have benefited from advances in computing and computational techniques. Steady-state simulation is being used off-line for process analysis, design, and retrofit process simulators can model flow sheets with up to about a million equations by employing nested procedures. Other applications have resulted in great economic benefits these include on-line real-time optimization models for data reconciliation and parameter estimation followed by optimal adjustment of operating conditions. Models of up to 500,000 variables have been used on a refinery-wide basis. 

Nonlinear Programming The most general case for optimization occurs when both the objective function and the constraints are nonlinear, a case referred to as nonlinear programming. While the ideas behind the search methods used for unconstrained multivariable problems are applicable, the presence of constraints complicates the solution procedure. All the methods discussed below have been utilized to solve nonlinear programming problems in the field of chemical engineering design and operations. Nonlinear programming is now used extensively in the area of real-time optimization. 

Nowadays every Brazilian oil refinery has at least one operating advanced control application. This is the result of many years of investment in hardware, software and the development of hirnian resources. Additionally, real time optimization systems are being successfully implemented in many imits. 

Real-time optimization or on-line optimization has proven itself to be an effective form of process optimization for delivering lasting economic benefit. The objective of this entry is to provide the reader with a concise, yet comprehensive introduction to RTO that discusses the challenges, benefits, and opportunities for RTO the range of applicability of RTO the current status of RTO technology and the research on which this technology is based. 

For particular cases, it maybe required to add more complex phenomena with additional effects or more evolved descriptions of the same mechanisms. In general, however, reduced models are appropriate and desirable. Historically, this stemmed from the shorter computational effort and time required for the numerical solution of such models. Today this is also an advantage for optimization, control, and real-time simulation applications, and reliable simplified models are still used for almost all purposes due to the lower number of dimensionless parameters requiring estimation and to the success found in the description of experimental results. On the other hand, complex detailed models fulfill the most generic purpose of reactor simulation, which is related to the prediction of the actual behavior from fundamental, independently measured parameters. Therefore, it is important to understand the equivalence and agreement between both detailed and reduced models, so as to take advantage of their predictive power without unnecessary effort. 

In particular, nonlinear model predictive control and dynamic real-time optimization are recent online applications of dynamic optimization. 

The open and modular characteristics of the software created as well as the strict adherence to present and emerging standards should ease application to other scenarios. It can be also concluded that the pathway for real-time optimization in batch procelsses is becoming a reality. 

They tackle the problem by evaluating the importance of each pixel and apply high or low quality DOF (Depth Of Field) renderings. The adaption of these methods from computer imaging to photographs has been presented by Yu et al. [70]. Zhan et al. [71] introduced a real-time optimized implementation of the artificial depth-of-field synthesis proposed by Yu et al. to utilize this technique in video applications. 

Application 1 Maximize operating profit In Chapter 19, real-time optimization was considered problems where the operating profit was expressed in terms of product values and feedstock and utility costs. If the product, feedstock, and utility flow rates are manipulated or disturbance variables in the MPC control structure, they can be included in objective function Js- In order to maximize the operating profit OP), the objective function is specified to be Js = —OP, because minimizing is equivalent to maximizing The weighting matrices for two quadratic terms, Qsp and Rsp, are set equal to zero. 

The next section describes the utilization of //PLC for different applications of interest in the pharmaceutical industry. The part discusses the instrumentation employed for these applications, followed by the results of detailed characterization studies. The next part focuses on particular applications, highlighting results from the high-throughput characterization of ADMET and physicochemical properties (e.g., solubility, purity, log P, drug release, etc.), separation-based assays (assay development and optimization, real-time enzyme kinetics, evaluation of substrate specificity, etc.), and sample preparation (e.g., high-throughput clean-up of complex samples prior to MS (FIA) analysis). 

This section describes recent applications of jitPEC methodologies for separation-based enzymatic assays. It covers the most common applications (1) those involving the development and optimization of assays (2) those in which jitPLC is use to evaluate real-time enzyme kinetics and (3) those in which /./PEC is used to determine substrate specificity. 

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