Real-time optimization (RTO) is widely used in industry to improve the steady-state performance of a process using the available measurements, reacting to changing prices and demands scenarios and respecting operating, contractual, and environmental constraints. Traditionally, RTO has used nonlinear continuous formulations to model the process. Mixed- Integer formulations have not been used in RTO, because of the need of a fast solution (on the order of seconds or a few minutes), and because many discrete decisions, such as startups or shutdowns, are taken with less frequency in a scheduling layer. This work proposes the use of disjunctions in RTO models, listing a series of examples of discrete decisions (different to startups or shutdowns...
Due to current changes in the global market with increasing competition, strict bounds on product sp...
In the context of real-time optimization, modifier-adaptation schemes update the model-based optimiz...
For good performance in practice, real-time optimization schemes need to be able to deal with the in...
Real-time optimization (RTO) is widely used in industry to improve the steady-state performance of a...
ABSTRACT. Real-time optimization (RTO) is a class of methods that use measurements to reject the eff...
The rise of new digital technologies and their applications in several areas pushes the process indu...
Throughout the petroleum and chemicals industry, the control and optimization of many large-scale sy...
In the framework of real-time optimization, measurements are used to compensate for effects of uncer...
In dynamic optimization problems, the optimal input profiles are typically obtained using models tha...
The idea of iterative process optimization based on collected output measurements, or "real-time opt...
Real-time optimization (RTO) is widely used in industry to operate processes close to their maximum ...
The idea of iterative process optimization based on collected output mea-surements, or “real-time op...
Real-time optimization (RTO) is an established technology, where the process economics are optimized...
A new solution method for solving the real time production optimization (RTPO) problem for a petrole...
Process optimization is the method of choice for improving the performance of industrial processes, ...
Due to current changes in the global market with increasing competition, strict bounds on product sp...
In the context of real-time optimization, modifier-adaptation schemes update the model-based optimiz...
For good performance in practice, real-time optimization schemes need to be able to deal with the in...
Real-time optimization (RTO) is widely used in industry to improve the steady-state performance of a...
ABSTRACT. Real-time optimization (RTO) is a class of methods that use measurements to reject the eff...
The rise of new digital technologies and their applications in several areas pushes the process indu...
Throughout the petroleum and chemicals industry, the control and optimization of many large-scale sy...
In the framework of real-time optimization, measurements are used to compensate for effects of uncer...
In dynamic optimization problems, the optimal input profiles are typically obtained using models tha...
The idea of iterative process optimization based on collected output measurements, or "real-time opt...
Real-time optimization (RTO) is widely used in industry to operate processes close to their maximum ...
The idea of iterative process optimization based on collected output mea-surements, or “real-time op...
Real-time optimization (RTO) is an established technology, where the process economics are optimized...
A new solution method for solving the real time production optimization (RTPO) problem for a petrole...
Process optimization is the method of choice for improving the performance of industrial processes, ...
Due to current changes in the global market with increasing competition, strict bounds on product sp...
In the context of real-time optimization, modifier-adaptation schemes update the model-based optimiz...
For good performance in practice, real-time optimization schemes need to be able to deal with the in...