Model Adaptation for Real-Time Optimization in Energy Systems

Real-time optimization (RTO) is widely used in industry to operate processes close to their maximum performance. The models used for RTO need to be adapted using real-time data to ensure feasibility of the model optimal inputs and convergence to the real plant optimal point. Heat and power systems are suitable for being optimized in real-time because of their fast dynamics and the benefits achievable by reacting to changes in power prices and steam demand. This work proposes a modifier adaptation strategy that exploits the structure of certain problems to make the adaptation faster and more reliable, which is proven to be particularly useful for heat and power systems. The adaptation is performed in the equations that predict efficiencies or performance of unit operations. By identifying the variables that modify each performance factor, the number of data sets needed for gradient correction is reduced. This makes the proposed strategy suitable for real-time optimization of processes with a large number of inputs. Two alternatives are proposed to implement the approach: gradient calculation by finite differences and quadratic regression using current and past data. The features and behavior of this approach are shown through two case studies: (i) a simple model with three processes, and (ii) a heat and power system of a sugar and ethanol plant. A comparison with other existent approaches shows a better performance in terms of operating cost and sensitivity to noise.Fil: Serralunga, Fernán José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Santa Fe. Instituto de Desarrollo y Diseño (i); Argentina;Fil: Mussati, Miguel Ceferino. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Santa Fe. Instituto de Desarrollo y Diseño (i); Argentina;Fil: Aguirre, Pio Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Santa Fe. Instituto de Desarrollo y Diseño (i); Argentina

Optimización en tiempo real con disyunciones lógicas: aplicación a sistemas de calor y potencia

La Optimización en Tiempo Real (RTO) permite operar en cercanías del óptimo económico de una planta, respetando restricciones y respondiendo a cambios en el proceso. La adaptación con términos modificadores de las restricciones y los gradientes corrige eficientemente los errores estructurales de los modelos de RTO. Este trabajo propone el uso de RTO incluyendo disyunciones lógicas en el problema de optimización, y plantea una estrategia de adaptación con modificadores para este problema. La estrategia se muestra a través de un caso de estudio que consiste en un sistema de generación de vapor y potencia. Los resultados obtenidos muestran la validez de la estrategia sugerida y la utilidad de incluir variables discretas o disyunciones en los sistemas de RTO.Fil: Serralunga, Fernán José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); ArgentinaFil: Mussati, Miguel Ceferino. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); ArgentinaFil: Aguirre, Pio Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); Argentin

Energy Management: A polish case study

Grupa LOTOS, a vertically integrated oil company working in the field of crude oil production, refining, and oil products distribution, employs an online model, Visual MESA, to monitor and optimize the energy system. The energy system is based around several steam pressure levels, with a set of fired boilers producing high pressure steam, a set of steam turbo generators producing electricity, and a set of process heaters which can run with fuel gas and fuel oil. The steps of the system include data collection and control system review, software installation, model building and optimization configuration, midpoint review and users training, and burn in period. An important monitoring aspect of the system include the continuous auditing of the energy system so the data can be relied on for evaluating the value of energy production and usage, and waste can be eliminated. Imbalances are flagged graphically by using balloons of different colors and sizes.Fil: Majchrowicz, J.. Grupa Lotos S.a., Gdansk Refinery; PoloniaFil: Herra, M.. Grupa Lotos S.a., Gdansk Refinery; PoloniaFil: Serralunga, Fernán José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Ruiz, D.. Soteica Europe S.l.; Españ

Including Disjunctions in Real-Time Optimization

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) that can be addressed by RTO. Two model adaptation approaches (the two-step approach and the modifier adaptation strategy) are revised and modified to make them suitable for RTO with discrete decisions. Some common techniques used in RTO (such as filtering the optimal inputs) are also analyzed and adapted for a formulation with disjunctions. The performance of RTO with disjunctions is shown by a case study in which a generic process is optimized. The results show that the performance of a process can be improved by RTO with discrete decisions. The system converges to the vicinity of the real plant optimum when constraints gradients are corrected, even under structural and parametric mismatch.Fil: Serralunga, Fernán José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Aguirre, Pio Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Mussati, Miguel Ceferino. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentin

Making the most of it

The authors demonstrate how a reduction in energy costs was achieved at the SARAS refinery complex.Fil: Diego Ruiz. Soteica Europe SL; EspañaFil: Serralunga, Fernán José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); Argentina. Soteica Europe SL; EspañaFil: Diana, Gian Luigi. SARAS SPA; ItaliaFil: Floris, Pinuccio. SARAS SPA; ItaliaFil: Mallica, Francesco. SARAS SPA; Itali