Ponencia
Neuro-Fuzzy Digital Twin of a High Temperature Generator
Autor/es | Chicaiza Salazar, William David
Ortiz Machado, Diogo Gallego Len, Antonio Javier Escaño González, Juan Manuel Bordons Alba, Carlos Andrade, Gustavo A. de Normey Rico, Julio Elías |
Departamento | Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática |
Fecha de publicación | 2022 |
Fecha de depósito | 2023-02-21 |
Publicado en |
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ISBN/ISSN | 2405-8963 |
Resumen | Solar absorption plants are renewable energy systems with a special advantage: the cooling demand follows the solar energy source. The problem is that this plant presents solar intermittency, phenomenological complexity, ... Solar absorption plants are renewable energy systems with a special advantage: the cooling demand follows the solar energy source. The problem is that this plant presents solar intermittency, phenomenological complexity, and nonlinearities. That results in a challenge for control and energy management. In this context, this paper develops a Digital Twin of an absorption chiller High Temperature Generator (HTG) seeking accuracy and low computational efort for control and management purposes. A neuro-fuzzy technique is applied to describe HTG, internal Lithium-Bromide temperature, and water outlet temperature. Two Adaptative Neuro-Fuzzy Inference Systems (ANFIS) are trained considering real data of eight days of operation. Then, the obtained model is validated considering two days of real data. The validation shows a RMSE of 1.65e−2 for the internal normalized temperature, and 2.05e−2 for the outlet normalized temperature. Therefore, the obtained Digital Twin presents a good performance capturing the dynamics of the HTG with adaptive capabilities considering that each day can update the learning step. |
Cita | Chicaiza Salazar, W.D., Ortiz Machado, D., Gallego Len, A.J., Escaño González, J.M., Bordons Alba, C., Andrade, G. A. de y Normey Rico, J.E. (2022). Neuro-Fuzzy Digital Twin of a High Temperature Generator. En 11th IFAC Symposium on Control of Power and Energy Systems, CPES 2022, IFAC-PapersOnLine, 55(9) (466-471), Virtual, Online: Elsevier. |
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