Capturing Thermal Dynamics in Air-Conditioned Rooms
A Data-Driven Approach
DOI:
https://doi.org/10.17979/ja-cea.2024.45.10818Palabras clave:
filtering and smoothing, identifiability, identification for control, software for system identification, model validationResumen
Thermostatically controlled loads (TCLs) play a crucial role in reducing energy consumption in buildings. Thus, developing accurate models that enable the effective implementation of energy control strategies is essential. With this goal in mind, a model of a room influenced by an air conditioning (AC) unit was developed as an initial starting point for our research into TCL systems modeling and control. In this work, a data-driven modeling approach was utilized, employing data collected from an ad-hoc data collection platform. In addition, an algorithm was developed to determine the AC’s operational states. The results, based on RMSE (Root Mean Square Error) and MAXAE (Maximum Absolute Error) metrics, demonstrate the effectiveness of the proposed algorithm and data-driven modeling approach in capturing the thermal dynamics of the room under the influence of the AC unit.
Citas
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Derechos de autor 2024 Gabriel Gómez-Ruiz, Adolfo J. Sánchez, Reyes Sánchez-Herrera, José M. Andújar
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.
