A predictive model of indoor air temperature evaluation in a semi-arid climate
DOI:
https://doi.org/10.46421/entac.v19i1.2058Keywords:
Thermal performance, Thermal inertia, Linear RegressionAbstract
Predictive models for air temperature can be used to improve the thermal quality in indoor environments and the building's thermal performance. This study evaluated a simple air temperature predictive method. The air temperature is estimated considering the moving average of the outdoor temperatures of previous hours by implementing linear regression. For this purpose, a naturally ventilated dwelling was measured for 89 days in Aracati/CE, located in a semi-arid climate. The results were evaluated considering the root mean square error and the mean bias error. It was evidenced the good adjustment of the estimated values to the measured data.
References
Centers for Disease Control and Prevention. Protecting Vulnerable Groups from Extreme Heat. Heat and Older Adults. 2017. Disponível em: https://www.cdc.gov/disasters/extremeheat/older-adults-heat.html. Acesso em: 03 abril 2022.
FERNANDES, L. C. et al. Estimativa de temperaturas internas horárias de edificações a partir de temperaturas externas: proposta de método alternativo. In: XIII Encontro Nacional e IX Encontro Latino-americano de Conforto no Ambiente Construído – Campinas. Anais... Campinas: ENCAC e ELACAC, 2015.
FERNANDES, L. C. Experimentos de campo com teto-reservatório: desempenho térmico e percepção do usuário. 2018. Tese (Doutorado em Tecnologia) - Programa de Pós-Graduação em Tecnologia e Sociedade, Universidade Tecnológica Federal do Paraná, 2018.
GIVONI, B. Minimum Climatic Information Needed To Predict. In: THE INTERNATIONAL CONFERENCE ON PASSIVE AND LOW ENERGY ARCHITECTURE – PLEA’99 1999, Brisbane. Proceedings... Brisbane: PLEA, 1999.
HIETAHARJU, Petri; RUUSUNEN, Mika; LEIVISKÄ, Kauko. A dynamic model for indoor temperature prediction in buildings. Energies, v. 11, n. 6, p. 1477, 2018.
JIN, J.; SHU, S.; LIN, F. Prediction of Indoor Air Temperature Based on Deep Learning. Sensors and Materials, v. 31, n. 6, p.2029-2042, 2019.
KRÜGER, E. L. et al. Proposition of a simplified method for predicting hourly indoor temperatures in test cells. Ambiente Construído, v. 17, p. 57-70, 2017.
LI, X.; ZHAO, T., ZHANG, J., CHEN, T. Predication control for indoor temperature time-delay using Elman neural network in variable air volume system. Energy and Buildings, v. 154, p.454-552, 2017.
PAPST, A. L. Método Estimativo da Temperatura Interna de Edificações Residenciais em Uso. PhD Thesis (Programa de Pós-Graduação em Engenharia Civil) – Universidade Federal de Santa Catarina, Florianópolis, 2004.
SHI, X.; LU, W., ZHAO, Y.; QIN, P. Prediction of Indoor Temperature and Relative Humidity Based on Cloud Database by Using an Improved BP Neural Network in Chongqing. IEEE Access Multidisciplinary Open Access Journal, v.6, p.30559-30566, 2018.
SONG, J.; XUE, G.; MA, Y.; LI, H.; PAN, Y.; HAO, Z. An Indoor Temperature Prediction Framework Based on Hierarchical Attention Gated Recurrent Unit Model for Energy Efficient Buildings. IEEE Access Multidisciplinary Open Access Journal, v.7, p.157268-157283, 2019.
XU, Chengliang et al. Improving prediction performance for indoor temperature in public buildings based on a novel deep learning method. Building and Environment, v. 148, p. 128-135, 2019.
