Research Article

Development of a Building Simulation Model for Indoor Temperature Prediction and HVAC System Anomaly Detection

Volume: 7 Number: 4 December 31, 2023
EN

Development of a Building Simulation Model for Indoor Temperature Prediction and HVAC System Anomaly Detection

Abstract

In order to reduce global energy consumption, energy-efficient, green and smart buildings have to be built. In addition to the application of other energy efficiency measures, an effective management of HVAC systems is required. High quality management and control of these systems ensures optimal occupant comfort levels, proper operation, rational energy consumption, and a positive impact on the environment. This is especially important for large buildings with complex systems such as hotels. As a contribution to the creation of appropriate tools for the management and control of HVAC systems in smart buildings, this paper presents the results of the current development of a detailed dynamic simulation model based on data collected from a smart room system in a hotel in Zagreb, Croatia. The smart room system, which is integrated into the hotel's building management system, provides historical data on set and current room temperatures, room occupancy schedule, window opening, fan coil operation status, fan rotation speed, valve opening, and operating mode with a time step of 5 minutes. The simulation model based on the TRNSYS software uses a part of the available data and calculates the current internal room temperatures. A comparison of the predicted and measured temperatures at each time step showed that the deviations are within the acceptable limits. The final objectives of the model development are the identification of anomalies in the operation of the HVAC system and the optimization of its operation with the aim of reducing energy consumption.

Keywords

Supporting Institution

This work was supported in part by European Regional Development Fund (ERDF) under grant agreement number KK.01.2.1.02.0303, project Adria Smart Room. TRNSYS software was provided by Croatian Science Foundation under the project HEXENER (IP-2016-06-4095).

References

  1. [1] Mariano-Hernández, D, Hernández-Callejo, L, Zorita-Lamadrid, A, Duque-Pérez, O, Santos García, F. A review of strategies for building energy management system: Model predictive control, demand side management, optimization, and fault detect & diagnosis. Journal of Building Engineering 2021; 33: 101692, DOI: 10.1016/j.jobe.2020.101692
  2. [2] Drgoňa, J, Arroyo, J, Cupeiro Figueroa, I, Blum, D, Arendt, K, Kim, D, Perarnau Ollé, E, Oravec, J, Wette, M, Vrabie, D, Helsen, L. All you need to know about model predictive control for buildings. Annual Reviews in Control 2020; 50: 190-232, DOI: 10.1016/j.arcontrol.2020.09.001
  3. [3] Kampelis, N, Papayiannis, GI, Kolokotsa, D, Galanis, GN, Isidori, D, Cristalli, C, Yannacopoulos, AN. An integrated energy simulation model for buildings. Energies 2020, 13(5):1170, DOI: 10.3390/en13051170
  4. [4] Huang, H, Chen, L, Hu, E. A neural network-based multi-zone modelling approach for predictive control system design in commercial buildings. Energy and Buildings 2015; 97: 86-97, DOI: 10.1016/j.enbuild.2015.03.045
  5. [5] Rao, DMKKV, Ukil, A. Modeling of room temperature dynamics for efficient building energy management. IEEE Transactions on Systems, Man, and Cybernetics: Systems 2020; 50(2): 717-725, DOI: 10.1109/TSMC.2017.2758766
  6. [6] Afroz, Z, Shafiullah, GM, Urmee, T, Higgins, G. Modeling techniques used in building HVAC control systems: A review. Renewable and Sustainable Energy Reviews 2018; 83: 64-84, DOI: 10.1016/j.rser.2017.10.044
  7. [7] Reis, AS, Vaquero, P, Dias, MF, Tavares, A, Costa, A, Fonseca, J. Residential building rehabilitation in Porto historic center: Case study analysis by using a simulation model. Energy Reports 2022; 8(3): 437-441, DOI: https://doi.org/10.1016/j.egyr.2022.01.048
  8. [8] Qiu, S, Li, Z, Pang, Z, Zhang, W, Li, Z. A quick auto-calibration approach based on normative energy models. Energy and Buildings 2018; 172: 35-46, DOI: 10.1016/j.enbuild.2018.04.053

Details

Primary Language

English

Subjects

Engineering, Mechanical Engineering

Journal Section

Research Article

Early Pub Date

December 15, 2023

Publication Date

December 31, 2023

Submission Date

February 17, 2023

Acceptance Date

September 25, 2023

Published in Issue

Year 2023 Volume: 7 Number: 4

APA
Palaić, D., štajduhar, I., Ljubic, S., Matetić, I., & Wolf, I. (2023). Development of a Building Simulation Model for Indoor Temperature Prediction and HVAC System Anomaly Detection. Journal of Energy Systems, 7(4), 339-349. https://doi.org/10.30521/jes.1251339
AMA
1.Palaić D, štajduhar I, Ljubic S, Matetić I, Wolf I. Development of a Building Simulation Model for Indoor Temperature Prediction and HVAC System Anomaly Detection. Journal of Energy Systems. 2023;7(4):339-349. doi:10.30521/jes.1251339
Chicago
Palaić, Darko, Ivan štajduhar, Sandi Ljubic, Iva Matetić, and Igor Wolf. 2023. “Development of a Building Simulation Model for Indoor Temperature Prediction and HVAC System Anomaly Detection”. Journal of Energy Systems 7 (4): 339-49. https://doi.org/10.30521/jes.1251339.
EndNote
Palaić D, štajduhar I, Ljubic S, Matetić I, Wolf I (December 1, 2023) Development of a Building Simulation Model for Indoor Temperature Prediction and HVAC System Anomaly Detection. Journal of Energy Systems 7 4 339–349.
IEEE
[1]D. Palaić, I. štajduhar, S. Ljubic, I. Matetić, and I. Wolf, “Development of a Building Simulation Model for Indoor Temperature Prediction and HVAC System Anomaly Detection”, Journal of Energy Systems, vol. 7, no. 4, pp. 339–349, Dec. 2023, doi: 10.30521/jes.1251339.
ISNAD
Palaić, Darko - štajduhar, Ivan - Ljubic, Sandi - Matetić, Iva - Wolf, Igor. “Development of a Building Simulation Model for Indoor Temperature Prediction and HVAC System Anomaly Detection”. Journal of Energy Systems 7/4 (December 1, 2023): 339-349. https://doi.org/10.30521/jes.1251339.
JAMA
1.Palaić D, štajduhar I, Ljubic S, Matetić I, Wolf I. Development of a Building Simulation Model for Indoor Temperature Prediction and HVAC System Anomaly Detection. Journal of Energy Systems. 2023;7:339–349.
MLA
Palaić, Darko, et al. “Development of a Building Simulation Model for Indoor Temperature Prediction and HVAC System Anomaly Detection”. Journal of Energy Systems, vol. 7, no. 4, Dec. 2023, pp. 339-4, doi:10.30521/jes.1251339.
Vancouver
1.Darko Palaić, Ivan štajduhar, Sandi Ljubic, Iva Matetić, Igor Wolf. Development of a Building Simulation Model for Indoor Temperature Prediction and HVAC System Anomaly Detection. Journal of Energy Systems. 2023 Dec. 1;7(4):339-4. doi:10.30521/jes.1251339

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