Advances in building energy management systems (BEMS): A comprehensive review with bibliometric analysis and future research directions

Very Sihombing, Erkata Yandri, Kukuh Priyo Pramono, Ratna Ariati

Abstract

Building energy management systems (BEMS) are essential for enhancing energy efficiency and sustainability in buildings. This literature review analyzes BEMS research trends from 1982 to 2024, utilizing bibliometric analysis based on a dataset from Scopus. The study identifies key developments that influence all publications and emerging research topics in the field. While BEMS offers significant potential for real-time energy monitoring and control, challenges remain, including the need for standard protocols, improved cybersecurity, and cost-effective solutions for small buildings. This research highlights the importance of addressing these challenges to foster wider adoption of BEMS technology and contribute to a sustainable energy future. The findings aim to guide future research directions and enhance the implementation of BEMS in various building types.



Keywords


bibliometrics analysis; building energy management systems; building sustainability; energy efficiency; energy monitoring.

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References


Y. Yuan et al., “A novel multi-step Q-learning method to improve data efficiency for deep reinforcement learning,” Knowledge-Based Syst., vol. 175, no. July, pp. 107–117, 2019.

A. Y. Nageye, A. D. Jimale, M. O. Abdullahi, Y. A. Ahmed, and B. S. A. Jama, “Enhancing energy efficiency in Mogadishu: IoT-based buildings energy management system,” SSRG Int. J. Electr. Electron. Eng., vol. 10, no. 10, pp. 54–60, 2023.

A. Irawan et al., “An energy optimization study of the electric arc furnace from the steelmaking process with hot metal charging,” Heliyon, vol. 8, no. 11, p. e11448, 2022.

A. Chojecki, A. Ambroziak, and P. Borkowski, “Fuzzy controllers instead of classical PIDs in HVAC equipment: Dusting off a well-known technology and today’s implementation for better energy efficiency and user comfort,” Energies, vol. 16, no. 7, p. 2967, Mar. 2023.

E. Yandri et al., “Implementation of walk-through audits for designing energy management system: A first step towards an efficient campus,” IOP Conf. Ser. Earth Environ. Sci., vol. 490, no. 1, p. 012005, Apr. 2020.

M. Rumbayan, I. Pundoko, D. Ruindungan, and N. V. Panjaitan, “Development of internet of things-based monitoring system for application solar energy technology in Bunaken island,” IOP Conf. Ser. Earth Environ. Sci., vol. 1041, no. 1, p. 012023, Jun. 2022.

T. Mega, K. Murakami, and N. Kushiro, “BEMS architecture and service modules for realizing sophisticated algorithms,” Electron. Commun. Japan, vol. 106, no. 4, p. 32, Dec. 2023.

M. Hossain, Z. Weng, R. Schiano-Phan, D. Scott, and B. Lau, “Application of IoT and BEMS to visualise the environmental performance of an educational building,” Energies, vol. 13, no. 15, p. 4009, Aug. 2020.

K. Song, Y. Jang, M. Park, H. Lee, and J. Ahn, “Energy efficiency of end-user groups for personalized HVAC control in multi-zone buildings,” Energy, vol. 206, p. 118116, Sep. 2020.

E. Yandri et al., “Recent research progress on sustainable energy management system based on energy efficiency and renewable energy,” BIO Web Conf., vol. 104, p. 00012, May 2024.

O. Pedram, E. Asadi, B. Chenari, P. Moura, and M. Gameiro da Silva, “A review of methodologies for managing energy flexibility resources in buildings,” Energies, vol. 16, no. 17, p. 6111, Aug. 2023.

A. T. Dahiru, D. Daud, C. W. Tan, Z. T. Jagun, S. Samsudin, and A. M. Dobi, “A comprehensive review of demand side management in distributed grids based on real estate perspectives,” Environ. Sci. Pollut. Res., vol. 30, no. 34, pp. 81984–82013, 2023.

D. Mariano-Hernández, L. Hernández-Callejo, A. Zorita-Lamadrid, O. Duque-Pérez, and F. Santos García, “A review of strategies for building energy management system: Model predictive control, demand side management, optimization, and fault detect & diagnosis,” J. Build. Eng., vol. 33, p. 101692, Jan. 2021.

A. Ahmi, “Bibliometric analysis for beginners,” in Bibliometric Analysis for Beginners, Book Pre-P., A. Ahmi, Ed., Malaysia, 2021, pp. 1–180. [Online].

N. Donthu, S. Kumar, D. Mukherjee, N. Pandey, and W. M. Lim, “How to conduct a bibliometric analysis: An overview and guidelines,” J. Bus. Res., vol. 133, no. May, pp. 285–296, 2021.

I. Bernatović, A. Slavec Gomezel, and M. Černe, “Mapping the knowledge-hiding field and its future prospects: a bibliometric co-citation, co-word, and coupling analysis,” Knowl. Manag. Res. Pract., vol. 20, no. 3, pp. 394–409, 2022.

D. Mukherjee, W. M. Lim, S. Kumar, and N. Donthu, “Guidelines for advancing theory and practice through bibliometric research,” J. Bus. Res., vol. 148, no. May, pp. 101–115, 2022.

W. M. Lim and S. Kumar, “Guidelines for interpreting the results of bibliometric analysis: A sensemaking approach,” Glob. Bus. Organ. Excell., vol. 43, no. 2, pp. 17–26, 2024.

F. Rezazadeh and N. Bartzoudis, “A federated DRL approach for smart micro-grid energy control with distributed energy resources,” in 2022 IEEE 27th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), IEEE, Nov. 2022, pp. 108–114.

J. Hossain et al., “A review on optimal energy management in commercial buildings,” Energies, vol. 16, no. 4, 2023.

S. Alawadi, D. Mera, M. Fernández-Delgado, F. Alkhabbas, C. M. Olsson, and P. Davidsson, “A comparison of machine learning algorithms for forecasting indoor temperature in smart buildings,” Energy Syst., vol. 13, no. 3, pp. 689–705, 2022.

A. I. Dounis and C. Caraiscos, “Advanced control systems engineering for energy and comfort management in a building environment—A review,” Renew. Sustain. Energy Rev., vol. 13, no. 6–7, pp. 1246–1261, Aug. 2009.

P. Du and N. Lu, “Appliance commitment for household load scheduling,” IEEE Trans. Smart Grid, vol. 2, no. 2, pp. 411–419, Jun. 2011.

E. Mocanu et al., “On-line building energy optimization using deep reinforcement learning,” IEEE Trans. Smart Grid, vol. 10, no. 4, pp. 3698–3708, Jul. 2019.

H. Doukas, K. D. Patlitzianas, K. Iatropoulos, and J. Psarras, “Intelligent building energy management system using rule sets,” Build. Environ., vol. 42, no. 10, pp. 3562–3569, Oct. 2007.

M. W. Ahmad, M. Mourshed, D. Mundow, M. Sisinni, and Y. Rezgui, “Building energy metering and environmental monitoring – A state-of-the-art review and directions for future research,” Energy Build., vol. 120, pp. 85–102, May 2016.

R. Missaoui, H. Joumaa, S. Ploix, and S. Bacha, “Managing energy smart homes according to energy prices: Analysis of a building energy management system,” Energy Build., vol. 71, pp. 155–167, Mar. 2014.

D. Lee and C.-C. Cheng, “Energy savings by energy management systems: A review,” Renew. Sustain. Energy Rev., vol. 56, pp. 760–777, Apr. 2016.

F. Wang et al., “Multi-objective optimization model of source–load–storage synergetic dispatch for a building energy management system based on TOU price demand response,” IEEE Trans. Ind. Appl., vol. 54, no. 2, pp. 1017–1028, Mar. 2018.

P. Zhao, S. Suryanarayanan, and M. G. Simoes, “An energy management system for building structures using a multi-agent decision-making control methodology,” in 2010 IEEE Industry Applications Society Annual Meeting, IEEE, Oct. 2010, pp. 1–8.

M. A. Hannan et al., “A review of internet of energy based building energy management systems: issues and recommendations,” IEEE Access, vol. 6, no. september 2016, pp. 38997–39014, 2018.

D. Kolokotsa, A. Pouliezos, G. Stavrakakis, and C. Lazos, “Predictive control techniques for energy and indoor environmental quality management in buildings,” Build. Environ., vol. 44, no. 9, pp. 1850–1863, Sep. 2009.

H. Doukas, K. D. Patlitzianas, K. Iatropoulos, and J. Psarras, “Intelligent building energy management system using rule sets,” Build. Environ., vol. 42, no. 10, pp. 3562–3569, Oct. 2007.

D. F. Espejel-Blanco, J. A. Hoyo-Montano, J. M. Chavez, and F. A. Hernandez-Aguirre, “Environment sensor node design for building energy management systems (BEMS),” in 2023 IEEE Conf. Technol. Sustain. (SusTech), pp. 99–103, 2023.

N. T. Ngo, N. S. Truong, T. T. H. Truong, A. D. Pham, and N. T. Huynh, “Implementing a web-based optimized artificial intelligence system with metaheuristic optimization for improving building energy performance,” J. Asian Archit. Build. Eng., vol. 23, no. 1, pp. 264–281, 2024.

A. Fetanat, M. Tayebi, G. Shafipour, and M. Moteraghi, “A novel integrated method of fsQCA and digital design for sustainability monitoring and assessment in building energy management systems: a case study,” J. Build. Perform. Simul., vol. 16, no. 1, pp. 107–130, 2023.

J. G. B. Abad, D. G. Romero, J. M. Dolalas, R. C. Parocha, and E. Q. B. Macabebe, “MQTT based appliance control and automation with room occupancy monitoring using YOLO,” in Lecture Notes in Networks and Systems, 2022, pp. 757–770.

L. Ma, Y. Huang, and T. Zhao, “A synchronous prediction method for hourly energy consumption of abnormal monitoring branch based on the data-driven,” Energy Build., vol. 260, p. 111940, Apr. 2022.

O. B. M. Magtibay, R. H. Cabrera, J. P. Roxas, and M. A. de Vera, “Green switch: An IoT based energy monitoring system for mabini building in De La Salle Lipa,” Indones. J. Electr. Eng. Comput. Sci., vol. 24, no. 2, pp. 754–761, 2021.

O. Kotevska and P. Andelfinger, “Reinforcement learning for intelligent building energy management system control*,” in Intelligent Data Mining and Analysis in Power and Energy Systems, Wiley, 2022, pp. 371–386.

M. Subramaniam A., T. Jain, and J. J. Yamé, “Bilinear observer-based robust adaptive fault estimation for multizone building VAV terminal units,” J. Build. Perform. Simul., vol. 16, no. 6, pp. 717–733, Nov. 2023.

D. P. Finn and C. J. Doyle, “Control and optimization issues associated with algorithm-controlled refrigerant throttling devices,” in ASHRAE Transactions, 2000. [Online].

A. Burda, D. Bitner, F. Bestehorn, C. Kirches, and M. Grotjahn, “Mixed-integer real-time control of a building energy supply system,” IEEE Control Syst. Lett., vol. 7, pp. 907–912, 2023.

A. Banjac, H. Novak, and M. Vašak, “Implementation of model predictive indoor climate control for hierarchical building energy management,” Control Eng. Pract., vol. 136, no. september 2016, p. 105536, Jul. 2023.

C. Zhang, Y. Shi, and Y. Chen, “BEAR: physics-principled building environment for control and reinforcement learning,” in 14th ACM Int. Conf. Futur. Energy Syst. (e-Energy 2023), pp. 66–71, 2023.

K. Kurte, K. Amasyali, J. Munk, and H. Zandi, “Deep reinforcement learning with online data augmentation to improve sample efficiency for intelligent HVAC control,” in Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, New York, NY, USA: ACM, Nov. 2022, pp. 479–483.

S. Mohan Krishna, T. Perumal, S. Surya, and Chandrashekar, “Interoperability in IoT-driven smart buildings,” in Internet of Things in Modern Computing, no. september 2016, Boca Raton: CRC Press, 2023, pp. 133–142.

H. Agharazi et al., “Installation and testing of a two-level model predictive control building energy management system,” IEEE Trans. Control Syst. Technol., vol. 32, no. 2, pp. 326–339, Mar. 2024.

H. Elehwany, M. Ouf, B. Gunay, N. Cotrufo, and J.-S. Venne, “A reinforcement learning approach for thermostat setpoint preference learning,” Build. Simul., vol. 17, no. 1, pp. 131–146, Jan. 2024.

A. A. bin Mohd Ameeruddin, W.-N. Tan, M.-T. Gan, and S.-C. Yip, “Predictive AC control using deep learning: improving comfort and energy saving,” JOIV Int. J. Informatics Vis., vol. 7, no. 3–2, p. 1066, Nov. 2023.

M. Habib, E. Bollin, and Q. Wang, “battery energy management system using edge-driven fuzzy logic,” Energies, vol. 16, no. 8, 2023.

R. Selvaraj, V. M. Kuthadi, and S. Baskar, “Smart building energy management and monitoring system based on artificial intelligence in smart city,” Sustain. Energy Technol. Assessments, vol. 56, p. 103090, Mar. 2023.

S. Sarkar, A. Karthick, V. Kumar Chinnaiyan, and P. P. Patil, “Energy forecasting of the building-integrated photovoltaic façade using hybrid LSTM,” Environ. Sci. Pollut. Res., vol. 30, no. 16, pp. 45977–45985, Jan. 2023.

E. Zarate-Perez, C. Santos-Mejía, and R. Sebastián, “Global trends in building energy management systems (BEMS): A science mapping approach,” in AIP Conference Proceedings, 2023, p. 020038.

S. Yang, H. Oliver Gao, and F. You, “Model predictive control in phase-change-material-wallboard-enhanced building energy management considering electricity price dynamics,” Appl. Energy, vol. 326, p. 120023, Nov. 2022.

Z. Hu, Y. Gao, S. Ji, M. Mae, and T. Imaizumi, “Improved multistep ahead photovoltaic power prediction model based on LSTM and self-attention with weather forecast data,” Appl. Energy, vol. 359, p. 122709, Apr. 2024.

A. Jozi, T. Pinto, L. Gomes, G. Marreiros, and Z. Vale, “rule-based system for intelligent energy management in buildings,” in Экономика Региона, 2023, pp. 169–181.

M. F. Faiz, M. Sajid, S. Ali, K. Javed, and Y. Ayaz, “Energy modeling and predictive control of environmental quality for building energy management using machine learning,” Energy Sustain. Dev., vol. 74, pp. 381–395, Jun. 2023.

M. Ye, A. A. Serageldin, H. Sato, and K. Nagano, “Field study on indoor thermal comfort of a ‘ZEB Ready’ office building using radiant ceiling panel coupled with open-loop ground source heat pump,” in Environmental Science and Engineering (ESE), 2023, pp. 2353–2362.

M. Roccotelli, A. Rinaldi, M. P. Fanti, and F. Iannone, “Building energy management for passive cooling based on stochastic occupants behavior evaluation,” Energies, vol. 14, no. 1, p. 138, Dec. 2020.

N. Bucarelli and N. El-Gohary, “Deep learning approach for recognizing cold and warm thermal discomfort cues from videos,” Build. Environ., vol. 242, no. september 2016, p. 110277, Aug. 2023.

M. K. Yadav, A. Rampal, A. Verma, and B. K. Panigrahi, “Energy analysis of smart lighting system considering visual comfort of occupants for educational building,” in 2019 International Conference on Computing, Power and Communication Technologies (GUCON 2019), 2019, pp. 572–577. [Online].

A. Das, M. K. Annaqeeb, E. Azar, V. Novakovic, and M. B. Kjærgaard, “Occupant-centric miscellaneous electric loads prediction in buildings using state-of-the-art deep learning methods,” Appl. Energy, vol. 269, p. 115135, Jul. 2020.

A. Boodi, K. Beddiar, M. Benamour, Y. Amirat, and M. Benbouzid, “Intelligent systems for building energy and occupant comfort optimization: A state of the art review and recommendations,” Energies, vol. 11, no. 10, 2018.

N. Daurenbayeva, L. Atymtayeva, and A. Nurlanuly, “Choosing the intelligent thermostats for the effective decision making in BEMS,” in 2023 17th International Conference on Electronics Computer and Computation (ICECCO), IEEE, Jun. 2023, pp. 1–4.

E. Saloux and K. Zhang, “Towards integration of virtual meters into building energy management systems: Development and assessment of thermal meters for cooling,” J. Build. Eng., vol. 65, p. 105785, Apr. 2023.

M. Amin, G. A. Abdel Aziz, M. Naraghi, M. Palatty, A. Benz, and D. Ruiz, “Improving the data center servers cooling efficiency via liquid cooling-based heat pipes,” in 2020 IEEE Ind. Appl. Soc. Annu. Meet., pp. 3–7, 2020.

L. Desmomd and M. Salama, “Integrating blockchain & emerging technologies for sustainability assurance in the built environment,” in 2023 IEEE International Conference on Artificial Intelligence, Blockchain, and Internet of Things (AIBThings), IEEE, Sep. 2023, pp. 1–5.

P. Yefi, R. Menon, and U. Eicker, “Building IoT systems modeling: An object-oriented metamodeling approach,” in 2023 IEEE/ACM 5th International Workshop on Software Engineering Research and Practices for the IoT (SERP4IoT), IEEE, May 2023, pp. 1–8.

J. Lim, W. Ong, U. Tefek, and E. Esiner, “A security policy engine for building energy management systems,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2023, pp. 231–244.


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