A Review on Building Energy Efficiency Techniques
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2018-11-30 https://doi.org/10.14419/ijet.v7i4.35.22318 -
-use, building energy efficiency, occupant behavior-based energy-use prediction -
Abstract
This paper highlights a number of recently published research studies during last five years in order to provide a summary related to latest trends of energy efficiency in the smart buildings technology. It reviews numerous technical methods applied to achieve a high level of Building Energy Efficiency (BEE). In this paper, methods applied to measure the BEE and to predict the energy-use have been considered and reviewed. Furthermore, some other methods discussed in articles which consider retrofitting of interior design of buildings have been taken. One of the most impacts that has been considered is the light control system because it directly affects the energy use. This paper has reviewed different types of techniques that save energy consumptions such as predictive techniques of energy use, Internet of Things (IoT) buildings, light control systems inside buildings, and Quick Response (QR) code based services used to notify occupants for energy-use. It has provided a simple comparison between different techniques used to retrofit the interior design of buildings due to its high importance in saving energy. The paper has also recommended suitability of methods taking into account the existing situation, design, limitations, and conditions of the building being studied.
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References
[1] W. Wei and L.-Y. He, "China Building Energy Consumption: Definitions and Measures from an Operational Perspective," Energies, vol. 10, 2017.
[2] W. G. Cai, Y. Wu, Y. Zhong, and H. Ren, "China building energy consumption: Situation, challenges and corresponding measures," Energy Policy, vol. 37, pp. 2054-2059, 2009.
[3] J. D. Park, H. K. Yu, S. Y. Yoon, H. K. Kim, and S. S. Kim, "Analysis of a Building Energy Efficiency Certification System in Korea," Sustainability, vol. 7, 2015.
[4] M. S. Gul and S. Patidar, "Understanding the energy consumption and occupancy of a multi-purpose academic building," Energy and Buildings, vol. 87, pp. 155-165, 2015.
[5] C. P. Au-Yong, A. S. Ali, and F. Ahmad, "Improving occupants' satisfaction with effective maintenance management of HVAC system in office buildings," Automation in Construction, vol. 43, pp. 31-37, 2014.
[6] L. Pérez-Lombard, J. Ortiz, and C. Pout, "A review on buildings energy consumption information," Energy and Buildings, vol. 40, pp. 394-398, 2008.
[7] W. Shaomin, N. Keith, W. Michael, and H. Matthew, "Research opportunities in maintenance of office building services systems," Journal of Quality in Maintenance Engineering, vol. 16, pp. 23-33, 2010.
[8] J. Byun and T. Shin, "Design and Implementation of an Energy-Saving Lighting Control System Considering User Satisfaction," IEEE Transactions on Consumer Electronics, vol. 64, pp. 61-68, 2018.
[9] R. Carli, M. Dotoli, R. Pellegrino, and L. Ranieri, "A Decision Making Technique to Optimize a Buildings; Stock Energy Efficiency," IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 47, pp. 794-807, 2017.
[10] A. Pellegrino, V. R. M. L. Verso, L. Blaso, A. Acquaviva, E. Patti, and A. Osello, "Lighting Control and Monitoring for Energy Efficiency: A Case Study Focused on the Interoperability of Building Management Systems," IEEE Transactions on Industry Applications, vol. 52, pp. 2627-2637, 2016.
[11] L. A. M. Riascos and S. E. Palmiere, "Energy Efficiency and Fire Prevention Integration in Green Buildings," IEEE Latin America Transactions, vol. 13, pp. 2608-2615, 2015.
[12] R. Gulbinas, A. Khosrowpour, and J. Taylor, "Segmentation and Classification of Commercial Building Occupants by Energy-Use Efficiency and Predictability," IEEE Transactions on Smart Grid, vol. 6, pp. 1414-1424, 2015.
[13] Z. Ma, P. Cooper, D. Daly, and L. Ledo, "Existing building retrofits: Methodology and state-of-the-art," Energy and Buildings, vol. 55, pp. 889-902, 2012.
[14] Y.-J. Wen and A. M. Agogino, "Personalized dynamic design of networked lighting for energy-efficiency in open-plan offices," Energy and Buildings, vol. 43, pp. 1919-1924, 2011.
[15] G. Y. Yun, H. Kim, and J. T. Kim, "Effects of occupancy and lighting use patterns on lighting energy consumption," Energy and Buildings, vol. 46, pp. 152-158, 2012.
[16] Z. Wang and Y. K. Tan, "Illumination control of LED systems based on neural network model and energy optimization algorithm," Energy and Buildings, vol. 62, pp. 514-521, 2013.
[17] Y. W. Bai and Y. T. Ku, "Automatic room light intensity detection and control using a microprocessor and light sensors," IEEE Transactions on Consumer Electronics, vol. 54, pp. 1173-1176, 2008.
[18] A. Pandharipande and D. Caicedo, "Daylight integrated illumination control of LED systems based on enhanced presence sensing," Energy and Buildings, vol. 43, pp. 944-950, 2011.
[19] C. Diakaki, E. Grigoroudis, and D. Kolokotsa, "Towards a multi-objective optimization approach for improving energy efficiency in buildings," Energy and Buildings, vol. 40, pp. 1747-1754, 2008.
[20] C. Diakaki, E. Grigoroudis, N. Kabelis, D. Kolokotsa, K. Kalaitzakis, and G. Stavrakakis, "A multi-objective decision model for the improvement of energy efficiency in buildings," Energy, vol. 35, pp. 5483-5496, 2010.
[21] E. Asadi, M. G. da Silva, C. H. Antunes, and L. Dias, "Multi-objective optimization for building retrofit strategies: A model and an application," Energy and Buildings, vol. 44, pp. 81-87, 2012.
[22] Y.-K. Juan, P. Gao, and J. Wang, "A hybrid decision support system for sustainable office building renovation and energy performance improvement," Energy and Buildings, vol. 42, pp. 290-297, 2010.
[23] E. M. Malatji, J. Zhang, and X. Xia, "A multiple objective optimisation model for building energy efficiency investment decision," Energy and Buildings, vol. 61, pp. 81-87, 2013.
[24] K. Alanne, "Selection of renovation actions using multi-criteria “knapsack†model," Automation in Construction, vol. 13, pp. 377-391, 2004.
[25] A. M. Rysanek and R. Choudhary, "Optimum building energy retrofits under technical and economic uncertainty," Energy and Buildings, vol. 57, pp. 324-337, 2013.
[26] Y. M. Lee, F. Liu, L. An, H. Jiang, C. Reddy, R. Horesh, et al., "Modeling and simulation of building energy performance for portfolios of public buildings," in Proceedings of the 2011 Winter Simulation Conference (WSC), 2011, pp. 915-927.
[27] Y.-H. Perng, Y.-K. Juan, and H.-S. Hsu, "Genetic algorithm-based decision support for the restoration budget allocation of historical buildings," Building and Environment, vol. 42, pp. 770-778, 2007.
[28] I. Khajenasiri, A. Estebsari, M. Verhelst, and G. Gielen, "A Review on Internet of Things Solutions for Intelligent Energy Control in Buildings for Smart City Applications," Energy Procedia, vol. 111, pp. 770-779, 2017.
[29] A. Fensel, D. K. Tomic, and A. Koller, "Contributing to appliances’ energy efficiency with Internet of Things, smart data and user engagement," Future Generation Computer Systems, vol. 76, pp. 329-338, 2017.
[30] G. Zimmerman. (2018). Small Buildings, Big Savings? Available: https://www.facilitiesnet.com/green/article.aspx?id=8061#
[31] G. Zimmerman. (2018). Internet of Things Can Help Save Energy When It's Most Expensive. Available: https://www.facilitiesnet.com/energyefficiency/article/Internet-of-Things-Can-Help-Save-Energy-When-Its-Most-Expensive--17801?utm_source=trending
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How to Cite
Al-Ghaili, A. M., Kasim, H., Othman, M., & Hassan, Z. (2018). A Review on Building Energy Efficiency Techniques. International Journal of Engineering & Technology, 7(4.35), 35-40. https://doi.org/10.14419/ijet.v7i4.35.22318Received date: 2018-11-29
Accepted date: 2018-11-29
Published date: 2018-11-30