154
Views
1
CrossRef citations to date
0
Altmetric
Research Article

A novel method on the optimization problem of energy conservation in public buildings

, ORCID Icon, &
Pages 3279-3296 | Received 20 Jul 2022, Accepted 27 Jan 2023, Published online: 29 Mar 2023

References

  • Abiodun, O. I., A. Jantan, A. E. Omolara, K. V. Dada, N. A. Mohamed, and H. Arshad. 2018. State-of-the-art in artificial neural network applications: A survey. Heliyon 4 (11):e00938. doi:10.1016/j.heliyon.2018.e00938.
  • Ah, A., B. Ses, and A. Mrg. 2020. Effects of different window configurations on energy consumption in building optimization and economic analysis. Journal of Building Engineering 35:102099.
  • Alghamdi, S., W. C. Tang, and S. Kanjanabootra. 2022. Effect of architectural building design parameters on thermal comfort and energy consumption in higher education buildings. Buildings 12 (3):329. doi:10.3390/buildings12030329.
  • Alvo, M., and L. H. Philip. 2014. Statistical methods for ranking data. New York: Springer.
  • Anuntasethakul, C., and D. Banjerdpongchai. 2021. Design of supervisory model predictive control for building HVAC system with consideration of peak-load shaving and thermal comfort. IEEE Access 99:41066–81. doi:10.1109/ACCESS.2021.3065083.
  • Asvadi-Kermani, O., H. Momeni, A. Justo, J. M. Guerrero, J. C. Vasquez, J. Rodriguez, and B. Khan. 2022. Energy optimization of air handling units using constrained predictive controllers based on dynamic neural networks. IEEE Access 10:56578–90. doi:10.1109/ACCESS.2022.3177660.
  • Barber, K. A., and M. Krarti. 2022. A review of optimization based tools for design and control of building energy systems. Renewable and Sustainable Energy Reviews 160:112359. doi:10.1016/j.rser.2022.112359.
  • Barbhuiya, S., and S. Barbhuiya. 2013. Thermal comfort and energy consumption in a UK educational building. Building & Environment 68:1–11. doi:10.1016/j.buildenv.2013.06.002.
  • Cai, D. 2021. Optimal control of energy saving based on indoor thermal comfort. Shandong: Shandong Normal University.
  • Cheng, W. L., Y. S. Chen, J. Zhang, T. J. Lyons, J. -L. Pai, and S. -H. Chang. 2007. Comparison of the revised air quality index with the PSI and AQI indices. The Science of the Total Environment 382 (2):191–98. doi:10.1016/j.scitotenv.2007.04.036.
  • China building energy consumption research report. 2021. CABEE.
  • Ding, S., W. Qinghui 2013. A matlab-based study on performances of improved algorithms of typical BP neural networks. Journal of Applied Mechanics and Materials, 1353–56.
  • Geng, Y., W. Ji, Z. Wang, B. Lin, and Y. Zhu. 2019. A review of operating performance in green buildings: Energy use, indoor environmental quality and occupant satisfaction. Energy and Buildings 183:500–14. doi:10.1016/j.enbuild.2018.11.017.
  • Ghalambaz, M., R. J. Yengejeh, and A. H. Davami. 2021. Building energy optimization using grey wolf optimizer (GWO). Case Studies in Thermal Engineering 27 (4):101250. doi:10.1016/j.csite.2021.101250.
  • Hachem-Vermette, C., and K. Singh. 2022. Optimization of energy resources in various building cluster archetypes. Renewable and Sustainable Energy Reviews 157:112050. doi:10.1016/j.rser.2021.112050.
  • Hamdy, M., A. Hasan, and K. Siren. 2013. A multi-stage optimization method for cost-optimal and nearly-zero-energy building solutions in line with the EPBD-recast 2010. Energy & Buildings 56:189–203. doi:10.1016/j.enbuild.2012.08.023.
  • Huang, Y., Y. Xiang, R. Zhao and Z. Cheng. Air Quality Prediction Using Improved PSO-BP Neural Network. IEEE Access, Vol.8, 99346–53, 2020.
  • Iijima, F., S. Ikeda, and T. Nagai. 2022. Automated computational design method for energy systems in buildings using capacity and operation optimization. Applied Energy 306. doi:10.1016/j.apenergy.2021.117973.
  • Jiang, F. 2018. Application of Pearson correlation coefficient to evaluate heat transfer characteristics of mixed working medium and nanofluids. Tianjin: Tianjin University.
  • Jiangdai, L., D. Yuntao, and H. Siping. 2021. Speech intelligent recognition system of picking robot based on LM-BP neural network. Journal of Agricultural Mechanization Research 43 (09):215–18.
  • Jiang, W., Z. Ju, H. Tian, Y. Liu, M. Arıcı, X. Tang, Q. Li, D. Li, and H. Qi. 2022. Net-zero energy retrofit of rural house in severe cold region based on passive insulation and BAPV technology. Journal of Cleaner Production 132198:132198. doi:10.1016/j.jclepro.2022.132198.
  • Kishore, R. A., M. Bianchi, C. Booten, J. Vidal, and R. Jackson. 2020. Optimizing PCM-Integrated walls for potential energy savings in U.S buildings. Energy and Buildings 226:110355. doi:10.1016/j.enbuild.2020.110355.
  • Kumar, R., S. Kumar and E. Amiy. 2022. Air Quality Indices Prediction using Sugeno’s Fuzzy Logic. 2022 International Conference on IoT and Blockchain Technology (ICIBT), Ranchi, India, 1–5.
  • Liang, Y., S. -C. Chu, J. -S. Pan, and Y. Liang. 2020. A novel pigeon-inspired optimization based MPPT technique for PV systems. Processes 8. doi:10.3390/pr8030356.
  • Mahdavi Adeli, M., S. Farahat, and F. Sarhaddi. 2020. Increasing thermal comfort of a net-zero energy building inhabitant by optimization of energy consumption. International Journal of Environmental Science and Technology 17 (5):2819–34. doi:10.1007/s13762-019-02603-0.
  • Ofy, A., B. My, and C. Ac. 2022. Reduction of energy consumption and CO2 emissions of HVAC system in airport terminal buildings. Building and Environment 208 (15):108632. doi:10.1016/j.buildenv.2021.108632.
  • Rajamoorthy, R., G. Arunachalam, P. Kasinathan, R. Devendiran, P. Ahmadi, S. Pandiyan, S. Muthusamy, H. Panchal, H. A. Kazem, and P. Sharma. 2022. A novel intelligent transport system charging scheduling for electric vehicles using grey wolf optimizer and sail fish optimization algorithms. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 44 (2):3555–75. doi:10.1080/15567036.2022.2067268.
  • Sharma, P., A. Chhillar, Z. Said, Z. Huang, V. N. Nguyen, P. Q. P. Nguyen, and X. P. Nguyen. 2022. Experimental investigations on efficiency and instability of combustion process in a diesel engine fueled with ternary blends of hydrogen peroxide additive/biodiesel/diesel. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. 44 (3):5929–50. doi:10.1080/15567036.2022.2091692.
  • Sharma, P., Z. Said, and A. Kumar. 2022. Recent advances in machine learning research for nanofluid-based heat transfer in renewable energy system. Energy & Fuels. 36(13):6626–58. doi:10.1021/acs.energyfuels.2c01006.
  • Sh, A., B. Yd, and A. Eka. 2020. PSACONN mining algorithm for multi-factor thermal energy-efficient public building design. Journal of Building Engineering 34:102020.
  • Sun, C., Q. Liu, and Y. Han. 2020. Many objective optimization design of a public building for energy, daylighting and cost performance improvement. Applied Sciences 10 (7):2435. doi:10.3390/app10072435.
  • Yan, Q. 2021. Predicting SOC of power battery based on GA-BP algorithm. 2021 3rd International Conference on Applied Machine Learning (ICAML), Changsha, China, 431–34.
  • Yuksel, A., M. Arici, and M. Krajcik. 2020. A review on thermal comfort, indoor air quality and energy consumption in temples. Journal of Building Engineering 35:102013.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.