A linear mathematical programming model for optimization of the energy consumption in construction projects

Document Type : Original Article

Authors

1 Faculty of Engineering, University of Garmsar, Garmsar, Iran

2 Department of Industrial Engineering, Razi University, Kermanshah, Iran.

Abstract

In this study, a linear mathematical programming model is formulated to manage the consumption of electrical energy and fossil fuels in the construction projects simultaneously. The aim is to determine at what time period and for how long each electric machine is employed in the whole project, the optimal number of periodic services for the machines with fossil fuels and optimal service time so that the total objective function value is minimized. The objective function of the proposed problem is the sum of electricity consumption costs, service costs and fossil fuel consumption costs in the whole project. In the proposed model, different intervals are considered for electrical energy consumption and the effects of the average speed of each machine with fossil fuel consumption and the time required to these machines in each day are also applied in decisions-making. For solving the mathematical model, the LINGO optimization software package is employed. For a better understanding of the behavior of the proposed problem, sample problems with different sizes are investigated and the results are interpreted graphically. The results show that the objective function value of the proposed problem increases with an increment in the project completion time and number of machines, the consumption cost of the fossil fuels machines accounts for a significant portion of the objective function value in all samples and also, the contribution of service costs is more than that of the electric machines. Also, the proposed model is implemented for a sample problem and its sensitivity to some parameters are tested. The results of sensitivity analysis show that by increasing the project completion time, the number of intervals selected for the daily use of electric machines, number of service times required for the fossil fuel machinery and consequently the amount of objective function are increased. Also, the model solving time increases logarithmically with an increment in the project completion time.

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1. S. Afshari-Azad, P. Shirvani, and M. Karimi-Sabah, “Investigating the situation of renewable energy utilization in Iran,” 2nd International Congress on Structure, Architecture and Urban Development, Tabriz, https://civilica.com/doc/353657, 2014 (In Persian).
2. S. Haghnegahdar, and M. Taban, “A review of energy efficiency in the London City Council building,” 6th Conference on National Building Regulations, Shiraz, https://civilica.com/doc/555020, 2014 (In Persian).
3. S. Khodaverdizadeh, M. Khodaverdizadeh, and M. Imanzadeh, “Investigating the Impact of Globalization on the Energy Consumption of Selected Developing Countries: A Panel Approach,” 11th National Congress of Pioneers of Progress, Tehran, https://civilica.com/doc/742159, 2017 (In Persian).
4. X. Fan, H. Sun, Z. Yuan, Z. Li, R. Shi, and N. Ghadimi, “High voltage gain DC/DC converter using coupled inductor and VM techniques,” IEEE Access, vol. 8, pp. 131975-131987, 2020.
5. K. A. I. Menoufi, “Life cycle analysis and life cyle impact assessment methodologies: a state of the art,” 2011.
6. J. De Lassio, J. França, K. Espirito Santo, and A. Haddad, “Case study LCA methodology applied to materials management in a Brazilian residential construction site,” Journal of Engineering, 2016.
7. L. F. Amaral, G. C. G. Delaqua, M. Nicolite, M. T. Marvila, A. R. de Azevedo, J. Alexandre, C.M.F. Vieira, and S. N. Monteiro, “Eco-friendly mortars with addition of ornamental stone waste-A mathematical model approach for granulometric optimization,” Journal of Cleaner Production, vol. 248, no. 1, pp. 119283, 2020.
8. C. Y. Zhang, R. Han, B. Yu, and Y. M. Wei, “Accounting processrelated CO2 emissions from global cement production under Shared Socioeconomic Pathways,” Journal of Cleaner Production, vol. 184, pp. 451-465, 2018.
9. A. R. G. De Azevedo, J. Alexandre, M. T. Marvila, G. de Castro Xavier, S. N. Monteiro, and L. G. Pedroti, “Technological and environmental comparative of the processing of primary sludge waste from paperindustry for mortar,” Journal of Cleaner Production, vol. 249, pp. 119336, 2020.
10. S. Shrivastava, and A. Chini, “Estimating energy consumption during construction of buildings: a contractor’s perspective,” In Proceedings of the world sustainable building conference, pp. 18-21, 2011, October
11. M. Y. Han, G. Q. Chen, L. Shao, J. S. Li, A. Alsaedi, B. Ahmad, S. Guo, M. M. Jiang, and X. Ji, “Embodied energy consumption of building construction engineering: case study in E-town, Beijing,” Energy and Buildings, vol. 64, pp. 62-72, 2013.
12. F. H. Abanda, J. H. M. Tah, and F. K. T. Cheung, “Mathematical modelling of embodied energy, greenhouse gases, waste, time–cost parameters of building projects: A review,” Building and environment, vol. 59, pp. 23-37, 2013.
13. R. M. J. Janssen, “Assessing onsite energy usage: an explorative study,” Master’s thesis, University of Twente, 2014
14. S. Abbasi, and E. Noorzai, “The BIM-Based multi-optimization approach in order to determine the trade-off between embodied and operation energy focused on renewable energy use,” Journal of Cleaner Production, vol. 281, pp. 125359, 2021.
15. M. Dong, F. He, and H. Wei, “Energy supply network design optimization for distributed energy systems,” Computers & Industrial Engineering, vol. 63, no. 3, pp. 546-552, 2012
16. M. Zugno, J. M. Morales, P. Pinson, and H. Madsen, “A bilevel model for electricity retailers’ participation in a demand response market environment,” Energy Economics, vol. 36, pp. 182-197, 2013.
17. J. C. Steckel, R. J. Brecha, M. Jakob, J. Strefler, and G. Luderer, “Development without energy? Assessing future scenarios of energy consumption in developing countries,” Ecological Economics, vol. 90, pp. 53-67, 2013
18. A. Alwisy, B. Barkokebas, S. B. Hamdan, M. Gül, and M. Al-Hussein, “Energy-based target cost modelling for construction projects,” Journal of Building Engineering, vol. 20, pp. 387-399, 2018.
19. I. A. Sultanguzin, H. Toepfer, I. D. Kalyakin, A. V. Govorin, E. V. Zhigulina, S. Y. Kurzanov, and Y. V. Yavorovsky, “Mathematical modeling and control system of nearly zero energy building,” Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Srodowiska, vol. 8, no. 2, pp. 21-24, 2018.
20. A. S. Shah, H. Nasir, M. Fayaz, A. Lajis, and A. Shah, “A review on energy consumption optimization techniques in IoT based smart building environments,” Information, vol. 10, no. 3, pp.108, 2019.
21. J. Hong, T. Hong, H. Kang, and M. Lee, “A Framework for Reducing Dust Emissions and Energy Consumption on Construction Sites. Energy Procedia, vol. 158, pp. 5092-5096, 2019.
22. A. Pallikere, R. Qiu, P. Delgoshaei, and A. Negahban, “Incorporating occupancy data in scheduling building equipment: A simulation optimization framework,” Energy and Buildings, vol. 209, pp. 109655, 2020.
23. M. Jiang, H. An, X. Gao, D. Liu, N. Jia, and X. Xi, “Consumption-based multi-objective optimization model for minimizing energy consumption: A case study of China,” Energy, vol. 208, pp. 118384, 2020
24. F. A. Fard, and F. Nasiri, “A bi-objective optimization approach for selection of passive energy alternatives in retrofit projects under cost uncertainty,” Energy and Built Environment, vol. 1, no. 1, pp. 77-86, 2020.
25. J. Feng, X. Luo, M. Gao, A. Abbas, Y. P. Xu, and S. Pouramini, “Minimization of energy consumption by building shape optimization using an improved Manta-Ray Foraging Optimization algorithm,” Energy Reports, vol. 7, pp. 1068-1078, 2021