Keywords
Dymola software
Energy modelling
Modelica language
Energy conservation
How to Cite
Abstract
In developed nations, there's a growing concern for sustainable energy management, particularly regarding enhancing energy efficiency in both existing and new buildings. The methodology presented considers the energy modelling and simulation of manufacturing buildings through thermal and electrical loads calculations using Dymola/Modelica software. The thermal model is built with the primary components of Dymola along with available models to calculate the heating and cooling loads, whereas the electrical model was calculated using consumption patterns, then the total model was validated against real measurements where the error percentage was 9.96 %. The yearly heating load baseline was 6295 kWh/y and for cooling 46276 kWh/y., the exciting potential for energy- savings and load flexibility, and some suggestions for improving consumption were pointed out and identified. It found that the highest influence on the thermal load reduction was using the double glaze with shading with 61% of the energy-saving options, then replacing the fluorescent with LED with 30%, and finally, the roof insulation was the least influence with 9.5%. For the total consumption, the highest percentage was for replacing the fluorescent with LED with 78% of energy-saving options, then double glaze with shading, and finally the lowest is for the roof insulation.
References
Al-omary M, Kaltschmitt M, Becker C. Electricity system in Jordan: Status & prospects. Renew Sustain Energy Rev. 2018: 2398-409. https://doi.org/10.1016/j.rser.2017.06.046
Tawalbeh M. Energy Efficiency; Current Trends and Future Perspectives in Jordan. Royal Scientific Society; International workshop, Athens: 22-23/2/2016. Available from: http://www.cres.gr/kape/publications/pdf/mare_2016/12_Tawalbeh.pdf
Hassouneh K, Al-Salaymeh A, Qoussous J. Energy audit, an approach to apply the concept of green building for a building in Jordan. Sustain Cities Soc. 2015; 14: 456-62. https://doi.org/10.1016/J.SCS.2014.08.010
Hasanbeigi A, Price L. Industrial energy audit guidebook: guidelines for conducting an energy audit in industrial facilities. Lawrence Berkeley National Laboratory; 2010, LBNL Report #: LBNL-3991E. Available from: https://escholarship.org/uc/item/4rw140wk
Coakley D, Raftery P, Keane M. A review of methods to match building energy simulation models to measured data. Renew Sustain Energy Rev. 2014; 37: 123-41. https://doi.org/10.1016/j.rser.2014.05.007
Bhatt MS. Energy audit case studies I—steam systems. Appl Therm Eng. 2000; 20(3): 285-96.
Albert T, Terry N, William WJ. Handbook of energy audits. 9th ed. Distributed by Taylor & Francis Ltd., FL 33487, USA: 2012.
Saltelli A, Ratto M, Andres T, Campolongo F, Cariboni J, Gatelli D, et al. Global sensitivity analysis: the primer. John Wiley & Sons Ltd.; England: 2007.
Crawley DB, Hand JW, Kummert M, Griffith BT. Contrasting the capabilities of building energy performance simulation programs. Build Environ. 2008; 43(4): 661-73. https://doi.org/10.1016/j.buildenv.2006.10.027
Lucentini M, Rottenberg F, Di Palma D. A model for the evaluation of energy indicators in end users audit for hospital sector. ASME 2011 International Mechanical Engineering Congress and Exposition, Denver, Colorado, USA: November 11-17, 2011, Paper No: IMECE2011-63434, pp. 305-11. https://doi.org/10.1115/IMECE2011-63434
Keirstead J, Jennings M, Sivakumar A. A review of urban energy system models: Approaches, challenges and opportunities. Renew Sustain Energy Rev. 2012; 16(6): 3847-66. https://doi.org/10.1016/j.rser.2012.02.047
Obara H, Azar M, Curci F. Method and tools for assessment of energy performance of buildings- case study. Sustainable Building Conference 2016, Turin: February 2016.
Wang S, Yan C, Xiao F. Quantitative energy performance assessment methods for existing buildings. Energy Build. 2012; 55: 873-88. https://doi.org/10.1016/j.enbuild.2012.08.037
Dongellini M, Marinosci C, Morini GL. Energy Audit of an Industrial Site: A Case Study. Energy Procedia. 2014; 45: 424-33. https://doi.org/10.1016/j.egypro.2014.01.046
Traoré I, Valentin G, Riffonneau Y, l’henoret B, drouet E. Development of a generic and scalable modelica based model of a typical french railway station. Application to forecast, scheduling and energy consumption management. Proceedings of Building Simulation 2013: 13th Conference of IBPSA, Chambery, France: August 26-28, 2013, pp. 2139. https://doi.org/10.26868/25222708.2013.1229
Wetter M. A view on future building system modeling and simulation. In Hensen JLM, Lamberts R, Eds., Building performance simulation for design and operation. UK: Routledge; 2011, pp. 631-56.
Ruiz G, Bandera C. Validation of calibrated energy models: common errors. Energies 2017: 10(10): 1587. https://doi.org/10.3390/en10101587
Akash BA, Mohsen MS. Current situation of energy consumption in the Jordanian industry. Energy Convers Manag. 2003; 44(9): 1501-10. https://doi.org/10.1016/S0196-8904(02)00146-2
Kablan M. Energy conservation projects implementation at Jordan’s industrial sector: a total quality management approach. Energy. 2003; 28(15): 1533-43. 10.1016/S0360-5442(03)00129-4
Al-Ghandoor A, Al-Hinti I. Prospects of energy savings in the Jordanian plastic industry. Jordan J Mech Ind Eng. 2007; 1(2): 93-98.
Al-Widyan M, Soliman I, Alajlouni A, Al Zu'bi O, Jaradat A. Energy performance assessment of a non-domestic service building in Jordan. Jordan J Mech Ind Eng. 2018; 12(2): 69-75.
Sharma P, Salkuti SR, Kim SC. Energy audit: types, scope, methodology and report structure. Indones J Electr Eng Comput Sci. 2021; 22(1): 45-52. http://doi.org/10.11591/ijeecs.v22.i1.pp45-52
Alrwashdeh SS. Energy sources assessment in Jordan. Results Eng. 2022; 13: 100329. https://doi.org/10.1016/j.rineng.2021.100329
Kuntuarova S, Licklederer T, Huynh T, Zinsmeister D, Hamacher T, Perić V. Design and simulation of district heating networks: a review of modeling approaches and tools. Energy. 2024; 305: 132189. https://doi.org/10.1016/j.energy.2024.132189
Cucca G, Ianakiev A. Assessment and optimisation of energy consumption in building communities using an innovative co-simulation tool. J Build Eng. 2020; 32: 101681. https://doi.org/10.1016/j.jobe.2020.101681
Alasmar R, Schwartz Y, Burman E. Developing a housing stock model for evaluating energy Performance: The case of Jordan. Energy Build. 2024; 308: 114010. https://doi.org/10.1016/j.enbuild.2024.114010
Sandri S, Hussein H, Alshyab N. Sustainability of the energy sector in Jordan: Challenges and opportunities. sustainability. 2020; 12(24): 10465. https://doi.org/10.3390/su122410465
Nagy Z, Henze G, Dey S, Arroyo J, Helsen L, Zhang X, et al. Ten questions concerning reinforcement learning for building energy management. Build Environ. 2023; 241: 110435. https://doi.org/10.1016/j.buildenv.2023.110435
Khan AA, Minai AF. A strategic review: the role of commercially available tools for planning, modelling, optimization, and performance measurement of photovoltaic systems. Energy Harvest Syst. 2024; 11(1): 20220157. https://doi.org/10.1515/ehs-2022-0157
Muhič S, Dimitrije Manić, Ante Čikić, Komatina M. Influence of building thermal envelope modeling parameters on results of building energy simulation. J Build Eng. 2024; 87: 109011. https://doi.org/10.1016/j.jobe.2024.109011
Joshi A, Khandelwal N, Suryavanshi Y, Broota S, Kurulekar M, Dhaneshwar P. Energy conservation: Virtual energy audit of an industrial plant. Mater Today. 2023; 72: 1882-9. https://doi.org/10.1016/j.matpr.2022.10.055
Zipplies J, Orozaliev J, Jordan U, Vajen K. Heat consumer model for robust and fast simulations of district heating networks using modelica. Electronics. 2024; 13(7): 1201. https://doi.org/10.3390/electronics13071201
Al Momani D, Al Turk Y, Abuashour MI, Khalid HM, Muyeen SM, Sweidan TO, et al. Energy saving potential analysis applying factory scale energy audit – A case study of food production. Heliyon. 2023; 9(3): e14216. https://doi.org/10.1016/j.heliyon.2023.e14216
Qiu K, Yang J, Gao Z, Xu F. A review of Modelica language in building and energy: Development, applications, and future prospect. Energy Build. 2024; 113998. https://doi.org/10.1016/j.enbuild.2024.113998
Hinkelman K, Wang J, Zuo W, Gautier A, Wetter M, Fan C, et al. Modelica-based modeling and simulation of district cooling systems: A case study. Appl Energy. 2022; 311: 118654. https://doi.org/10.1016/j.apenergy.2022.118654
Akpahou R, Mensah LD, Quansah DA, Kemausuor F. Energy planning and modeling tools for sustainable development: A systematic literature review. Energy Rep. 2024; 11: 830-45. https://doi.org/10.1016/j.egyr.2023.11.043
Martin O. Modelica Association (Hrsg.): Modelica Overview. Available from: https: //www.modelica.org/. Version: 2009
Mathias MR. Object oriented modeling thermal building behavior. (Dissertation) University of Kaiserslautern; 2002.
Clemens H. Dynamic simulation of the heating and cooling loads of Jordanian households with Dymola. (Master Thesis) Hambur: Technische Universität Hamburg; 2017.
Alsaad MA, Hammad MA. Heating and air conditioning for residential buildings. 5th ed. Library Catalog (Koha). Amman: Alsaad; 2011.
Al-Sheraideh MY. Low energy and energy rating for apartment buildings in Jordan. (Master Thesis) Amman: University of Jordan; 2015.
ASHRAE Fundamentals (2013), ASHRAE, 1791 Tullie Circle, N.E., Atlanta, GA 30329. Available from: www.Ashrae.org
Renewables.ninja. Available from: https://www.renewables.ninja
Schmitz G. Thermal Engineering: Script for the lecture use. TUHH, Hamburg, Germany, 2012.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright (c) 2024 Abeer Al-Jbour, Heba Abutayeh, Bashar R. Qawasmeh