Affiliation:
1. Department of Electrical Engineering, Islamic Azad University, Faculty of Engineering, Marvdasht University, Fars, Iran
2. Department Department of Electrical Engineering Islamic Azad University, Faculty of Engineering, Tehran University, Tehran, Iran
Abstract
According to the studies conducted by the Energy Consumption Management and Optimization Organization, in the common constructions of the country, energy loss in buildings is often 22% through windows, 22% from floors, and 30% from walls. Applying the principles of energy consumption optimization in coordination with climatic conditions and design uses, as well as the use of active and passive methods, can play an effective role in reducing energy consumption in conventional urban buildings. This research aims to provide solutions that address how to reduce energy consumption while creating quality in the architectural space. These solutions are obtained by recognizing the indicators of sustainable and comparative study with the climate of the desired design context. In the present study, the role of technology and digital tools in the field, which is the first and most important step in locating roles and functions, as well as small-scale designs such as building facades. Then, the architectural recommendations of the climate and international standards were examined, and a total of solutions were presented to reach the zero energy building (ZEB). Finally, the simulation method in Design Builder software analyzed the amount of energy consumption in the residential complex and using the analysis of the researchers' efforts and finding the best answer to the problems of architecture and urban planning; results show a significant reduction in energy consumption to be able to manage available resources in the best way.
Publisher
Research and Education Promotion Association (REPA)
Reference18 articles.
1. Wright JA, Loosemore HA, Farmani R (2002) “Optimization of building thermal design and control by multi-criterion genetic algorithm” Energy Build (vol. 34, no. 9, pp. 959–972) https://doi.org/10.1016/S0378-7788(02)00071-3
2. Figueiredo J, Sá da Costa J (2012) “A SCADA system for energy management in intelligent buildings” Energy Build (vol. 49, pp. 85–98) https://doi.org/10.1016/j.enbuild.2012.01.041
3. Parisio A, Glielmo L (2011) “Energy efficient microgrid management using model predictive control” 2011 50th IEEE Conference on Decision and Control and European Control Conference Florida, USA, IEEE - pp. 5449–5454. https://doi.org/10.1109/CDC.2011.6161246
4. William G (2012) “California renewable energy forecasting, resource data, and mapping: Final project report” California, USA, University of California. 101 p. (https://lccn.loc.gov/2014496186)
5. Nogales FJ, Contreras J, Conejo AJ, Espinola R (2002) “Forecasting next-day electricity prices by time series models” IEEE Trans Power Syst (vol. 17, no. 2, pp. 342–348) https://doi.org/10.1109/TPWRS.2002.1007902