Windows have the most contribution to ENERGY loss through the BUILDINGS envelope. One of the offered solutions to improve the ENERGY efficiency of the windows and glazing units is the filling of the vacant space of the multilayer glazing systems with aerogel. Aerogels are the lightest commercialized solids and have the lowest thermal conductivity among solid materials. Furthermore, their good acoustic insulation as well as daylight and solar ENERGY transmittance properties, make them interesting insulation materials that can be used in the vacant space of multilayer glazing units. Multilaye r polycarbonate planes recently have found extensive applications in BUILDINGS. In this work, the vacant space, air gaps, of the polycarbonate planes were filled with silica aerogel and their thermal performance as an innovative glazing system was investigated. Polycarbonate planes with different thicknesses (5-15 mm) were filled with granular aerogels and the amount of reduction in the heat loss through the planes at different temperatures (40-70oC) was measured. Also, the effect of aerogel granule size on the thermal efficiency of the planes was investigated. Granule size in the range of 2-3 mm showed the best performance. Depending on the plane thickness, applied temperature, and aerogel granule size, the ENERGY loss through aerogel-filled planed is reduced 21 to 66 % in comparison with conventional air-filled planes. Typically, the U-value of the 10 mm polycarbonate plane was reduced from 2. 74 W/m2K in the air-filled plane to 1. 1 W/m2K in the aerogel-filled plane.

Improper design and construction, non-standard materials and equipment, materials used in BUILDINGS and improper choice of building coatings such as walls, windows and insulation system are the most important factors of high ENERGY consumption in BUILDINGS. Improving the above measures reduces the share of internal ENERGY losses from each of the building shell components. The increasing advancement of technology and the need of the industry to use it has made building information modeling as one of the new technologies in the construction industry is growing and has attracted the attention of researchers for its use and how to develop it. The aim of this study was to investigate the ENERGY efficiency patterns of the exterior wall of a high-rise residential building using building information modeling. For this purpose, in this study, the use of different materials in the construction of external walls of the building based on a case study and using the facilities of a building information modeling, has been investigated in terms of ENERGY consumption. The materials studied in this research are clay block, pumice cement block, foamed cement block, Iranwall block, fan block, and wallcrete. Cement block with pumice and foamed cement block with about 10% savings in fuel consumption and 8.3% savings in electrical ENERGY, was selected as the best wall.

In recent years, the issue of ENERGY consumption modeling techniques in the building sector has been widely considered by researchers and managers. Researches indicate that ENERGY consumption in residential sector is one of the main parts of the total consumption. Moreover, the urban residence is supposed as a significant consumer of ENERGY in every country and therefore a focus for ENERGY consumption efforts. For over increasing building ENERGY consumption there can be some causes including: climate change, increase in household electricity load, fast-growing household electrical appliances, huge ENERGY consumption of the BUILDINGS, and the lack of strict government supervision. Recently the issue of assigning different prices to different time-periods of ENERGY consumption has been taken into consideration for ENERGY prices of consumers’ bills. Therefore, in this paper a model for multi-prices and multi-periods single-type ENERGY consumption in urban residential sector is presented; also an EFFICIENT heuristic method is provided for solving the mentioned model.

First step in designing smart homes is ENERGY efficiency analysis including ENERGY optimization and consumption analysis, This paper incorporates the uncertainty of the effective parameters and probabilistically optimizes the ENERGY consumption in a building, To this end, probability density functions (PDFs) of building uncertain parameters are modeled by point estimate method and the ENERGY usage in BUILDINGS is optimized, ENERGYPlus and MATLAB software are respectively used to compute the ENERGY consumption in a building and to optimize the ENERGY consumption, ENERGY consumption of the building and the thermal comfort are considered as objective functions of the proposed multi-objective optimization problem, The 12-story commercial building is used as a case study, To assess the proposed method, the proposed probabilistic method is compared with the deterministic method, The results show a significant difference between the deterministic and probabilistic cases, The maximum difference between the mean optimal values of variable parameters in these cases is about 28%, Finally, sensitivity of the results to the climate changes is also investigated in this paper,

Due to the limited ENERGY resources and the need to save ENERGY, use of solar ENERGY as a strategic approach is extremely important. So in this article by using system to store solar ENERGY for heating BUILDINGS in Laboratory of Islamic Azad university-Semnan Branch. In this approach tried to optimized using of solar ENERGY. In this system, the ENERGY requirements of the building using software «Carrier» during the day and then the solar ENERGY are calculated using mathematical equations. A code written in «MATLAB» for optimum Solar ENERGY consumption where calculates storage system level thermal load and thermal load of the auxiliary system (boiler) on the day. Utilizing the code, all needed magnitude of geometry as the collector area requirements according to the heat load are provided.

Managing ENERGY consumption in smart BUILDINGS has become an increasingly important challenge. EFFICIENT ENERGY management can have a positive impact on both micro and macroeconomics. Moreover, it is essential to ensure that the comfort of smart building residents is maintained at an acceptable level. Optimization algorithms can be used to achieve user convenience while minimizing ENERGY consumption. In this study, we propose an optimization approach that utilizes an agent-based architecture. This architecture comprises intelligent agents that communicate with each other via message exchange in a network structure consisting of three layers: (1) The switch layer monitors user preferences and comfort levels. (2) The coordination layer includes a coordinating agent that determines the optimal timing for electrical appliances to minimize electricity consumption costs and maximize user comfort. (3) The execution layer contains performer agents. Our focus in this research is on the coordination layer with the aim of reducing ENERGY consumption costs and peak average rates, while increasing user comfort to the highest possible level. However, this optimization problem is highly complex due to the large number of electrical devices and their capabilities. To address this, we propose a hybrid method based on genetic and bat algorithms. We evaluated its performance based on objective functions and compared it with recent research on SmartHome and CU-Bems datasets. Our results demonstrate an improvement in performance