Energy Efficiency of Residential Complexes Using BIM-Integrated Analysis of Building Design, Climatic Conditions and Facilities Optimization

Abstract
This study investigated the cost benefits of BIM-integrated energy optimization for a residential complex. The purpose of this research is to optimally design residential buildings for energy efficiency by observing climatic conditions and the proportion between energy-consuming facilities using a building information modeling (BIM) system in a temperate and humid environment. Revit software was used for modeling and simulation and Green Building Studio for scenario comparisons. Both are Web-based and resource-efficient. The project aimed to assess energy cost variations due to BIM optimization, considering the building’s size and seaside location. BIM was also used to examine building form and orientation. The building is a four-block residential complex exceeding 18,000 sq m with a central corridor. Located near the Caspian Sea, it experiences hot summers and mild winters with high humidity and frequent fog. The research steps include initial building modeling using parameters common in the Iranian construction industry; initial energy analysis to determine building energy consumption costs; selection of a plan sample for optimization in design, layout and building materials/components; integration of a photovoltaic system, considering operating costs; and energy analysis of the optimized building, comparing energy consumption in normal and optimized modes. Solar panels with a 20.4% efficiency rating were used, covering 90% of the available roof area, with a 30-year operational lifespan. The analysis revealed that using BIM technology to optimize energy consumption parameters could reduce energy costs by up to 58% compared to the existing building and by up to 69% compared to a baseline scenario. Adjusting for the current building conditions, the annual energy consumption cost was reduced to $13 per square meter, with a corresponding energy intensity of 112 kWh/m². Following the optimization of structural and utility design, internal layout and energy-related parameters, the annual energy consumption cost was further reduced to $5.43 per square meter, and the energy intensity decreased to 83.1 kWh/m². The framework of research would enable designers to explore a wider range of design options, considering not only the static geometry of the building but also its dynamic interaction with the surrounding environment. By incorporating real-time weather data, the framework could predict the building’s energy performance across different seasons and weather conditions, allowing for more informed design decisions and a significant reduction in energy consumption. Furthermore, the methodology moves beyond generic climate zone categorization, performing a granular, localized performance analysis where the high humidity and fog directly influence key design outputs, such as thermal bridge mitigation strategies and the precise sizing and balancing of dehumidification-aware heating, ventilation and air conditioning systems, thereby ensuring the resulting energy efficiency framework is not only technically sound but also intrinsically tied to the demanding conditions of the building’s specific seaside locale.

BIM-Based Approach to Optimizing Energy Consumption in Tower Buildings: Investigation of Parameters and Factors Affecting Energy Efficiency

Abstract
This research aims to develop a multi-criteria framework for optimizing energy consumption in tower buildings by evaluating parameters and factors affecting energy efficiency over 30 years. Building information modeling (BIM) is employed to model and analyze the results. This study employed a building information modeling (BIM) approach using Autodesk Revit software to model a residential complex in northern Iran. The study considered various building parameters, including form, orientation, materials, HVAC systems and occupancy patterns, to assess their impact on energy consumption. Climatic data for Astara, Iran, with its humid subtropical climate, was automatically integrated into the energy models. The research focused on optimizing energy consumption by analyzing different building configurations and identifying design strategies that minimize energy use and costs. The results of the modeled building analysis indicate that the average annual energy cost will be $19.2 per square meter per year. Accordingly, the average energy use intensity is equivalent to 181 kWh per square meter per year. Compared to the previous building state, potential savings could reach up to 50% in the final annual energy cost. In comparison to the overall baseline, this value could rise to 66.40%. Regarding energy use intensity, the potential savings are estimated at 20.25% compared to the previous building state and 47.57% compared to the overall baseline. The study uniquely combines the evaluation of energy efficiency with a comprehensive assessment of parameters and factors affecting energy consumption over 30 years, all within the context of a building information modeling (BIM) system. This integrated approach distinguishes it from previous research, which likely focused on either energy efficiency alone or without considering a hybrid framework within a BIM environment.

Building Energy Management Using Building Information Modeling: Evaluation of Building Components and Construction Materials

Abstract
Traditionally, the building energy model is created in isolation from the architectural building information model and energy analyses have relied on a single analysis tool. The building energy model can be generated more quickly by leveraging existing data from the BIM. The impacts of energy consumption are significant in the building usage phase, which can last several decades. Due to the large share of the final energy consumption in the building sector, accurate analysis of the thermal and cooling loads of a building and the efforts to reduce energy losses represent an effective way to reduce energy consumption. Therefore, it is essential to analyze the building energy performance in the design phase, which is when critical decisions are made. This study aims to investigate the impact of the building components and construction materials on building energy efficiency using Building Information Modeling (BIM) technology in a mild climate zone. After reviewing the proposed designs, the main building form was chosen for energy modeling and analysis. Then, building energy consumption analysis was performed based on the basic parameters of the building energy model. Eventually, the most optimal mode was selected by examining different energy consumption forms. This study showed that the building HVAC system always had the largest share of energy consumption. Finally, the results of parametric studies on alternative schemes of energy use intensity optimization showed that 22.59% savings could be achieved as compared to the base building model in a 30-year time horizon.

BIM-Based Optimum Design and Energy Performance Assessment of Residential Buildings

Abstract
Buildings are the largest energy consumer in the world, according to the United Nations Environment Program. Most of the energy will be used during the building life-cycle stage. Thus, achieving sustainable development at the national level requires minimizing the impact of buildings on the environment by reducing energy consumption. Using Building Information Modeling technology in energy performance assessment could be significantly reduced time and cost. This study aimed to optimize energy consumption in a residential building using BIM technology. The main focus of this study was to evaluate energy performance through the simultaneous evaluation of building components using BIM technology with a conceptual design approach, comparison, and reduction of energy consumption. To investigate different design ideas were created several conceptual masses in Autodesk Revit software with a top-down design approach. After reviewing the conceptual masses, the main building form was chosen for modeling. Then, building energy consumption was computed using related tools in this field, based on the type of materials, equipment, and project location. Finally, the most optimal mode was selected by examining different energy consumption forms. The results of parametric studies on alternative schemes of energy optimization showed that 58.46% of energy cost savings could be achieved compared to the initial model of the building on a 30-year time horizon.

Effective Energy Consumption Parameters in Residential Buildings Using Building Information Modeling

Abstract
Building information modeling can help in predicting energy efficiency in the future based on dynamic patterns obtained by visualization of data. This study aimed to investigate the effective parameters of energy consumption using BIM technology which can evaluate the building’s energy performance. First, three forms of general states in the building were modeled to evaluate the proposed designs in Autodesk Revit Software. Then, the main building form for energy modeling and analysis was selected. Autodesk Revit 2020 software was also used to obtain the results of climate data analysis and building energy consumption index. Finally, the optimal mode was selected by examining different energy consumption modes. The results showed that the use of building information modeling technology in adjusting the parameters affecting energy consumption can save energy costs up to 58.23% in block D. Energy cost savings for block C and the western lobby were obtained as 51.03% and 43.05%, respectively. Based on energy use intensity, energy cost savings for blocks C, D, and the western lobby were estimated as 16.67%, 16.30%, and 11%, respectively. The results of parametric studies on alternative energy use intensity optimization schemes showed that 16.30% savings could be achieved by the base building model in a 30-year time horizon. Therefore, it was concluded that optimizing energy consumption would reduce environmental pollutant emissions and contribute to the preservation and sustainability of the environment.

Handbook of Energy Analysis Using Building Information Modeling (BIM)

Abstract
According to the United Nations Environment Programme (UNEP), buildings are the largest worldwide consumers of energy. Most of the energy used by any building is consumed during the usage (or operational) stage of the building’s life-cycle. Achieving sustainable development at the national level will require minimizing the effects of buildings on the environment with the low energy consumed by buildings. The energy performance of a given building is predicted and assessed by conducting an energy simulation. Using BIM in EPAs greatly reduces time and costs. The purpose of this study was to optimize energy consumption in buildings, using Building Information Modeling Technology (BIM), which can assess energy performance in the building. In this research, the general form of the building was modeled in the Autodesk Revit Software. After reviewing the proposed designs, the main form of the building was selected for modeling. Then, according to the type of materials consumed, the equipment and location of the project, the calculation of the energy consumption of the building was carried out using relevant tools in this scope. Finally, the best possible mode was chosen by examining different energy consumption modes. The results of energy simulation showed that 61.48% of the difference between the best mode of energy consumption optimization and the current state of the building, as well as 79.35%, is compared to the initial state. Finally, parametric studies of alternative cost optimization schemes showed that saving 58.23% of the building's current status for a 30-year horizon.