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Energy Analysis with Revit Insight and Green Building Studio

Model

This article shows the flexibility and consistency of energy analysis performed with BIM-based simulations such as Revit, Insight, and Green Building Studio. These tools were used to study the energy performance and thermal comfort of an existing building to reduce the dependence on the mechanical system of the building through retrofitting strategies. The BIM tools helped the designers to experiment with all possible design alternatives before the execution for the final design solution, which saves money and time while simultaneously contributing to more energy-efficient building design.

Performing Energy Analysis

Rapid urbanization has resulted in exploitation of the available energy resources. Greenhouse emissions due to the maximum usage of the mechanical system for active cooling of the building has created greater impact on our fragile ecosystem. This was an eye-opening situation for people all around the world, thus promoting energy-efficient solutions for the buildings. Envelope systems pose a great scope to reduce the energy consumption and consequently improve building efficiency. It is not yet known in what way building envelope design measures are to be selected and the performance in hot and humid climates.

This research focuses on the energy performance of the building envelope of a high-rise residential building in Chennai, India. We explore how to improve thermal comfort through quantitative analysis of the effect of thermal characteristics of the exterior building envelope. The base model was developed in Revit and simulated in Autodesk Insight and Autodesk Green Building Studio. The study summarizes the design parameters for effective building envelope design from the simulation results to reduce the dependency on active means of a mechanical system, which in turn helps to improve thermal comfort.

Related: Powering BIM — Capitalizing on Revit for Building Energy Modeling with David Butts

Research Methodology

Research methodology, Part 1.
Research methodology, Part 1.

 

Research methodology, Part 2.
Research methodology, Part 2.

 

Variables and weightage.
Variables and weightage.

Site Documentation

Site documentation

View of the Kgeyes Carolinaa Apartment, Bharani Street, Ramagiri Nagar, Velachery.
View of the Kgeyes Carolinaa Apartment, Bharani Street, Ramagiri Nagar, Velachery.

 

Planning of Kgeyes Carolinaa Apartment, Bharani Street, Ramagiri Nagar, Velachery.
Planning of Kgeyes Carolinaa Apartment, Bharani Street, Ramagiri Nagar, Velachery.

 

East elevation of Kgeyes Carolinaa Apartment and section AA.
East elevation of Kgeyes Carolinaa Apartment and section AA.

 

South elevation of Kgeyes Carolinaa Apartment and section BB.
South elevation of Kgeyes Carolinaa Apartment and section BB.

 

The study area and the block taken for a particular period of time for the energy analysis study.
The study area and the block taken for a particular period of time for the energy analysis study.

 

Analytical Assessment

Performance Assessment via Simulation with Revit Insight and Green Building Studio

Model Simulation Parameters

Parameters 1

Parameters 2

Parameters 3

Inputs for Energy Model Generation in Revit

Based on location, Revit collects the required data for simulation from the local weather station for the weather data and sun path.

Project location and the location of the weather station which is 0.00 km away from the project location.
Project location and the location of the weather station.

Heating design temperature: 21℃

Weather data of Kgeyes Carolinaa Apartment, Bharani Street, Ramagiri Nagar, Velachery.
Weather data of Kgeyes Carolinaa Apartment, Bharani Street, Ramagiri Nagar, Velachery.

 

Energy Setting Inputs

It is to specify that the energy model uses the information generated by Revit for walls, doors, roofs, windows, and floors in order to perform the energy simulation.

Energy setting  in Revit.
Energy settings in Revit.

Advanced Energy Setting Inputs

Energy settings control the behavior of the energy model creation. They also control the optional use of additional information specified in the Revit model, such as material properties and thermal space properties.

Energy settings

Based on the thermal input values for different components in the building such as walls, roof, ceiling, slabs, floor, and glass, it creates an impact on the heating and cooling load in the building.

Material Thermal Properties: Conceptual Types

Material thermal properties

Material Thermal Properties: Analytical Types

Material thermal - analytical

Energy Models

Energy model generated in Revit.
Energy model generated in Revit.

Based on the inputs provided by Revit such as location, weather data, and thermal properties, the energy model is generated in the form of base color codes for different components in order to be simulated by Insight.

Energy model generated by Insight.
Energy model generated by Insight.

Energy Simulation Models: Heating Loads

Heating loads

The heating load diagram above shows the amount of heat energy which is needed to be added to the space in order to provide an acceptable temperature range. It can be seen that most of the top floor periphery rooms are cold during the day during the winter and rainy months. The spaces below and the rooms facing the open courtyard are also relatively cold compared to the rooms facing the outer environment.

Energy Simulation Models: Cooling Loads

The cooling load diagram below shows the amount of heat energy which is needed to be removed from the space in order to provide an acceptable temperature range. It can be seen that most of the top floor periphery rooms are hot during the whole day. The spaces below and the rooms facing the open courtyard have relatively less heat energy compared to the rooms facing the outer environment.

From the simulation results, it can be seen that the building consumes about 206 kWh/m2/yr.

Cooling loads

Analytical Assessment: Daylight Analysis with Revit Insight

Inputs for daylight analysis in Revit.
Inputs for daylight analysis in Revit.

 

Analysis for Illuminance

Illuminance analysis is mainly done to measure the daylight availability in the particular area. The floor level taken for the study is the first floor for the daylight analysis.

The Perez All-Weather Sky Model is a mathematical model used to describe the relative luminance distribution of the sky dome and has become the de facto standard model for day lighting calculations, as it uses real data gathered from weather stations all over the world.

The two parameters that the Perez Model uses are delta (representing sky brightness) and epsilon (representing sky clearness). These parameters are determined from the measured diffuse horizontal and direct normal irradiance values for specific sites and date/time combinations, which can be obtained from, for example, Energy Plus. Diffuse Horizontal Irradiance is from the sky alone, measured horizontally.

Study Samples

Daylight analysis for first floor.
Daylight analysis for first floor.

 

Daylight analysis for second floor.
Daylight analysis for second floor.

 

Daylight analysis for third floor.
Daylight analysis for third floor.

 

Daylight analysis for fourth floor.
Daylight analysis for fourth floor.

It is seen that the spaces that are arranged in the periphery of the building receive abundant to optimum levels of daylight during the day, but the inner spaces receive much less.

Analytical Assessment with Green Building Studio

Annual energy consumption.
Annual energy consumption.

 

Breakdown of energy consumption by different equipment annually.
Breakdown of energy consumption by different equipment annually.

 

Summary Result

Green Building Studio gives a report on the amount of energy and electricity consumed per annum by various factors such as area light, external usage, miscellaneous equipment, space cooling, vent fans, pump aux, and hot water.

Results and Inferences

Efficiency factors achieved through window-to-wall ratios and efficiency factors achieved through window shades.
Efficiency factors achieved through window-to-wall ratios and efficiency factors achieved through window shades.

 

Efficiency factors achieved through glass type, Iighting, green roof, wall type, orientation, and PV panels.
Efficiency factors achieved through glass type, lighting, green roof, wall type, orientation, and PV panels.

 

Energy-Saving Strategies

1. Building orientation

2. Window shades

3. Window-to-wall ratio

4. Window glazing

5. Wall construction helps in reducing heat loss and heat gain

6. Lighting efficiency—average internal heat gain and power consumption of electrical lighting per unit floor area is lower based on the reduced usage of lighting during the day which is attained by proper availability of daylight.

7. The efficiency in daylighting an occupancy control can be achieved by usage of advancement in technology for daylight dimming and occupancy sensor system.

8. Panel efficiency which is attained by the percentage of the sun’s energy that will be converted to AC energy. Higher efficiency panels cost more, but they produce more energy for the same floor area.

Conclusion

Based on the study and analyses, there are several factors which contribute to energy consumption in the building, including:

  • Building orientation
  • Window shades
  • Window-to-wall ratio
  • Window glass
  • Wall construction
  • Roof construction
  • Lighting efficiency

These energy consumption factors can be reduced by using appropriate technology for designing the building envelope, which plays an important role in the consumption of energy in the building. It is concluded from the simulation results that by proper use of shading devices and window glass help in the reduction of energy consumption wherein the roof construction showed less energy benefits.

The analysis done during the study highlights the importance of reducing the heat gain through the building envelope and improving the thermal comfort level and energy efficiency in residential buildings in Chennai.

The simulation results show the possible façade design that can efficiently control the amount of insolation, maintain a satisfactory quality of indoor environment, contribute to the reduction in energy demand, and at the same time support and consolidate the architectural vision.

The nature of the building envelope determines the amount of energy needed to heat and cool a building and hence needs to be optimized to keep heating and cooling loads to a minimum, which is a major factor that has to be considered while designing a building.

At a broader policy level, it is necessary to develop similar codes to be included in the building bye laws and national building code. This is necessary to make new residential building stock in India adhere to minimum levels of thermal comfort and energy efficiency.

Ferny Celina is a master's student in the Department of Architecture, School of Architecture and Planning, Anna University, Guindy, Chennai, Tamil Nadu, India.

References

Energy Efficient Building Envelope and Ventilation Strategies for Multi-Storey Residential Buildings in India. Pierre Jaboyedoff, Sameer Maithel, Ashok Lall, Saswati Chetia, Prashant Bhanware, Bharath Reddy (2017).

Energy-saving Potential of Building Envelope Designs in Residential Houses in Taiwan. Chi-Ming Lai and Yao-Hong Wang (2011).

Examining the Role of Building Envelope for Energy Efficiency in Office Buildings in India. Farheen Bano, Mohammad Arif Kamal (2016).

Technology Roadmap - Energy Efficient Building Envelopes. International Energy Agency, France (2013).

Zero Energy Building Envelope Components: A Review. Sunil Kumar Sharma (2013).

An Introduction to ECBC and Energy Efficiency in Buildings Sector. Amar Relen.

Energy Conservation Building Code (2017).

Sustainable Building Skin Design. Maggie McIntosh (2017).

High-Performance Commercial Building Façades. Eleanor Lee, Stephen Selkowitz, Vladimir Bazjanac, Vorapat Inkarojrit, Christian Kohler (2002).

 

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