Kiana Mokrian

Journal Entry For

Module 8 - Make Your Pitch

ACC Folder Link

Link to Student

“Sunergy” - Energy Efficient Building Design

This tool focuses on Passive House principles to optimize solar energy use by adjusting the window-to-wall ratio, enhancing insulation, and adding rooftop solar panels. It simplifies the tradeoff between sustainability and cost estimation by using simplified per-square-foot costs to calculate changes in cost and calculated total energy loads for different alternatives. To improve the user-experience, I’ve minimized the number of outputs, so that the user can focus on the most important values: energy load, solar energy generated, capital cost and usable area.

Inspired by my ‘Intro to Real Estate’ class, this tool is designed for new construction residential apartment buildings.

Intended users: Architects and designers, Energy consultants, Building owners

Need: There's a lack of tools that provide real-time alternatives showing how design decisions affect energy performance while considering cost. The complex and interconnected nature of energy loads—affected by features like the window-to-wall ratio and building insulation—makes understanding these factors difficult. For example, increasing windows increases daylighting, reducing internal heat load from lights, but also increases solar heating load and decreases the area of wall insulation. This trade-off significantly impacts energy efficiency.

Solution: A generative design tool that simulates various building designs with different window-to-wall ratios (WWR), window types, insulations and solar panels. It compares energy load and cost trade-offs and includes how much energy solar panels can generate to offset the energy load.

Inputs

The range of inputs given for inputs are based on industry ranges from low to high for residential apartment buildings of various sizes

Building details

square footage of base floor
number of floors
height per floor
total number of units

Window characteristics

Window-to-wall ratio (percent between 20% and 50%, aligning with industry range)
U-factor (between 0.15 - 1.3)
Solar Heat Gain Coefficient (between 0.15 - 0.9)
Transmittance (between 20% - 70%)
Cost per square foot

Building Insulation

R-values and cost per square foot

walls (R13-23)
roof (R30-R60)
floor (R15- R30)

Solar Panels

Percentage of roof area that will be solar panels ( 0 - 100%)
Panel efficiency
Cost per square foot

Longitude/Latitude of Building Location
Design Day (day, month, range of hours, year)

Fixed Values

Occupancy and internal load (per apartment per day given average size of unit) at any given time

Average internal temperature of 72 degF
Occupants - 200 Watts per person, 2 people per unit
Appliances - 1500 Watts per unit
Lights - using a simple formula to adjust for daylighting: Light = Qmaxlight*(1 - WWR*transmittance)

Qmaxlight is for the scenario of no windows, and would be 1.5 W/square foot * square feet per unit
Assumption: hallways are not accounted for, and so lighting is calculated for the total building

Outputs

Daily Cooling/Heating Load - cooling or heating dependent on the ‘design day’ inputted
Daily Solar Energy Generated
Total Capital Cost
Total Floor Area

Underlying logic of the model you’ll implement

After the user inputs all the required inputs:

Building Geometry:

Use inputted values to generate a building model
Calculate surface area and volume and total floor area (no roof)

Solar Insolation:

Use design day and location to find total solar insolation with solar analysis node
Determine the average temperature for the given design day and location (unsure how as of now)

Windows:

Calculate heat gain (Qsolar = solar insolation * window area total * SHGC)
Calculate daylighting capabilities using the simplified daylighting formula from above
Calculate total capital cost using surface area and WWR