Passive Solar Optimization - Storing Solar Energy in Mass
For this module, I decided to explore how geometry of simple building can affect the capacity for that building to hold solar energy while also prioritizing cost and an energy efficient design (with relation to the facade).
Step 1 - Generative Design Framework
A very brief description of the design decisions from Step 1 following the Generative Design Framework.
- Passive Solar Design (Thermal Mass) vs. Embodied Carbon Impact
- Design Variables
- slab thickness (between 5” and 8” step by 1/2”)
- Floor Length (between 50 and 100’)
- Floor Width (between 40 and 80’)
- Evaluators
- Embodied Carbon
- Thermal Heat Storage
- Most Important Tradeoffs to Consider
- maximizing thermal mass and minimizing carbon impact (both related to total volume).
- Access to Daylight and Views vs. Energy Efficiency
- Design Variables
- Building dimensions (length, width, and height)
- Amount of windows
- Evaluators
- Overall access to the outdoors - amount of perimeter space with glass.
- Energy Efficiency
- based on either total building volume and surface area
- window-wall ratio
- Most Important Tradeoffs to Consider
- As you increase the window to wall ratio and/or the amount of perimeter space with glass, you increase the amount/access to views outside, but at the same time you start to decrease the energy efficiency of the building (less insulated walls and more windows leads to a less efficient facade construction)
- Thermal Storage vs. Energy Efficiency & Cost
- Design Variables
- Dimensions (length and width)
- Total Building Heigh
- Evaluators
- Amount of Thermal Storage Capacity per unit of Solar Insolation (solar storage capacity)
- Cost of building
- Surface Area to Volume Ratio
- Most Important Tradeoffs to Consider
- Maximize the thermal storage capacity while minimizing the heat transfer through the envelope and cost. Adding more material costs more money, but also contributes to long term energy efficiency.
Step 2 - Generative Design Study
- Thermal Storage Capacity vs. Energy Efficiency and Cost
- Design Framework
- Objective:
- what is the optimal layout (floor plate area) and and building height to maximize the thermal mass of the building and minimize cost and heat transfer through the facade?
- What types of designs are achievable to prioritize harnessing solar energy within building materials and making sure that it does not get lost to the exterior through the facade?
- Model:
- Set up Design Inputs and Constant Inputs
- Create a simple rectangular building by lofting two profiles together and making a solid.
- Split the building into floor areas based on a floor to floor height and calculate the slab volume from this floor surface area.
- Compute thermal storage value for slab and facade based on heat capacitances and slab volume and facade area.
- Perform a solar study on all building surfaces to calculate total insolation on the surfaces.
- Compute evaluators based on Surface Area, volume, total insolation, storage capacity, and Floor Area.
- Design Variables:
- Length
- Total Height
- Building Volume
- Constants:
- (able to choose before running calculation)
- Concrete material type (for heat capacitance and carbon factor)
- Slab thickness
- Construction Cost per Square Foot
- Built in constants
- floor to floor height.
- Volumetric Thermal Capacitances for typical facade and concrete.
- Evaluators:
- Maximize - Site Normalized Thermal Storage capacity (kBtu of storage per kWh of solar insolation per year).
- Minimize - Cost of building
- Minimize- Surface Area to Volume Ratio (indicator of building façade efficiency).
- Interpretation:
- Explore tradeoffs between energy efficiency metrics (passive solar and heat lost to facade) and cost.
- Looking at a starting point for sweet spots within geometries to see what types of values are achievable for energy efficiency metrics.
- Identify bands for different heights of widths that would promote low cost energy efficient design.
Step 3 - Generative Design Study Results
Energy Efficiency Indicator (Surface Area to Volume Ratio) vs. Normalized Thermal Storage Capacity (with Construction Cost as Size)
Based on the above graph with energy efficiency indicator on the y-axis (where lower is more efficient), there seems to be a leveling off around 0.1 (where Normalized Storage capacity around 0.03) where the energy efficiency change becomes marginal and the more costly it become to add more thermal storage. I would recommend based on this graph to start to iterate designs around having thermal storage capacities around 0.03 to 0.04, but not move greater with the idea to minimize cost.
Energy Total Cost vs. Thermal Storage Capacity
There are some designs that have the same normalized thermal storage capacity (x-axis) and relatively similar SA/Volume ratio, but varying cost. This starts to lead me to believe that the form does have an affect of maximizing the benefits of the façade while limiting the amount of square footage (relative to cost).
Main Dynamo Graph
