Design Process
Interactive Map
Our final design consists of an interactive map made through a program called MapHub to certify the most suitable zip codes for solar panel implementation.
The map contains the all 80 zip-codes present in Miami-Dade County. We used government-based websites to collect data regarding climate and solar panel investment.
When clicking on one specific code, it displays the information:
Elevation
Flood risk
Cost savings
Our Recommendation
Additionally, the zip codes are color coded in accordance with our recommendation that we are making for that area, where the green locations are the most optimal, yellow locations are feasible but there are concerns, and the red locations being really dangerous spots to build infrastructure.
Information Display
When clicking at a specific zip code, the program will demonstrate climate and investment information.
Based on the discovered data, we set a recommendation regarding whether solar panels should or not be implemented through traffic light colors and our verdict sentence.
Methodology and Implementations
Solar Implementation & Constraints
Climate Impact
Climate change and sea-level rise are prominent issues when it comes to Miami-Dade's future. Accounting for these variables will determine whether solar panels are ideal for a given area.
- Average Elevation
Understanding the elevation of an area and how it will be impacted by sea-level rise will influence the lifespan of a solar panel. Due to the electrical components of our recommended energy source, we evaluated areas with high elevations.
Breakdown
We chose the maximum elevation within the Miami-Dade area and compared it with other areas.
Maximum elevation: 30 ft
Formula: Maximum elevation among all zip codes/ Actual elevation = X
Our source for average elevation: National Geologic Map Database Project's TopoView
- Flood Risk
We selected flood as our key weather hazard because Miami-Dade has a rigorous wet season during the summer, which is the period when heavy rainfall is expected on various days, and hurricanes, tropical storms, and consequently storm surges may occur. By adding impending sea-level rise threats along with frequent tropical systems, flash flooding will become even more recurrent.
Breakdown
We found a scale of 1 to 6 (minimal, minor, moderate, major, severe, and extreme, respectively)
Formula: specific zip code's flood risk / best case based on the key (moderate) = X
Our source for flood risk: First Street Foundation's Flood Factor
X is the value used within the design matrix for a specific category.
Economic Constraints
- Average Roof Space
This factor controls the amount of available area that roof-top solar panel installations have, and therefore correlate to how much electricity can be generated in a location. This factor is used and was sourced by Google's Project Sunroof, and is the basis for our economic considerations for the product.
Breakdown
Used computer-generated estimates based on satellite images of average roof space, to display to users on our map.
Our source for average roof space: Google's Project Sunroof
- Annual Electricity Generated
The purpose is to give users an overview of the amount of electricity that can be generated per year by zip code. This was taken into account by considering areas of high electricity generation to yield the highest rate of return on investment.
Breakdown
Used computer-generated outcomes to provide an overview of electricity generated over a specific zip code. Allows users to quickly compare these values amongst zip codes.
Our source for annual electricity generated: Google's Project Sunroof
- Annual Cost Savings
The cost savings were crucial to determine whether to install solar panels in a certain zip code once the area is deemed safe from a climate perspective. This data is provided so users can determine their own breakeven point and visually see their savings. Areas of higher cost savings were prioritized over others.
Breakdown
Formula to calculate cost savings: average roof space / (cost per 1 kwH 2021) = X
Using a quartile methodology we were able to rank cost savings costs of each zip-code from smallest savings to largest and assign 2021 dollar sign values.
Our source for annual cost savings: Google's Project Sunroof
Recommendations
According to interviews with stakeholders and additional research we narrowed down factors that are critical to the community we are serving and would ultimately impact our recommendations. From interviews with stakeholders, economic factors such as potential savings was a prominent concern. When the team considered long term affects of climate uncertainty we established from our research that flood risk and elevation is the most common pattern we will see in South Florida that can cause damage to solar panel infrastructure. Based on this information we established a design matrix to assist in formulating our recommendations.
We created a scale from one to zero, with one being the most optimal case, and ranked all of the data we had on this scale. We found the sum of these values and then ranked them relatively as a starting point for evaluating the locations.
Beyond ranking each using these variables relative to each other, special care was taken to ensure that our outputs followed in line with our design centered around facing threats from climate change. Every location that did not meet the minimum criteria for flood risk and elevation were automatically assigned as not recommended to build here.
Flood risk was evaluated first, as it defines the propensity of the area to have all of its electrical components damaged and require repair, with all locations containing an extreme flood risk becoming red, or not recommended, and most severe flood risk locations becoming red based on its other climate factor.
Elevation was evaluated second, as it gives an idea for how long it will be before rising sea levels will become an issue for the people in that location, with the spots containing the lowest elevation making it more likely that it becomes not recommended, specifically after considering the flood risk of an area.
These two factors mostly aligned with our data, as spots with extremely high risks of flood and low elevation tend to end up with a low score anyhow, but manual evaluation prevented any recommendations of at-risk locations. Finally, the zip-codes with a high potential cost savings and population density pushed the location closer to green, or highly recommended. These two other considerations were the main components that, once a location was deemed resilient, determined if it became a yellow or green location.
Design Conclusions
In the map, through the incrementation of official data and calculations, we weighted locations based on weather impacts to define the zip codes where solar panels should or not be installed. Through user testing and reviews by our stakeholders, we have determined that the information presented and recommendations through the program are appropriate for decision-makers to refer to when considering installing solar panels.