A few years ago, Tyler Hartshorn began growing his own fruits and vegetables in his backyard and commuting by bicycle to his job teaching mathematics at a local high school.  When a solar power company approached him offering to install solar panels on the roof of his home, it seemed like the logical next step to a more sustainable lifestyle.

Hartshorn’s growing interest in an eco-conscious mindset also served as the inspiration behind his capstone project for Springboard’s Data Analytics Career Track. Using his newly-gained analytical skillset, Hartshorn decided to calculate the return on investment of producing his own electricity. He wanted to do this not only for his own personal benefit but also to show others that using renewable energy isn’t just an act of environmental stewardship—but an astute investment for any homeowner. 

“I don't believe that altruism is a great motivator for people—I don’t think anyone is truly selfless—so when I talk about my sustainability efforts, I really try to frame them in terms of personal self-interest,” said Hartshorn. 

Installing solar panels on a home not only reduces monthly utility bills. It can potentially also increase a home’s value by up to 4.1%. A recent study found that solar panels are viewed as upgrades equivalent to a renovated kitchen or finished basement, and homebuyers across the country are willing to pay a premium of $15,000 for a home with an average-sized solar array. Homeowners also benefit from an energy tax credit that allows them to deduct 26% of their installation costs from their taxable income, saving nearly $9,000 on average. What drove Hartshorn to invest in solar energy himself was the incentive that his loan payments on the solar array would be roughly equal to the savings on his electricity bill. By installing 15 solar panels on his roof, he could generate just over 60% of his energy needs.

“This is a legitimate investment in my main source of equity,” Hartshorn explained. “I'm just taking money that I would have been giving to the power company and instead investing it in my home.”

In recent years, residential solar has become more affordable and accessible than ever before. PV panels are the most common type of solar panels in residential use. They contain photovoltaic (PV) cells that absorb photons from sunlight, which creates an electrical field across the layers and causes electricity to flow. Since 2014, the average cost of PV solar panels has dropped nearly 70%. While just 3% of the electricity produced in the U.S. comes from solar energy, according to the Office of Energy Efficiency and Renewable Energy, the U.S. surpassed two million PV solar installations in 2019, and this $17 billion industry is on track to double again in the next five years. However, finding data on financial incentives for residential solar requires extensive research. What’s more, the returns vary widely depending on the home’s location and its conduciveness to generating solar energy—which hinges on factors like tree cover and the size and slope of the roof. 

Analyzing the ROI of residential solar

One year after installing a solar array on the roof of his home in North Carolina, Hartshorn noticed that the energy data he received from the utility company didn’t match up with the reported values from his home system. This is because energy is lost in transmission. Estimates show that a solar PV plant loses 12-15% of its power as it passes through a series of power transformers in transmission. For the U.S. energy grid overall, energy loss is estimated at 6% —2% in transmission and 4% in distribution. 

Hartshorn decided to do a three-part analysis using a year’s worth of data on solar energy generation at his home:

1. What is the actual return on solar investment after accounting for transmission loss?

2. How does residential solar ownership in North Carolina compare to the rest of the U.S.?

3. How can we use data insights to enhance solar investment incentives? 

Dataset

Hartshorn generated his own dataset by collecting a year’s worth of data on solar energy production at his home through a web browser application called Enphase, which allows homeowners to track the performance of their solar panels through an app or web browser. These dashboards can be used to monitor energy production and usage on a daily, weekly, monthly, and lifetime basis, while also inspecting the performance of individual solar panels.

Analysis

Hartshorn analyzed energy production across a range of variables, including weather conditions and time of year. He also wanted to understand how the solar potential of his home state, North Carolina, compared with other regions, and how natural weather conditions coupled with state policies lead to either favorable or unfavorable conditions for residential solar investment. 

Weather conditions

Hartshorn compared energy discharged (measured in Wh) across the following weather categories: 

• Clear 

• Partially cloudy

• Rain

• Rain, Partially Cloudy

• Snow

• Snow, Partially Cloudy

He used a weather API to cross-reference the energy data with weather conditions on each day of the year and categorize the data points according to the six weather categories. Unsurprisingly, clear weather makes for optimal energy discharge. However, Hartshorn found that rain does not impact solar power generation as much as cloudiness. On a clear day, median energy discharge is a peak 23,667 Wh, while partially cloudy weather yields a median of only 14,693 Wh. A watt-hour is a unit of energy equal to one watt of output for an hour. While the watt-hour is the SI unit of power, electrical power consumption in a household is usually measured in Kilowatt-hours (which is equivalent to 1000 watt-hours). For context, a 100-watt light bulb operating for 10 hours would use one kilowatt-hour of electrical energy. The average home in the U.S. uses approximately 909 kWh of energy per month (909,000 Wh), or around 10,909 kWh per year, according to the U.S. Energy Administration. 

Time of year

March through December were peak months for energy generation, with June being the most productive month. Energy discharge peaked in April 2020, with 640,086 Wh discharged. (See dashboard above.)

What weather-related variables affect solar energy production?

According to Hartshorn’s analysis, two main determining factors for energy production are cloud cover (%) and visibility (miles). In other words, there is an inverse relationship between cloud cover and energy production, and a positive relationship between visibility and energy production. 

Using a Python package for linear regression, Hartshorn performed a multivariate linear regression on the dataset he’d collected for one year in order to generate a formula he could use to predict energy production based on weather report inputs for these variables with 92% confidence.

The equation is:

• Energy discharged (Wh) = -263.1524*(Cloud Cover) + 2581.7071*(Visibility)

In addition to these two variables being most strongly correlated with energy production, Hartshorn says he chose cloud cover and visibility because they are more or less observable, even without technology. 

“Maybe there’s a mountain in the distance and I can look at it to estimate the visibility on a given day. I can look at the sky to estimate cloud cover,” said Hartshorn. “I have this idea of someone being off the grid and wanting to predict how much power they're going to get for the day, and use that to estimate just with their own observations and plan things like ‘Should I do laundry today?’”

How do conditions for residential solar investment compare across the U.S.?

The attractiveness of residential solar varies across the country not only because of unequal climate conditions (for example, the west coast receives more average daily sunlight than the northeast) but also because of differences in state-level policies that incentivize residential solar installation.

One of the main metrics for measuring innate solar potential is Direct Normal Irradiance (DNI). This quantitative measure estimates the irradiance from the sun at a perpendicular intersection with the earth. Solar panels are tilted to optimize this interaction. Seeing as regions exhibit different variations in DNI throughout the seasons, DNI is expressed as an average for the year.

The darker regions in Hartshorn’s map exhibit a higher average DNI and therefore have the potential to generate the most solar energy. Hartshorn mapped DNI levels across the country to compare the solar potential in North Carolina to other parts of the U.S. and reveal which regions could benefit from greater financial incentives around residential solar investment given their solar potential. He also cross-referenced this data with publicly available data from the Office of Energy Efficiency and Renewable Energy on average monthly utility bills in each state with the idea that states with the highest rates would benefit most from offsetting their costs using solar energy. 

Regions in the southeast exhibit high utility rates and usage due to a range of factors, including an above-average number of days with 100-degree-plus weather in the summer leading to heavy reliance on air conditioning. The deregulation of the energy grid in Midwestern states like Texas and Georgia allows customers to choose their own electricity and natural gas suppliers but leads to price gouging during peak times of the year.   

According to Hartshorn’s analysis, the southeast is the region where financial incentives for residential solar could create the most impact. The southeast receives relatively lower DNI compared to the western states—which already have the highest rates of solar adoption due to a combination of ideal weather conditions and government-sponsored financial incentives—but consumers pay high electricity bills and thereby stand to save the most money. 

Innate solar potential and financial incentives are an important combination for residential solar adoption.

The role of state incentives in residential solar investment 

Given the ideal weather conditions for solar generation in western states, it’s little wonder that California and Hawaii are the states with the highest rates of solar adoption, dwarfing all other regions in terms of overall residential deployments and storage.

Hartshorn’s home state of North Carolina is ranked second-highest after California in terms of existing solar capacity, however, there are few state-level financial incentives to encourage people to further invest in residential solar or to generate surplus electricity. North Carolina has a “net metering” policy that credits homeowners when they produce more electricity than they use (eg: during midday when most people are at school or work). Homeowners can then use those credits to offset their energy needs during off-peak times, such as evenings or on cloudy days. A net meter records the energy spent compared to the energy received from the grid and credits the homeowner for the surplus.  

Storage is a key component for scaling residential solar power. Storage enables homeowners to store surplus energy generated during the peak season to use later, rather than sending it back to the grid. In fact, even homes that don’t have a solar array can use storage to capture power from the grid and store it for power outages or times of peak demand, thereby reducing the cost of power. But due to North Carolina’s net metering policy, storing surplus power in a battery rather than sending it back to the grid eliminates the cost savings you would otherwise see in your electricity bill. 

“Creating a system where people are paid for overproducing, as opposed to just pumping the energy back to the grid, would make up for the fact that not everyone can install solar panels on their home,” said Hartshorn. 

The energy lost in transmission

While the net metering policy provides an incentive to invest in solar power in exchange for a lower utility bill, it forces homeowners to transfer power back to the grid in order to reap the benefits. Energy is lost during transmission—each time power is transferred to and from the grid. Hartshorn calculated how much energy he was losing during transmission by comparing the data on energy production from his home system with data on his energy usage provided by his utility company. He found that his solar panels were in fact producing 112% of his energy needs, but 46% of this electric power was lost during transmission to and from the grid. A solution to this would be local governments investing in neighborhood storage systems or states giving out micro loans so that homeowner’s associations can pool funds to purchase a shared storage system. 

“If we can store power at the source of energy we can prevent loss of power in transmission,” said Hartshorn. “So storage would really help with sustainability and value and efficiency for the grid. And I think that's where policies should go.”

Residential solar incentives as a social mobility tool for low-middle income households 

Hartshorn says that investing in residential solar can help low-middle income households build wealth by saving on their electricity bills, building equity in their homes and increasing their home’s value. Generally speaking, LMI households are underrepresented in the residential solar market because of other factors that preclude them from homeownership, such as a low credit score or history of eviction. 

Hartshorn used a dataset from the National Renewable Energy Laboratory to visualize the percentage of LMI buildings with solar potential state by state, as well as the potential dollar savings per year from switching to solar energy. In southwestern states such as New Mexico, Arizona, and Kansas, residents can save over $1,000 a year.