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Solar tax breaks don’t work for low-income Americans, but study finds another incentive


Solar tax breaks don't work for low-income Americans, but another incentive works

Graphic illustrating the use of satellite imagery over time to identify solar installations, then map specific communities and model income growth and saturation trends. Credit: Zhecheng Wang

When a new consumer technology debuts for the first time, whether it’s a smartphone or an electric car, its adoption rate often follows a predictable route. The first buyers came from a small group of high-income users or tech enthusiasts willing to pay high prices. Over time, as prices fell and economies of scale began, sales surged and the technology became a mass product. Eventually, the market becomes saturated and the number of users reaches a stable level.

That didn’t happen to the residential area Solar in the United States, however. Although solar power has increased dramatically over the past decade and the cost of photovoltaic panels has dropped significantly, low-income communities are still much slower than high-income users in getting up to speed. .

In a new study using artificial intelligence to interpret a decade’s worth of satellite images, Stanford University researchers found that low-income communities are much less motivated than high-income communities by tax incentives that the state and local government often make offerings. Even when low-income communities initially installed some solar, their adoption rates remained relatively low.

In contrast, the researchers found, less-used performance-based incentives appear to promote solar energy use in lower-income communities. Interestingly, efficiency incentives, which reward customers based on how much solar they produce or how much less electricity they buy from the grid, appear to have little or no impact on low-income areas. higher input.

“This is the first study to examine the use of solar energy across the United States,” said Ram Rajagopal, associate professor of civil and environmental engineering at Stanford and one of the senior collaborators on the paper. Period in such a detailed manner over a long period of years. -author.

He added: “Our conclusions are a bit surprising. Low-income communities have not accelerated solar use.” “They don’t start at all, or they reach saturation at a very low level. On the contrary, think of smartphones, which were initially so expensive that they were only available to very high earners or super enthusiasts. technology. But in less than 10 years, they became cheaper and are now owned by hundreds of millions of people.”

deep solar

The study is published in today’s issue of the journal Jouleused a machine learning model—dubbed DeepSolar++ by the researchers—analyzed satellite images to determine the location of solar panels and when they were installed in more than 400 counties across the United States. The researchers compiled images from 2006 to 2017, then combined that data with information about each community’s demographics as well as local financial incentives for solar.

The research was led by Zhecheng Wang, a PhD student in Stanford’s Department of Civil and Environmental Engineering. Wang helped build DeepSolar++.

In 2018, the Stanford team published An early study analyzed the number of solar installations at a time. That study confirmed that solar arrays were less common in low-income communities, but it didn’t provide much insight into trends over time. Did those communities start later but then catch up, as is the case with smartphones, big-screen TVs, and other new technologies?

To map the long-term orbit, the researchers were faced with the fact that commercial satellite imagery in the mid-2000s had low resolution. That makes it hard to recognize solar panels. The solution, says Rajagopal, is for DeepSolar++ to compare more recent high-resolution images with older images in the same location. That comparison provided enough information for the system to choose Solar power panels although the previous images are much dimmer.

Time-lapse analysis shows that low income community not simply start later. They are also settling at a much lower rate than high-income communities.

Of course, lower income families by definition have less money to invest in solar energy. Even now, solar energy is often more expensive than buying electricity from the grid, Rajagopal said.

Better incentive

Federal and state governments have long offered financial incentives, often in the form of income or property tax breaks. Performance-based incentives are much less. In theory, those financial incentives should make solar energy more attractive to low-income households. To find out, the Stanford team used a federal database of state incentives for renewable energy to determine what types of incentives were available in each community.

They found the tax incentives only affected high-income communities. One reason, they suspect, is that lower-income families have much lower tax rates and therefore benefit less from tax breaks. Those who rent rather than own their home have no property tax at all.

From a fairness point of view, Rajagopal said, that’s an important finding. By relying too heavily on tax breaks to promote residential solar, governments at all levels may be exacerbating the solar divide between haves and have-nots.

“If you want to accelerate solar adoption in lower-income communities, performance-based incentives are the way to go,” says Rajagopal.

Here, the researchers observed correlations, not causation. They are not sure why performance-based incentives seem to work for lower income community. It is possible that a less common category of incentives could motivate owners of apartment buildings, says Rajagopal.

More information:
Zhecheng Wang et al., DeepSolar++: Understanding the orbit of residential solar energy with computer vision and technology diffusion models, Joule (2022). DOI: 10.1016/j.joule.2022.09.011

Journal information:
Joule


quote: Solar tax breaks don’t work for low-income Americans, but research shows another incentive works (2022, Nov. 16) retrieved Nov. 17, 2022 from https://techxplore.com/news/2022-11-tax-rebates-solar-power-inefficient.html

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