AI’s Potential For The Solar Panel Industry
With recent advancements in artificial intelligence, how can it help to improve the leading clean energy source?
When do humans not encounter it in their everyday lives? From scrolling through TikTok to turning on a light switch in the morning, the average American uses about 10,632-kilowatt hours of energy yearly, with the majority of them coming from fossil fuels.
Today there are plenty of clean energy sources that help to reduce our carbon footprint, although most of them can only be used in certain areas. Hydropower needs flowing water to create electricity, and geothermal energy is usually only obtained near fault lines and other sources of heat. Nevertheless, 92,714,000 miles away from planet Earth lies one of the most readily available energy sources — the sun. Not only is it extremely powerful, but its absorption emits none of the greenhouse gasses that contribute to global warming.
However, this resource is currently not being used to its full potential. With conventional solar panels, like the ones found on top of houses and in solar farms, only 20–30% of rays are converted to energy. Although this is partially because the average solar panel can only absorb visible light, things like a panel’s placement and its overall condition also add to this low efficiency rate.
Artificial Intelligence, or AI, is one of the most versatile technologies out there. Its usage ranges from medicine to video games, and it can also be used to improve solar panel effectiveness. In this article, I’ll discuss the ways AI can and has helped the issues mentioned above, allowing solar energy to be as effective as possible.
Panel Placement
Where a solar panel gets placed has a huge impact on its ability to produce electricity. Does this area get frequent cloud cover? Is the air in this location often polluted? While these questions matter less for a residential panel, as there is only a given amount of space to work with, solar farm developers need to keep them in mind to increase overall effectiveness. The truth is, however, that this kind of information can be hard to find without accurate future predictions. This is where AI comes in.
Data Science, or the studying of data to create insights, has been used ever since the 1960s to analyze and create trends based on prior information. With the help of machine learning, a type of AI, computers can make more precise forecasts than ever before. By applying this to the solar panel industry, researchers can collect data on climate and pollution patterns in a certain area, factor in current issues like climate change, and create predictions about how much solar radiation the location will receive in the future.
Maintenance
Like almost any machine on earth, solar panels require routine maintenance to ensure that as much electricity as possible can be generated. Some potential issues, including obstructions and internal malfunctions, need to be resolved as soon as possible to prevent further damage. With artificial intelligence, we can reduce these negative impacts significantly.
Obstructions
When solar panels are exposed to photons or sunlight, they release electrons that are converted to a current of energy. This means that the more surface area a panel has, the more photons it can absorb, and therefore more electricity can be produced. By this logic, if something was obstructing the panel, less solar energy would be generated because there is less surface area available.
Using previous data, machine learning algorithms can be trained to detect the differences between panels with or without obstructions. After interpreting enough data to have high accuracy rates, cameras on the panel can be used to detect these foreign objects. The objects are run through the software, and the company gets notified.
Internal Malfunctions
In the diagram above, one can see how the different components of a solar panel work to generate electricity. When sunlight gets absorbed through the p-type and n-type silicon in the solar cells, it causes electrons to become ejected from the silicons. Once ejected, they travel between the two layers to form a current, which can then be used as electricity.
If even one of these steps does not function properly, the panel may not work to its full potential. From minor damage, such as broken glass, to a blown fuse, every part of a solar panel has an impact on how much electricity can be generated. This impacts the efficiency rate of these panels significantly, but there are ways to help this issue.
Similar to the applications used for obstructions, AI can be used to learn what malfunctions look like and can send out help to repair them. The less time that panels spend out of commission, the more electricity that can be produced, helping to power homes and businesses.
Problems with Implementing AI in Solar Power
While these solutions may seem like they should already be common in solar, that is not the case. Cost is a huge factor in this, as AI-driven tech is extremely expensive to develop. Companies that do decide to invest in solutions like these would need to pass the costs onto consumers, which would then prevent many households from switching to solar. In the current crisis of global warming, the goal is to get as many people as possible to use clean energy. To do this, clean energy needs to be an affordable option for everyone, not just people of higher classes. While higher efficiency is something that we will need in the future, it would need to be more accessible for it to be commonplace.
Future of Solar Energy
Today, a few organizations, including Open Climate Fix and SETO, have worked to integrate similar concepts into their solar technology. While this is a huge step in the right direction, it will not make much of an impact on a small scale. Until this and similar technology have widespread into the majority of solar panels on Earth, we are underutilizing the greatest source of energy that humankind has.
