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Low-Tech is the key Problem for Solar Electricity Companies

Kirk Edelman, chief commercial officer of Safari Energy, a Solar Electricity development, construction, and asset management firm based in New York City, spoke with Electrek about the three technologies that the solar industry needs to adopt to transform processes and infrastructure. Many solar companies started as small businesses that hacked together whatever methods and software they could to handle everything from sales to accounting.

They frequently expanded by concentrating on finding less expensive, more efficient equipment. According to the Solar Energy Industries Association and Wood Mackenzie, solar capacity in the United States will rise by a factor of four this decade. To keep up with the increased demand for Solar Electricity, Edelman outlined to Electrek what technology he believes the US solar sector requires and why.

Low-Tech is the key Problem for Solar Electricity CompaniesFrom shading to soiling, the efficacy of panels is influenced by millions of variables and data points. Artificial intelligence will be required to parse and derive insights from these data points. AI allows us more automation, fewer human errors, and more time to arrive at previously unachievable discoveries.By continuously upgrading the algorithms utilized, machine learning enhances the benefits of AI. A program may recognize patterns and self-correct by giving it real-world data and reference cases, resulting in increased accuracy.

Simply put, solar enterprises must employ sophisticated analytics in their operations. Companies can de-bottleneck resources to maximize productivity out of current equipment and enhance daily operations by recording and analyzing the data they generate to detect flaws in their equipment and processes.

The aforesaid technological breakthroughs open the door to other developments, such as digital twinning, which entails developing digital representations of actual solar equipment to run simulations on its degradation through its lifetime. Companies may predict when their equipment will fail and replace it ahead of time with this preventative maintenance idea, avoiding costly downtime.

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