19 AUG 2019 / Author: Erkin Çakar
How far does AI power extend In Solar energy?

Artificial Intelligence is quite a powerful tool used by emerging companies to understand and alleviate upcoming issues in a more effective way. Now, the question arises, how far does AI’s “power” extend?

Taking the simplest of examples, the retail industry has begun to shift from traditional data collection, leaning heavily on AI based real time collection. This means that customer behavioral patterns are analyzed and measures are taken to reel them in at the same instant. In the energy sector, it may be translated to prediction type problems which pose the question: ‘is it possible to predict when this equipment will fail?’ If yes, I can establish maintenance prior to the failure to certify that the plant doesn’t grind to a halt, hence saving on unnecessary maintenance.

On a large scale this pre-emptive alert can save you millions of kWh over time, which is a vital edge to have in this energy deficient world. Saving at this magnitude is the equivalent of investing, putting the AI backed energy companies, two steps ahead of their competitors, in terms of both profit and environmental impact.

Bill Gates, founder of Microsoft, wrote an online essay to college students graduating worldwide in 2017 where he stated:

“If I were starting out today… I would consider three fields. One is artificial intelligence. We have only begun to tap into all the ways it will make people’s lives more productive and creative. The second is energy, because making it clean, affordable, and reliable will be essential for fighting poverty and climate change.”

Renewable energy, has recently taken a digital turn, incorporating itself with different online systems, indicating that AI has a bright future in the energy sector. One example is of Google’s DeepMind technology, which rose to fame for teaching itself to play the game GO, through a technology called reinforcement learning and went on to become the World’s number one player. Shortly after, the team responsible for the technology announced that its machine learning algorithms could cut electricity usage at Google’s data centers by 15% and subsequently it reduced the energy usage by 40% which translated into saving hundreds of millions of dollars for Google over several years.

The Solarify model initially takes 40 days to learn the patterns displayed by the PV cells and then adapts to their behavior, thus enabling the AI system to conduct a predictive & preventative analysis for any problem with a detection rate of 98%, the accuracy level is highly efficient, propelling Solarify into the league of the future.

With the ascent of cloud computing and the diminishing expenses related with computations, currently and later on this innovation will be increasingly more accessible. With Google Cloud, the ability to perform profoundly complex calculations is promptly accessible for all Solarify users. One of the most substantial strides in AI frameworks is model training and validation. Having the option to pay every moment or even second for the utilization of computing power eliminates the need for enormous initial investment and server maintenance costs.

Switch to Solarify to be a part of the future!