Jan 24, 2017: Over the recent years,solar industry has started to embrace methods to examine and crunch data, with the aim to reduce solar energy cost. Also, the industry is looking to extend its reach into new markets for their technology with the help of data tools.
Easy consumer reach
One of the major issues that solar companies face is selling solar panels to consumers. Most consumers are price-sensitive when it comes to buying solar panels.Now, with the rise of data tools such as machine learning, sensors and algorithms, the companies are finding it much easy to reach out to its potential consumers and convince them.
Machine learning is an artificial intelligence method which involves feeding data to algorithms so that the algorithms get improved at finding out the patterns in the data.
Reduced solar cost
The solar companies have now started to invest on tracking, monitoring and assessing data from solar projects across the world. This helps to reduce the cost of generating energy from the sun.
This data can be utilized to push down the solar cost in order to compete with fossil fuel energy. Hence, it helps solar companies to make business, and helpssave the world from generating energy that emits huge carbon emissions.
Solar firms use data tools
PowerScout, a startup firm based in California, has developed a smart technology that utilizes e-commerce, analytics and big data to find efficient ways to sell solar panels. PowerScout’s software can scan numerous data regarding the existing and future solar customers. The software can also predict which customers are likely to purchase the panels.
Another company, kWh Analytics based in San Francisco, has launched an innovative solar software product that uses data from worldwide solar projects to persuade insurance companies to back a production guarantee for solar projects. The guarantee helps to reduce the interest rate of the money for solar systems, and therefore reduces the cost of financing them.
On the other hand, key electronic player Flex has acquired a machine learning startup known as BrightBox Technologies through its solar gear subsidiary NEXTracker. The company developed a software to optimize heating and cooling systems in buildings.
NEXTracker intends to utilize the company’s softwareto use machine learning to optimize the expansion and operation of its solar hardware across the world.
In addition, machine learning giants such as IBMare initiating ways to utilize data to reduce solar energy cost. In 2013, IBM’s research division worked on finding out how to leverage artificial intelligent engine Watson for clean power.
Currently, IBM research has 200 partners that utilize its solar and wind forecasting technology. Such technologies can forecast solar and wind conditions from between 15 minutes to 30 days in advance.
Azuri, a UK-based startup, which sells solar panels, is using machine learning to know about its customer’s usage patterns and to administer the batteries and power sources in the most favourable manner.
A good combination of several data tools will definitely help in reducing solar cost. This will prove to be vital in transforming thesolar sector into a more mainstream energy source.