|Big data and technological advancements are transforming the way we use solar energy / Photo Credit: Liptak Robert (via Shutterstock)|
As we become more aware of climate change, using the energy produced by renewable sources is becoming more crucial in reducing greenhouse gas emissions, according to Daniel Neiditch of entrepreneur news website Entrepreneur. While wind and solar energy play a valuable role in this initiative, they can be intermittent and unpredictable.
There are days when the wind doesn't blow or if it's cloudy. In order for us to rely on an energy source, we must first understand "how much power will be available and what the demand for it to be." Then, we use the energy source to efficiently meet the demands of consumers. This is where big data will shine.
For example, IBM’s Hybrid Renewable Energy Forecasting solutions (HyREF) leverages cloud-imaging technology and sky-facing cameras to forecast the weather "up to a month in advance." This can increase renewable power generation- either stored or delivered to the grid- by up to 10%, which is enough to power 10,000 homes.
Forecasting technology and big data also help in maintaining hundreds and thousands of panels across a solar farm. Without the help of technology, this can be a difficult, sensitive, and expensive process.
Extra Space Storage (ESS) utilizes big data analytics to detect underperformance and predict when inefficiencies occur without deploying a worker on site. The firms Virtual Irradiance (VI), a solar management program, gathers ground level sunlight-intensity to determine when "panels aren't performing at expected rates," sending a notification that repairs or maintenance are needed.
This particular type of analytics can be leveraged to study whole communities to offer suggestions on where solar panels could be the most effective based on weather patterns and sun exposure. For instance, South Australia has collaborated with Tesla to establish the world's largest virtual power plant. 50,000 Tesla batteries are connected with the panels, thereby slashing costs associated with stabilizing the energy grid by $28.9 million.
Big data and machine learning have started to transform many industries. Now, it's revolutionizing the way "we think and use solar energy." Energy companies, investors, and consumers alike have heard the cry for change. Now, they finally have a solution for utilizing technological advancements to become part of the solution, rather than being a part of the problem.