Energy Sector Realizes Untapped Potential for Real-Time Analytics

The energy sector is undergoing rapid and radical changes moving towards more decentralized power generation, intelligent distribution grids, exchanges to instantly buy and sell capacity, smart meters in homes and offices, and innovative customer services. For these efforts to be successful requires data and real-time analysis to provide actionable insights based on that data.

Unfortunately, to date, most organizations have barely scratched the surface when it comes to leveraging the numerous streams of data available to them. A handful of organizations have used real-time data from sensors in grid elements such as transformers combined with predictive analytics for proactive maintenance. Others have combined smart meter electricity usage, customer financial information, and predictive analytics to identify which customers are most likely to fall behind on paying bills.

See also: Can IoT Provide Utilities With New Business Models?

For the most part, efforts like these are the exceptions. And many in the industry are starting to recognize this problem. Industry leaders have called out the market, noting businesses have the potential to make use of the data they capture, but very few have succeeded.

But the situation is about to change. Recent market studies have found a broad embracement of real-time data collection and analysis is poised for significant growth in the coming years.

For example, one study found that investment in IoT in the energy sector in the U.S. will grow at a compound annual growth rate (CAGR) of 17.3 percent through 2027. It noted the growth is attributed to the need for “operational potency and real-time decision-making.”

Eyeing the benefits and value of using this technology, almost every month there is an announcement of another major IoT expansion from major utilities and grid operators. For example, earlier this month, Arizona Public Service, the largest electric utility in Arizona, said it would scale from a pilot program using wireless IoT monitoring devices in its fleet of combined cycle power plants to full deployment of the technology in three of its plants. The utility noted that the IoT data combined with predictive analytics software would help eliminate downtime by solving what has historically been a major problem. That being, how to ensure the uptime of its power plant assets.

Naturally, as the industry embraces IoT and deploys more sensors, the data they generate will need to be analyzed. Another recent study reflects just that point. It predicts that big data analytics use in the energy sector will expand at a CAGR of 10.2 percent through 2024.

The bottom line: The use of new real-time data streams and predictive analytics will give utilities intelligent decision-making capabilities to improve operations, reduce downtime, and better serve their customers.