Data Dominates at DistribuTECH 2019

Each year, approximately 12,000 utility industry professionals gather for 3-4 days to learn, teach, and discuss products and trends in the industry at DistribuTECH. The 2019 show, held in New Orleans, Louisiana, had a consistent theme in the transmission and distribution (T&D) space—the collection, assimilation, and analysis of grid data and its applications for grid performance improvement. Data collection through the deployment of sensors and monitoring devices has been among the most consistent market forces in the T&D space over the past few years. However, part of the focus has shifted, and utilities and other market players recognize an important fact: data is only as valuable as the information gained from it. 

The T&D Data Collection Market Is Growing, Will Analytics Keep Up?

The amount of data utilities have at their disposal is growing significantly. The global market for utility data collection via T&D sensing and measurement technologies is estimated to be nearly $2.4 billion in 2019, and is expected to grow at a compound annual growth rate (CAGR) of approximately 10.7% through 2026 according to Guidehouse Insights' T&D Sensing & Measurement Market Overview report. But the deployment of sensors and measurement devices across the grid is only part of the solution. These devices collect data. For the data to have value it must be interpreted and analyzed, and transformed into information. 

For the interpretation, analysis, and conversion of collected data into information, utilities are investing significantly into the IT and analytics sector. According to Guidehouse Insights' Smart Grid IT Systems report, the global market for smart grid IT and analytics will reach $21.4 billion by 2026, at a CAGR of 5.9%. 

Smart Grid IT and Analytics Revenue by Region, World Markets: 2017-2026

(Source: Guidehouse Insights)

The market activity that drives these high growth rates—for both sensing and measurement as well as IT and analytics—was readily apparent throughout the massive exhibit hall at DistribuTECH. Long-time industry mainstays such as ABB, General Electric, and Siemens AG showcased end-to-end grid management and Internet of Things analytics platforms and newer, more focused companies highlighted offerings such as Sentient’s Ample Analytics platform. The emphasis on data was clear. Also noticeable on the exhibit floor was an increase in the number of exhibitors without a hardware or communications offering. That highlighted the recognition by the industry that software- and- analytics-only vendors do have a place in the market, and their share is growing. 

As the quantity of grid data collected by utilities continues to grow, so too must utility investment in increasingly complex and diverse analytics platforms. The figure below illustrates the evolution of utility analytics, highlighting the effect of innovation on the value delivered by data analytics. 

Utility Analytics Progression

(Source: Guidehouse Insights)

In the figure, most utilities would currently find themselves between reporting and descriptive analytics in regard to analytics for their T&D assets. Reporting analytics are those that simply notify the utility of an operation condition, such as an outage. Descriptive analytics will not only report the outages but also include details such as its location and the scope of affected customers. And it might also provide additional details on possible causes. Examining the figure through the scope of just the distribution network, most utilities fall somewhere between zero and reporting, as many utilities are without any distribution outage notification mechanisms. 

Keep Collecting Data but Prioritize Investment in Analytics 

DistribuTECH 2019 was just the latest exhibition to firmly display the importance of creating information out of data. For years, utilities have prioritized data collection, seeking grid visibility as the first step toward improving reliability and resiliency. Utilities must continue to collect data, but should also prioritize investments in data analytics that can transform data from numbers on a screen into informed decisions that will shape the grid of the future.