Data insights for utilities lessen energy disruptions and improve customer service

By | 2 minute read | March 10, 2020

The lights again went out in California, and this time, the outage wasn’t directly caused by nature.

Several times in the fall of 2019, the utility Pacific Gas and Electric took preventative measures to intentionally cut power, due to fear that high winds and dry conditions could have caused outdoor equipment to spark wildfires.

While companies like PG&E work to update their infrastructure, data insights for utilities can help energy providers take precise actions to lessen the need for wide-scale preventative outages. With a comprehensive understanding of infrastructure and data, utilities will not only make informed forward-looking decisions that minimize risk and blanket outages — they’ll also have pointed insight to satisfy customer demands for affordable, sustainable and reliable electricity.

For utilities trying to rebuild from the costly damages of wildfires and weather events, modernized outage management and energy forecasting will go a long way toward maintaining equipment, delivering service and restoring public trust. Utility modernization is a significant investment, and it might give utilities pause.

But they can’t afford to wait.

Getting a handle on vegetation

PG&E experienced the worst of worst-case scenarios, and it serves as the ideal illustration for what can happen to utilities when they don’t upgrade infrastructure and data management. Utilities worldwide now contend with an increase in severe weather, which scientists attribute to climate change. Whether it’s intense storms or heat and drought causing dry vegetation, utilities have to prepare for the new reality of unfavorable weather.

Fortunately, modernization lets utilities take advantage of AI-supported applications that provide rich, detailed insights by combining internal information, such as maintenance records and staffing, with external sources, such as real-time weather, localized prediction models and the data that outlines supply and demand.

For example, AI-based applications are identifying troublesome vegetation areas near utility equipment and combining historic and real-time weather data to offer clear snapshots of trouble spots that might otherwise go hidden. A Texas-based utility teamed up with IBM in 2019 to create a predictive analytics tool that analyzes data from satellite and drone imagery, IoT sensors and weather models to provide continuous insight on how tall, wide, dry or wet vegetation is — and how close it is to equipment. The utility uses the data to identify outage threats so that it can send work crews to the highest-priority areas, prevent fires and avoid service interruptions.

Trying to predict unpredictable weather

Much in the way they can’t depend solely on employees to stay on top of the overgrowth that poses a risk to hundreds of miles of transmission and distribution lines, utilities can no longer rely on manual analysis to predict storm damage. Severe weather can strike fast and can do more damage than anticipated. Utilities in North America and Europe have turned to automated outage management applications supported by advanced analytics to get a better handle on what’s to come.

One of IBM’s utility clients in Europe needed help preparing for increasingly regular severe-weather events: flooding and severe thunderstorms in the summer, snow and ice storms in the winter. Armed with hyperlocal weather data, the utility can mobilize crews to areas for prep work, ready its supply chain for expected parts and have accurate estimates on the need for generators — all moves that can cut restoration times and mitigate revenue loss.

Preparing for short-term disruptions is critical, but so, too, is planning for the long-term health of the business. Advanced analytics-supported utility modernization will reveal potential supply and demand issues, improve customer service and produce reliable and affordable electricity.