Utilities and energy providers aim to be the new weather experts in town

By Rob Boucher, IBM

In 2020, there were 22 weather-related disaster events with losses exceeding $1 billion each that affected the United States. North America grappled with a hyperactive hurricane season that set multiple records for the frequency of storms, in addition to widespread, destructive wildfires over the summer. This year, the impact of severe weather could be similarly devastating.

Naturally, just as severe weather conditions and hurricanes in the U.S. have increased in frequency and intensity over the last thirty years, so too have the length and scale of power failures. Under these circumstances, energy providers and utilities are facing increased pressure from consumers around the world to make their services more resilient to severe weather. 

Consequentially, now more than ever, energy providers are becoming experts on the weather.

By keeping a closer eye on the forecast, energy providers can help predict and prevent many of their biggest problems before they ever occur. With deeper insights into how weather conditions will affect their daily operations and energy consumption rates, energy providers can make more informed, proactive decisions to restore power faster and increase customer satisfaction. It can also help them reduce costs.

Related: Load forecasting, weather anomalies, data access are key to managing the grid of the future

More and more of these companies are investing in sophisticated technology that closely tracks upcoming weather conditions in their region, analyzes the impact of those conditions on their services, and incorporates that information into daily decision-making. With this information, energy providers and utilities can anticipate interruptions to their service and respond accordingly, including efficient task force allocations and real-time, location intelligence information delivered in an easily digestible, actionable manner.

Weather decisions are business decisions

Businesses that anticipate the impact of severe weather can make proactive choices that positively impact their bottom line, rather than responding reactively.

Take for example the leading Canadian utility provider Hydro One, who is steadily focused on maintaining safe, reliable and affordable power for their customers in the province of Ontario. However, without an on-site meteorologist, Hydro One relied on a third party for information on incoming severe weather. Ultimately, Hydro One couldn’t respond proactively to power outages because it didn’t know exactly where and how weather events might impact its system.

To meet rising customer expectations, better manage resources, and respond faster and more proactively to severe weather, Hydro One integrated a sophisticated artificial intelligence model and weather forecasting data to help make better decisions around mobilizing resources ahead of severe weather. The AI tool takes historical data from Hydro One’s outage database and compares it against the weather patterns that caused the interruptions. When storms are predicted, the forecasted weather is run through the AI model to generate an outage forecast. With this new toolset at its disposal, Hydro One can look out 72 hours in advance, map the forecasts against its emergency response staging and planning, and begin to activate those emergency procedures well in advance of any storm. Instead of using the first 24 hours to reposition resources, Hydro One’s prepositioned people and equipment so they can be repairing lines and restoring power more quickly.

Ultimately, severe weather and fallen trees cause the majority of all outages. Organizations that are serious about tackling outages must consider how the surrounding vegetation will impact their operations while developing their strategies. 

Pedernales Electric Cooperative, the largest electric cooperative in the United States with more than 300,000 active accounts across Texas, is helping to reduce their incidence of outages by analyzing the local plant life with artificial intelligence from IBM. Using aerial footage from drones, airplanes or satellites, as well as using forecast data from The Weather Company, the artificial intelligence tells Pedernales Electric Cooperative which lines are in danger of being disturbed by tree branches or other natural impediments that may bring them down in the event of a storm.

Staying ahead of the storm

Failing to properly manage the vegetation around power lines can be an expensive problem. Pedernales Electric Cooperative previously spent approximately $10 million annually to manage vegetation around its power lines – but would still miss overgrowth areas or unnecessarily trim vegetation because they relied so heavily on a scheduled cutting regime. Additionally, in California, three investor-owned utilities have historically spent more than $250 million annually for vegetation management on distribution lines alone.

Utility companies must stay ahead of the storm to restore power quickly when severe weather strikes. Although 49 percent of utilities say they are very prepared for a major weather event and 69 percent say they are using predictive methods, 45 percent are experiencing weather-based outages multiple times a year and 30 percent are experiencing them at least once a year. 

By keeping a close eye on the weather, and using technology that creates insights from that information, energy providers and utilities will be better equipped to manage severe weather in the future.

About the Author

Robert Boucher is meteorologist and senior offering manager for energy & utilities at IBM. Robert has 20 years of experience working in the weather industry and in his role he is responsible for developing innovative weather solutions and decision support tools to the energy and utility companies, as well as energy commodity traders. Prior to joining The Weather Company, Robert was a research associate at TASC, Inc. Robert received his Bachelor of Science degree in Meteorology at Plymouth State University and a master’s degree in Atmospheric Science at Texas Tech University.

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