Modern-day infrastructure is a success story of human ingenuity. Thanks to innovations in engineering and technology, people around the world have access to safe and reliable electricity, gas, water, and internet. And this reliability brings huge benefits, from increased productivity to better health.
But while innovation strives towards more robust power grids, safer water systems and improved connectivity, climate change impacts are creating new challenges. Utilities are now turning to data-driven weather intelligence to help them make agile, confident decisions to address these challenges.
Weathering the storm
The U.S. is home to weather extremes – from the searing heat of Death Valley to frigid northern winters. It means utility companies need to provide services that can withstand a huge range of temperatures, elements, and natural forces. But increasing extreme weather events are testing grid resiliency and raising the potential for outages, downtime, and damage to infrastructure.
According to Climate.gov, in 2022, the U.S. experienced 18 separate weather and climate disasters costing at least 1 billion dollars. This is a trend that’s being repeated worldwide. To help mitigate these threats, utilities are leveraging weather intelligence and sophisticated modeling, such as AI and machine learning, to better plan, prepare and respond to power disruptions, even before bad weather begins.
How predictive analysis benefits utilities
Data-driven weather intelligence can help protect assets, improve planning, and cut the length and severity of outages and avoidance of regulatory penalties. For example, one company reports the improved efficiency in mobilizing contractors ahead of large event reduce their system average interruption duration index (SAIDI) by 10% outage durations by achieving 96-hour estimated time of restoration.
But not all companies have the resources for a dedicated data science team to process and deliver continuous data. This is where utility solutions like within the DTN Storm Risk suite can make a big difference. Utilities of all sizes can leverage weather data to predict and prepare for the impacts of adverse weather.
Weather data may be plentiful. But it's finding relevant, actionable insights within that data that bring valuable insights. For example, Storm Risk Dashboard, one of the utility solutions in the DTN Storm Risk Suite, differs from standard weather reporting tools in that it's designed to deliver insights and warnings tailored to a specific operation.
The dashboard monitors conditions based on custom settings, parameters, and thresholds. A user can enter and map assets, set weather thresholds, and establish alerts for a broad range of weather variables, such as high winds, lightning, and extreme temperatures. Storm Risk Dashboard has user-friendly interface with real-time insights served up in a timely, efficient way.
The speed and accuracy of this system means utilities can better anticipate, prevent, and mitigate outages. Responses can become more targeted with faster service restoration. It boils down to good data, enabling good decisions.
Predicting outages before the storm
Hurricane Ian is a recent example of how advanced insights can help reduce restoration efforts. Hurricane Ian made landfall in southern Florida on September 28, 2022, and by the time it dissipated four days later in North Carolina. The third costliest weather disaster in U.S. history according to the National Oceanic and Atmospheric Administration National Hurricane Center, left more than four million homes and businesses without power.
While there was no way to stop the hurricane’s path, advanced knowledge of the potential impact would enable utility providers to plan and position crews and request mutual assistance before the hurricane hits. DTN put Storm Risk Analytics to the test to see how the outage solution would have performed under the constantly changing path of the hurricane. Nearly two days before landfall, DTN Storm Risk Analytics predicted 4.59 million customers would experience outages during the storm. This forecast was within 7% of the actual outage count (4.29 million). One day before landfall, the revised prediction fell within 3% of actual outages.
Whether it involves hurricanes or heatwaves, forecasting the impact of weather events with a high degree of accuracy puts utilities several steps ahead. Utilities that can determine as early as possible where and when outages will affect customers will find themselves at a significant advantage in terms of potentially reducing power disruptions, business costs, resiliency, regulatory compliance and reputation.
To find out more about how advanced weather intelligence can help build grid resiliency and maintain reliable power visit the DTN Storm Risk suite of utility solutions.
*Outage Insights Help Utilities Prepare Before the Storm: Hurrican Ian Insights
