162. How PG&E Is Reducing Wildfire Risks Using Satellite Imagery

The POWER Podcast

Wildfires have had a devastating impact on California and on the state’s largest utility company, Pacific Gas and Electric (PG&E). Potential wildfire liabilities exceeding $30 billion led PG&E to file for bankruptcy in January 2019. The company emerged from bankruptcy on July 1, 2020, with a renewed focus on mitigating wildfires within its 70,000-square-mile service territory in northern and central California. “A lot has changed,” Andy Abranches, senior director of Wildfire Preparedness and Operations with PG&E, said as a guest on The POWER Podcast. “We really saw the devastation that could occur from these wildfires, and so, that was the point that PG&E started really making a big pivot to addressing the wildfire risk. The way we address the wildfire risk is really through what we consider our layers of protection. We started initially learning as much as we could from San Diego Gas and Electric [SDG&E], and put in place the public safety power shutoff program.” High-fire-threat district maps were important in understanding risks. About half of PG&E’s service territory falls in high-fire-threat areas. “We have 25,000 distribution miles that run through the high-fire-threat districts and 5,000 transmission miles,” said Abranches. Vegetation plays a critical role in the risk, and while precisely quantifying the number of trees in and around those risky transmission and distribution lines is difficult, Abranches estimated it’s in the range of eight to 10 million. With such a large area and so many trees to monitor, PG&E turned to Planet Labs, a San Francisco-based provider of global, daily satellite imagery and geospatial solutions, for help. Planet’s satellite-derived data on vegetation, including canopy height, cover, and proximity to electric-system infrastructure, is used by PG&E to prioritize the mitigation of vegetation-associated risks. Quantifying Threats and Consequences Abranches explained PG&E’s risk characterization process by likening it to a bowtie. “The first part of your risk bowtie is: ‘How do you quantify and in a probabilistic way build a risk model to predict ignitions are going to happen?’ ” He noted that the biggest source of ignitions is through contact with vegetation, such as a tree falling on a line or a branch coming into contact with a line on a windy day, but birds and other animals can also cause ignitions. “The second half of the bowtie is the consequence,” said Abranches. “If an ignition occurs at a particular location, if the vegetation around it is just not there, that ignition will never spread.” The fire triangle requires heat (or a spark), oxygen, and fuel. The fuel is the vegetation bed around the line where the ignition event occurs. If there happens to be a lot of dry fuel, that’s when an ignition becomes a wildfire. Depending on the oxygen, which can be heavily influenced by wind conditions, it could become a catastrophic fire, Abranches explained. “As we built our risk models, you needed to understand the vegetation dimension on two levels. One level is for probability of ignitions: ‘How do we get better at predicting where we expect vegetation ignitions to occur?’ And the data that we’re able to get from Planet every year helps improve and keeps those models updated,” said Abranches. “The second piece of it is the consequence of the ignition—understanding the fuel layer. That also—data from Planet—helps inform and continually refreshes that information to make sure it’s most current. So, the risk model actually uses the Planet data on both sides of the bowtie, because it’s probability of ignition times the consequence of ignition gives you the risk event.”