Editor's Note: This is the first in a four-part series examining the growing role of machine learning and artificial intelligence in the power sector. Tomorrow, we look at how regional grid operators are using AI to optimize operations. The future of the electric grid is undoubtedly cleaner and more efficient and distributed, with hefty doses of technology and machine learning helping to operate it all. But if you're expecting a system dramatically transformed, experts say you'll be left waiting. Artificial intelligence and machine learning are already helping utilities run their networks more efficiently, extending the life of equipment and helping to dispatch energy into markets more efficiently.
We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. As technology evolves to support a wide range of tasks, companies are increasingly relying on automation to help improve overall work efficiency and operations. Satellite analytics, specifically, is rapidly growing in popularity and helping businesses in a variety of industries including utilities, energy, mining, transportation, construction and more. In fact, SnapLogic released a report stating 81% of employees say AI improves their job performance. Satellites can travel around the earth at 17,000 mph, capturing hi-res images to provide companies access to historical data, increase safety and cost-efficient insights.
California is becoming a poster child for the risks utilities face from climate change, from power lines starting wildfires to heat waves forcing increasingly renewable-powered grids to the brink of system collapse. But utilities around the world are facing similar risks as they seek to decarbonize their generation fleets and make their grids more resilient to extreme weather events that are becoming more extreme and more common. While the costs of mitigating those risks are hard to quantify, they're likely much smaller than the costs of doing nothing and facing the alternatives. We're seeing this calculation reflected in many ways, from massive asset manager BlackRock's decision to move away from investments in coal and other global-warming-causing industries, to the maintenance and planning failures that led to the power-line-sparked wildfires that forced Pacific Gas & Electric into bankruptcy last year. Data -- the lifeblood of investors, insurers and other professional calculators of risk -- can help utilities better identify these climate-change challenges and optimize their methods to mitigate them.
Life for millions of energy consumers in the United States came to a grinding halt several times in the last few years due to large-scale power blackouts caused by forest fires. Transmission and distribution lines and critical infrastructure belonging to utilities are spread over thousands of miles, often, through poorly accessible wilderness. Overgrown vegetation and dead trees can touch and fall on power lines causing break downs and short circuits. They can also cause forest fires, and when they go unchecked, flare up into major ones. The vegetation across thousands of miles requires constant monitoring, pruning, and maintenance to ensure the right-of-way is constantly maintained.
Relying on last year's weather to predict this year's power outages is an increasingly risky proposition. Climate change is shifting weather patterns in every region, increasing the frequency and severity of storms, wind, and drought. For example, in the wake of the recent tropical storm Isaias, Con Edison suffered its second-largest outage ever, mainly due to damage from trees in high winds. According to Con Ed: "The storm's gusting winds shoved trees and branches onto power lines, bringing those lines and other equipment down and leaving 257,000 customers out of power. The destruction surpassed Hurricane Irene, which caused 204,000 customer outages in August 2011."