IBM unveiled new technology to reduce
power outages by helping energy companies predict where trees and other
vegetation may threaten power lines. IBM worked with Oncor, the largest
utility company in Texas and the fifth largest in the U.S., to develop a
solution tailored for the energy and utility industry, to help improve
operations and provide reliable electric service for millions of
customers across the state.
The Weather Company Vegetation Management - Predict is built on IBM
PAIRS Geoscope, a groundbreaking technology developed by IBM Research.
The system quickly processes massive, complex geospatial and time-based
datasets collected by satellites, drones, aerial flights, millions of
IoT sensors and weather models.
The resulting insights can help companies like Oncor to monitor
vegetation growth across their entire service territory, allowing them
to better identify and predict potential infringement with power lines.
Businesses can more proactively and accurately plan for preventive
maintenance and rapid response, focusing crews in the highest-priority
locations and validating that necessary trimming was completed as
expected.
"Electricity is an essential part of our lives, and millions of Texans
depend on Oncor every day. Vegetation poses a serious risk to power
lines and the surrounding areas, but monitoring it is a challenging and
time-consuming process," said Peter Stoltman, vegetation management
program manager, Oncor. "By working with IBM, we are able to use
analytics and AI to prioritize high-risk areas. This helps us adapt
maintenance operations to improve public safety and service
reliability."
Vegetation is a leading cause of service interruption for utility
companies. With traditional approaches, the primary insight into
potential risks involves expensive on-site inspections or knowing the
last time an area was trimmed. With this new solution, hundreds of miles
of transmission and distribution lines will be regularly monitored to
provide continuous insight about the state of growth and maintenance. In
addition to helping identify and predict outage threats,
geospatial-temporal insights can help with overall grid reliability and
compliance, wildfire prevention, storm management and assessment.
"Our utilities clients told us that getting detailed insight into the
state of vegetation across their service territory was a key challenge,"
said Mahesh Sudhakaran, chief digital officer of IBM Energy, Environment
and Utilities. "By combining PAIRS with AI and industry expertise, we
can give clients one integrated solution, delivered through IBM Hybrid
Cloud, to help them predict and manage vegetation in a cost-effective
and intelligent way."
"Every business is affected by weather. But for energy companies and
their customers, it can mean the difference between whether they can
keep the lights on and heat their homes," said Cameron Clayton, IBM's
general manager of Watson Media and Weather. "The ability to layer
weather data with satellite and sensor data gives utility companies
powerful new insights to help them improve operations and minimize
impact on their customers."
PAIRS
Geoscope ingests more than 10 terabytes of new data per day and has
already served more than 15 million requests from more than 4,000
researchers, data scientists and developers in 80 countries. It removes
the labor-intensive process of generating insights from
geospatial-temporal data, which is known for its sheer size and
complexity. The inability to access, query and analyze this class of big
data in a scalable way is the reason it was long considered unsearchable
data. IBM scientists invented a new way to run and analyze complex
queries within minutes instead of weeks or months, making previously
impossible insights now a reality.
PAIRS Geoscope is generally available for different industries and use
cases. In addition to Vegetation Management - Predict, PAIRS is also the
underlying technology for Watson Decision Platform for Agriculture, a
suite of agribusiness tools that uses the power of AI and geospatial
data to help farmers make more informed decisions about their crops.
