AI-Powered Grid Inspection: NYSEG Uses Drones & Machine Learning to Upgrade New York’s Power Lines
Image Credit: Benjamín Gremler | Splash
New York State Electric & Gas (NYSEG) has embarked on an ambitious project integrating artificial intelligence with advanced imaging technologies. This initiative aims to comprehensively assess and upgrade the state's extensive overhead distribution system.
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Comprehensive Data Acquisition
Commencing in September 2024, NYSEG's project employs a multifaceted approach to data collection:
Vehicle-Based Imaging: Specially equipped vehicles traverse the state's roadways, capturing high-resolution images of overhead electrical equipment.
Aerial Drone Surveillance: Drones provide aerial perspectives, accessing hard-to-reach areas and offering detailed views of infrastructure components.
On-Ground Personnel Inspections: Trained staff conduct in-person evaluations, ensuring data accuracy and addressing areas requiring immediate attention.
This coordinated effort covers over 45,000 miles of overhead lines, marking it as the company's most extensive data acquisition endeavor to date.
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Integration of Artificial Intelligence
Central to this project is the deployment of AI-driven image recognition models. These models analyze the collected imagery, cross-referencing it with internal databases to identify equipment that may not meet current safety or durability standards. This proactive approach facilitates timely recommendations for equipment replacement and system upgrades.
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Operational Phases
The project unfolds in distinct phases:
Initial Imaging: Utilizing vehicles to capture comprehensive images of the overhead distribution network.
AI Analysis: Processing the imagery through AI models to detect potential equipment issues.
Targeted Inspections and Maintenance: Deploying drones and ground personnel to scrutinize identified concerns, followed by necessary repairs or upgrades.
Notably, this survey is designed to be non-intrusive, ensuring continuous power supply without interruptions. The focus remains solely on utility-owned equipment, respecting private property boundaries.
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Implications for Grid Reliability and Safety
By harnessing AI and advanced imaging, NYSEG aims to transition from traditional reactive maintenance to a predictive maintenance model. This shift is anticipated to enhance the grid's reliability, reduce outage occurrences, and optimize resource allocation.
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Challenges and Considerations
While the integration of AI offers numerous benefits, it also presents challenges:
Data Management: Handling and processing vast amounts of image data require robust infrastructure and sophisticated algorithms.
Accuracy of AI Models: Ensuring the precision of AI in identifying defects is crucial to prevent both false positives and negatives.
Privacy Concerns: Maintaining strict protocols to ensure that data collection respects individual privacy and complies with regulatory standards is imperative.
Source: Gov Tech, Yahoo News, News Break
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