Addressing the Complexity of Vegetation Management with Advanced Technology

Addressing the Complexity of Vegetation Management with Advanced Technology

Utility vegetation management (UVM) is a challenging task, requiring management of tree and vegetation growth around power lines and utility assets to prevent outages and maintain consistent service. As climate change increases, the risk of vegetation-related disruptions due to extreme weather, utilities, EPCs, and surveyors are turning to advanced technologies to enhance UVM practices.

The Importance of Vegetation Management 

Overgrown vegetation presents significant risks, including power line outages, and wildfires. In 2018, trees contacting power lines sparked a devastating wildfire in California, leading to tragic loss of life and destruction. 

Proactive vegetation management is crucial for preventing such disasters and complying with the strict regulations set by the North American Electric Reliability Corporation (NERC), where failure to meet standards can result in hefty fines. Though the initial investment in vegetation management may be high, the long-term benefits in safety and cost savings far exceed these upfront costs. For instance, CNUC found that 25% of U.S. energy outages are vegetation-related, underscoring the economic and environmental impacts of effective UVM.

To address these challenges, utilities are increasingly investing in UVM, with expenditures nearing $8 billion annually (Harris Williams, UVM report). By adopting advanced technologies, they can transition to proactive strategies, enhancing safety, efficiency, and reliability.

Enhancing UVM with Advanced Technology

Technologies likeartificial intelligence (AI) and digital twins are revolutionizing UVM. AI processes data from multiple sources, such as satellites, drones, and ground sensors, to identify areas where vegetation could pose risks to power lines. By analyzing growth patterns and potential obstructions, AI helps utilities and their partners proactively address risks, reducing vegetation-related outages by as much as 15% (McKinsey).

Digital twins, meanwhile, offer real-time insights by creating dynamic virtual models of physical infrastructure. These models allow users to predict and mitigate the effects of vegetation on the reliability of power grids. Studies show that digital twins can significantly lower maintenance costs by enabling more targeted and efficient management strategies.

Integrated infrastructure intelligence systems, combining AI-driven analysis, digital twins, and real-time monitoring give utilities a more holistic view of their assets. These systems help in scheduling maintenance, reducing risks, and improving grid resilience.

A notable example is the Looq Platform, developed by Looq AI. This platform utilizes the proprietary handheld qCam, which features multiple high-resolution cameras, survey-grade GPS, and an AI processor. The qCam captures intricate data, which is then uploaded to the cloud for analysis by Looq’s AI-powered software, resulting in survey-grade, geo-referenced 3D digital twins, ortho-images, and AI-generated semantic information.

The technology helps create an initial overview by identifying and analyzing vegetation and tree types along power lines. Modern remote sensing techniques pinpoint areas where vegetation might pose risks. This information allows engineering teams to take preventive actions, reducing the likelihood of power outages and improving grid reliability.

After completing vegetation management activities, such as tree trimming, are completed, the technology gathers new data to assess the effectiveness of these actions. By comparing this updated data with the initial assessment, teams can quickly pinpoint any residual risks and take necessary actions.

Looq AI’s platform represents a powerful solution for modernizing vegetation management and improving utility operations. Image: Courtesy of Looq AI

Furthermore, these tools continuously monitor vegetation growth, spotting potential hazards before they become serious problems. Real-time alerts and data-driven recommendations help users maintain the safety and reliability of power lines.

Benefits of a Modernized Approach

• Automated Identification: AI can be used to automatically identify and classify power poles, power lines, vegetation, and trees, creating detailed maps of dangerous areas. It can generate risk-based trimming plans that outline priorities and necessary actions for trim crews.
• Advanced 3D Modeling: Classified 3D models of power lines and their surrounding environment can be used for analysis and planning. The qCam, with its multi-camera system, survey-grade GPS, and AI processor, captures detailed field data up to 100 times faster than traditional methods.
• Growth Predictions: These advanced modeling techniques can be used to predict vegetation growth, offer accurate forecasts and flexible reporting. The ability to generate custom reporting and integrate seamlessly with other applications can help shorten project timelines, proactively manage issues, reduce risks, and enhance client interactions.

Caption: This integrated system is designed to reduce outages caused by trees, lower trimming costs, and minimize liability and operational risks. Image: Courtesy of Looq AI

Strategic Recommendations 

To fully leverage advanced technologies, utilities, EPCs, and surveyors should assess the capabilities of various tools, including AI, digital twins, LiDAR, ground control, and satellite systems. Conducting a detailed cost-benefit analysis can reveal the return on investment (ROI) for implementing either standalone technologies or a comprehensive multi-layered strategy. By combining multiple technologies, stakeholders can achieve an optimal balance between cost-efficiency and accuracy, ensuring the best value for their investment while improving safety and operational performance.

Improving the accuracy and accessibility of data is crucial for driving informed decision-making across diverse teams. Making sure that the information collected is user-friendly and actionable ensures that it supports efficient planning and execution. While aerial and remote sensing technologies provide broad coverage, ground-based assessments remain a critical part of any UVM strategy, capturing detailed information that may be missed from above. Ground control data further enhances the overall solution by enriching aerial data with on-the-ground precision.

Collaboration with technology vendors is crucial to tailoring solutions that address the unique needs of utility operations. Clear communication of the ROI, supported by real-world case studies, helps decision-makers understand the value of these technologies.

Staying current with the latest technological trends and maintaining a feedback loop with clients will drive continuous improvement in UVM strategies, helping utilities adapt and thrive in an ever-changing environment.

Conclusion

Effective vegetation management is critical to utility safety and reliability. Advanced technologies such as AI, digital twins, and ground-based reality capture solutions offer a more efficient approach to UVM, helping utilities prevent outages, comply with regulations, and safeguard customers. As climate change intensifies these challenges, investing in modern UVM tools is key to building a safer, more resilient power grid that benefits all stakeholders.

Author Bio: 

Christine Byrne serves as the PR and Corporate Communications Director at Looq AI, bringing 23 years of experience in infrastructure. In her role, she develops and implements strategies to enhance the company’s visibility and highlight its significant contributions to the built environment. Contact: cbyrne@looq.ai

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