How Can LiDAR Technology Improve Efficiency In Vegetation Management?

The Utility industry in Australia is facing a major problem that is unfolding at a massive scale. It’s a perfect storm of challenges, and this blog will break it all down for you.

Here is how vegetation encroachment impacts power lines:

For many utilities, vegetation encroachment is a major cause of outages. In some areas, vegetation can be blamed for anywhere between 25% and 50% of all outages. With increased instances of fire outages, managing vegetation along power lines is a crucial challenge that the industry has yet to solve.

Vegetation encroachment is a bigger concern today than it was decades ago, given the increasing number of poles used by different sectors. In addition to causing power outages, electricity wires have occasionally started wildfires. High winds have the potential to blow surrounding trees’ branches, which could then strike electricity lines and cause fires. As a result of live wires falling onto neighboring dry grass and starting fires, strong winds can also snap wooden distribution line poles.

Increased power outages and wildfires caused due to power lines also reveal an inherent concern that the industry is just beginning to unravel. There is a crucial requirement for developing reliable and sustainable solutions to mitigate such large-scale natural disasters.

A call for next-gen innovation:

Energy providers have been controlling the vegetation surrounding power lines for many years. In the current situation, many issues have cost utilities millions of dollars in losses, ranging from using conventional and antiquated procedures. The evident lack of skilled workers results in low efficiency, increasing the likelihood of errors and additional outages. It is challenging to patrol and closely monitor vegetation growth over tens of thousands of miles since most power utilities use manual vegetation management solutions. The lack of innovation and archaic practices pose higher risks that demand innovative approaches. Artificial intelligence (AI)-based solutions can identify problematic vegetation patches close to utility equipment and combine historical and current weather data to provide clear images of otherwise hidden problem regions. The traditional method of physically examining sites is very time-consuming and has intrinsic weaknesses that diminish the usefulness of this function, despite millions of dollars spent on identifying right-of-way (ROW) threats.

Bushfire and the Aftermath

There is no way to completely prevent bushfires from happening because bushfires in Australia have always existed naturally in the their ecosystem. There are ways to reduce some of the human causes of these outages by utilizing AI. The Hon. Judi Moylan MP claimed, ‘The aging power reticulation system in Western Australia appears to have been the cause of many fires.’ She was especially worried that the national infrastructure development program has not replaced aging wood power poles, which have long passed their Australian Standard service life. But this is not solely responsible for the frequent fire outages. Various other factors fuel the outages. Bushfires have the potential to seriously harm infrastructure, destroy property, and result in fatalities. Smaller spot fires can start because embers from a big blaze can travel many kilometers. Heavy smoke and toxic gases from bushfires can affect air quality, impede vision, and make breathing difficult.

Why is LiDAR the Need of the Hour?

The Australian energy grid consists of 7 million power poles, over 880,000 kilometers of transmission and distribution lines, or over 22 journeys around the globe. Since LiDAR point clouds can be acquired with higher resolutions at lower costs, they are widely employed in many applications, including predicting the structural features of forests. The possibility of integrating ground- and UAV-captured LiDAR data to create accurate and efficient heat transfer models for building structures aids in automating the tedious task of manual hunting for encroachments. The traditional manual approach is highly time-consuming and not the most reliable approach to deriving crucial data. An excellent technique for proving your network management to an outside regulator is LiDAR. The technology takes a snapshot of the network for compliance and auditing needs. With precise data points, LiDAR increases field efficiency by precisely identifying and locating high-risk off-ROW trees. LiDAR cannot accurately analyze the understorey in these dense overstorey areas because it cannot “see” through the overstorey. LiDAR can also be used to analyze topography and predict soil characteristics in agricultural areas.

Real-Time Use Case that Leverages LiDAR’s Potential

Combining costs for real estate, infrastructure, social programs, and the environment, the Australian economy is more than $100 billion. In Australia, bushfires are still at risk due to increasingly severe meteorological conditions. As a result, it is now more important than ever for Australia’s energy network operators to guarantee a secure supply. To reduce the risk of bushfires, extreme weather conditions and vegetation growth close to power lines must be carefully controlled. More than 1.5 million Victorian homes and businesses receive power from 54,000 kilometers of power lines managed by AusNet. This network has 62% of its locations in high-risk bushfire regions.

AusNet has been employing aerial and road-based mapping techniques to collect high-quality LiDAR data throughout the network. A detected point of an object contains additional data, including density, the number of returns, return number, and GPS timestamp, in addition to 3D coordinate information. To identify the vegetation growth that needs to be trimmed for bushfire safety, LiDAR is converted into a 3D model of AusNet’s network assets. The increased efficiency brought about significant changes in vegetation management. LiDAR data can be used to improve worker safety while minimizing the need for engineers, surveyors, and designers to travel to construction sites. Additionally, they achieved an accuracy of 80.53% for each of the five segmentation categories, saving AusNet an estimated AUD 500,000 annually through automated classification. This use case is a mammoth example that shows the potential of LiDAR and how it could benefit us in managing vegetation in a better way.

An Overview of LiDAR implementation in Real Time

Since it cannot be adopted on a wide scale overnight, the procedure is laborious and takes years of dedication. Accurate ground data is required to implement a more advanced vegetation management program that will provide a positive return on investment. The capacity to expand ML automation, scale analytics across their whole energy network, and become less reliant on human GIS rectification procedures. Automation and implementing LiDAR on a large scale is a lengthy process, but this proves to be the best practice, coupled with manual efforts, restores hope for a fruitful future for utilities.

Why Techwave?

We have a great deal of expertise in LiDAR technology and know-how to employ LiDAR mapping. We are skilled in taking the information gathered using LiDAR techniques and compiling it into thorough, usable models that businesses can use for easier and more efficient vegetation management for their future endeavors.