The Future of Utility Vegetation Management: Embracing Innovation for Resilience and Safety

Have you heard that vegetation management is at a crossroads? Several recent podcasts and webinars have been excited about the evolution taking place with utility vegetation management (UVM). Basically, it’s about where vegetation management is heading and how it will get there. It’s concerned with technological developments that make UVM relevant for today’s power delivery system. Climate change and global warming are impacting the vegetation that the power grid’s rights-of-way (ROWs) cut through and around. It’s a dynamic environment that changes constantly making a nimble footed UVM platform a must have for utilities.

All things considered, the vegetation managers, their staffs, and contractors have been accomplishing vegetation control methods beyond anything that can be expected. They have been getting the maximum performance levels from the tools available, but it’s time to shift the approach. Keeping up with the growing list of vegetation-related risks to the power grid requires an interactive UVM. Traditionally vegetation management was a labor-intensive process that relied on clipboards, paper maps, and physical surveys of the ROWs and still does for so many utilities.

These conventional tactics fall short in the areas of cost effectiveness and efficiency, but that’s why technologies progress. Those old-school systems were too dependent on human interactions. Twenty-first century UVM platforms, however, are proactive and they’re more adaptable, taking advantage of satellite imagery, GPS, ultrasensitive LiDAR, etc. features. There has been some pushback because it uses artificial intelligence (AI), but that makes it flexible and user-friendly and AI does the heavy lifting with data-driven analytics.

Navigating Risks

In simpler terms, AI’s data analytics has the ability to process the massive amounts of big-data, converting it into usable information and doing it autonomously. Another critical feature that AI brings to UVM systems is its ability to recognize patterns in that big-data and make predictions. That improves UVM’s risk-based assessment of encroaching vegetation at or near the ROWs. AI can differentiate between harmless vegetation and vegetation that is a probable hazard. It also addresses factors like growing budget constraints, increased state and federal regulatory oversight, and a shortage of skilled contractors.

That is why these AI-driven UVM systems are turning around the pushback into growing support in our conservative industry. There’s no simple solutions for managing vegetation in our ever changing environment and there never has been, but AI-driven UVM packages offer the best answers available. They improve risk assessments, increase safety, and maximize efficiencies, but their ability to quickly react to developing situations in real-time is invaluable to utilities. AI-driven UVM functions are the most flexible tool available to assure the meter keeps spinning and the power stays on. After all, controlling vegetation is one of the most significant O&M (operating and maintenance) expenses for utilities and grid operators.

Experts place the annual cost of vegetation management between US$6 billion to US$8 billion for U.S. electric utilities. One publication indicated that utilities in California are spending collectively over US$1billion annually in an effort to control vegetation. These figures prove no one is ignoring a problem, but there is pressure to maximize results and not exceed those budgets, which implies improving risk-based UVM strategies.

It's a powerful approach to the critical task of managing vegetation. AI, when integrated into UVM, moves it from being a reactive catchup process to a proactive activity. Moreover, cutting-edge platforms can assess a utility’s entire transmission system and distribution network constantly. AI-driven UVM systems supply real-time precision that identifies specific areas needing immediate action, so resource allocation is focused on critical locations first rather than the calendar.

Accelerating Innovation

Humans need assistance with the influx of big-data that floods today’s vegetation management team. That’s where AI-driven UVM makes sense. This technology makes everyday operation simpler than any of the older versions. Additionally, they access multifaceted databases seamlessly. By utilizing intuitive dashboards AI can take advantage of data visualization tools, making it easier for the users to adapt to real-time updates of the environment around them. This would be an excellent time to talk with an expert and get some firsthand knowledge about these advanced UVMs. “Charging Ahead” called on Hitachi Energy’s Director, Product Management, Work and Management Solutions, Jeff Pauska.

Mr. Pauska began the discussion saying, “When an outage happens, there’s a lot of effort spent identifying what tree was the cause of the outage and why was it missed by the utility’s vegetation management process. It’s an impossible task given the impact of climate change on the severity of extreme weather events. Healthy trees, not sick or damaged trees, are breaking in sustained winds above 70 miles per hour. They become missiles hitting the infrastructure like darts hitting a dartboard. Trying to determine which tree is the trouble tree is wasting time and resources because they’re undetectable with today’s technology.”

Pauska continued, “So what about using advanced technologies like AI to identify that trouble tree? They can’t do it either. AI doesn’t have the data input yet to be smart enough to get to that exact tree before the event. How do we get the intelligence to respond faster to reduce the storm’s impact by preventing outages? Maybe we’re looking at the wrong solution. The emphasis has been on reducing SAIDI (system average interruption duration index), which is critical, but in an environment where outages from storms and wildfires continue to increase, we need to shift our focus somewhat.”

He clarified, “It’s time for a more holistic view of the vegetation environment, which includes methods to improve CAIDI (customer average interruption duration index) too. It’s a well-known fact that the most common cause of power outages is vegetation-related impacts. They account for 20% of all incidents in the U.S. and present substantial operational challenges for all power line operators. Consider the customer who has life-threatening health issues or the business with perishable assets, or other critical needs. The only thing these customers are interested in is having electricity service restored as quickly as possible and Hitachi’s Vegetation Manager improves both SAIDI and CAIDI metrics.”

Continuing Mr. Pauska said, “Hitachi Energy’s application is a closed-loop digital vegetation management system. It uses a combination of AI, advanced satellite imagery, real-time weather forecasts, and other features to deliver predictive insights continuously. The system monitors large geospatial datasets nonstop, which allows for the identification and mitigation of vegetation interferences and risks uninterruptedly. In addition, last year two AI models from two different suppliers accurately predicted the exact path that a hurricane took. This AI technology development represents a breakthrough that’s momentous. It will give utilities the time they need to prepare and have personnel at staging points that gives fast access to impacted areas when it’s deployed. This feature will reduce downtimes along with improving service reliability and it addresses both SAIDI and CAIDI concerns.”

Pauska explained, “In addition, Hitachi Energy’s vegetation management system accurately predicts potential threats before they cause issues or outages, but what about the public safety power shutoffs (PSPS)? The vegetation management system also combines advanced imagery features with AI-driven risk assessment. This enables the identification and prioritizes areas with the highest risk of vegetation-related incidents from weather events and wildfires. It takes PSPS actions to a new level where the PSPS be tailored to specific locations rather than the wide areas commonly used today. PSPS areas can be monitored for revisions and cancelations when conditions warrant such action. Utilities have to reduce risks and at the same time be cost effective with what they are doing. Being able to utilize the latest technological innovations like predictive analysis are only a few of the advanced techniques available through AI-driven vegetation management systems.”

Enhancing Resiliency 

This holistic approach to AI-driven UVM systems presents a tremendous advantage with its autonomous features. It’s a total departure from previous vegetation management platforms because this next generation doesn’t rely on a single method approach to the multi-challenges of managing vegetation. It is a preemptive scheme that takes advantage of being able to incorporate its data-driven awareness into decision making. AI-driven UVM tools were made for today’s fast changing environment like identifying vegetation types and predicting growth patterns that indicate possible hazards before they become dangerous.

In addition, AI-driven UVM automates many of those tasks that traditionally required somebody monitoring and making decisions with limited data. Those resources can now be allocated to duties better suited to their skillsets. AI reduces risk, which in turn expands resiliency by combining enhanced awareness for predictive maintenance. By investing in technologies, utilities are shifting to more comprehensive management practices, which offers more protection for the grid’s critical infrastructure.

Utilities spend a great deal of money on managing vegetation, but despite this vegetation is still one of the leading causes of power outages, and why not! Worldwide, growing seasons have increased significantly. Today, 100-year storms have become commonplace.

Vegetation has the upper hand, but technologies like AI-driven UVM can shift the balance. It’s going to be electrifying watching that happen!