Vegetation Management (VM) is a top priority for electric utilities. It is the single most important lever for mitigating risks of wildfires and power outages. Despite serious efforts and investment by utilities, reality shows critical information gaps still exist — with safety, environmental and financial risks as a result. A complete view on the current state and forecasted state of vegetation is critical for an effective workflow to mitigate these risks. The rise of satellite data and Artificial Intelligence (AI) brings the opportunity to close the loop with continuous data-driven vegetation management intelligence. Helping to improve the safety and reliability of the power line system.
Transmission and distribution networks often cross through forests and cities. When vegetation and power lines interfere it brings serious safety, economical, and environmental risks. Vegetation, in combination with severe weather conditions, is the most dominant cause of outages in electric power systems, resulting in millions of people without power and billions of dollars in economic damage. The combination of wires, vegetation and severe drought are at the source of record-breaking wildfires, endangering public safety and environment. With increasing frequency and duration of severe weather such as drought and storms, vegetation management is becoming ever more important. Inspections and forecasting of vegetation is key to allow effective mitigation of these complex risks. Determined to ensure a safe and reliable network of lines, utility vegetation management is on top of mind, agenda, and budget, for utilities’ transmission and distribution departments. When managing vegetation, electric utilities take into account different vegetation encroachment risks on and around the rights-of-way (ROW). Two primary categories of encroachment that occur on and adjacent to power lines’ ROW are grow-in and fall-in. Proper vegetation management includes understanding grow-in and fall-in risks for every mile. On ROW but also on the land adjacent to ROW. Identification and prioritization of high-risk areas help correctly plan and evaluate vegetation maintenance and look into where and when encroachments might occur in the coming month, season, and year. Data is an integral part of all stages of the vegetation management process. This process starts with gathering and structuring available data. Understanding the state of the vegetation is step two and unveils the most important risk areas. With these maps in place companies can start to plan and execute vegetation maintenance. Continuously monitoring and reporting on the status and trends of these risks is not only key to confirm compliance but also to evaluate and adapt the current vegetation management strategy. This flywheel of vegetation management is complex, data-heavy, and often brings up various challenges to overcome. The world of vegetation management is evolving. Where helicopters and planes are widely used to inspect lines, the industry is still only scratching the surface of the potential of satellite data and Artificial Intelligence in vegetation management processes. The recent shift in quantity and quality of data comes with significant opportunities in downstream analytics. This fast-growing technology comes with opportunities to rethink vegetation management for utilities. The combination of satellite data and artificial intelligence allows for frequent, up to date insight into the status of vegetation around the full power line network. Applying AI to satellite data facilitates to focus on the right areas. Where satellite data gives an up-to-date and cost-effective view on the different grow-in and fall-in risks, there is the opportunity to leverage and combine different data sources in an efficient way. Combining satellite data strategically with drone imagery, LiDAR, or even inspections and other ground data, allows for a complete view of vegetation risks throughout the entire network. Information about the quality, quantity, distribution and forecasted state of vegetation can be extracted from these data sources. This is crucial input for optimizing trimming cycles and reporting on the most important key performance indicators that drive reliability and safety of the grid. Vegetation management is a complex flywheel with a variety of challenges. Understanding and leveraging the available data allows companies to get grip on social, environmental and economical risks. Challenge for society, economy and environment
Vegetation and power lines: grow-in and fall-in risks
What is missing from the equation?
Filling the data gaps — By combining satellite data and AI
Pinpointing risks by optimizing and combining data sources