COVID-19 crisis: Why cutting vegetation management costs is an urgent need
16th Jun, 20
A new report released by the International Energy Agency (IEA) has revealed that the global energy market is experiencing its biggest shock in 70 years. There has been a steady decline in the demand for energy as a result of the COVID-19 pandemic. Based on the analysis of 100 days of data, the IEA projects that global energy use in 2020 will fall by 6% - seven times the decline after the 2008 global financial crisis.
The demand for electricity is also set to see a 5% decline in 2020, the largest drop since the Great Depression in the 1930s. In light of this unprecedented impact due to COVID-19, the energy sector is looking to reduce costs and has resorted to extreme measures to sail through these tough times. A new analysis of US Department of Labor unemployment data indicates that almost 600,000 clean energy industry workers have lost their jobs since the spread of the coronavirus forced an economic shutdown.
These statistics clearly indicate that power utilities have been hit hard too. In this scenario, cutting costs seem to be an urgent and immediate need. Is there a way to reduce costs without having to downsize the workforce? Let’s find out how.
Reduce vegetation management costs by 20% and improve reliability by 15%
According to Power Grid, vegetation management is frequently the single largest line item in annual operating budgets, exceeding $100 million annually in many larger utilities. In California alone, utilities spend about $1 billion annually on vegetation management. While it is vitally important to ensure that reliability is not compromised, it is possible to cut down on the costs incurred in vegetation management with the help of cutting-edge technology. It is possible to cut down vegetation management budget by 20% and improving reliability by 15% with the help of Satellite Intelligence and AI. Read on.
Most power utilities have been using traditional and manual procedures of vegetation management. From fixed, routine and unoptimized annual trim cycles to poor efficiency in terms of unintelligent maintenance and no visibility of hazards or risks, the present system of vegetation management is marred with challenges. Now is the time to upgrade the archaic methods of managing vegetation along power lines and use technology to make it more intelligent and data-driven.
The adoption of technologies like Artificial Intelligence and Remote Sensing presents an exceptional opportunity for the energy sector. The right combination of these technologies could lead to financial gains far greater than what each technology would deliver on its own. And the right time to act is now. This tech upgrade of existing vegetation management practices will not only help reduce costs for power utilities, but it will also save jobs in these trying times.
Transforming Utility Vegetation Management with Satellite Intelligence and AI
The ultimate goal of vegetation management is to prevent hazards and risks along transmission lines proactively, not reactively. Satellite imagery and Artificial Intelligence can empower utilities with these capabilities and transform the vegetation management scenario. Let’s find out how:
The use of high-resolution multispectral satellite images combined with predictive analytics is capable of providing increased visibility on the growth of vegetation around transmission and distribution grids. This can help in predicting the growth of trees, planning cycle trims and prioritizing risk-prone maintenance before anything else. AI models can use the data to quickly and accurately process huge and complex inputs from geo-spatial and time-based datasets, helping utilities monitor the entire service territory for vegetation overgrowth and identify power line infringement. This system uses rigorous AI models to identify vegetation management activities, assess risk, and measure task completion for compliance and reliability.
With the help of satellite data, the AI models use location, weather, soil and tree species to identify and classify vegetation management tasks. These tasks are then prioritized as routine, preventive, or on-demand tasks. A mobile app and a web dashboard are user access points that help stakeholders assign and execute tasks on the ground. This model optimizes future decision-making by combining field inputs, vegetation data, and pre-trained models for growth rate, trim cycles and labor hours.
Here’s how AI and satellite-powered models can transform vegetation management for power utilities:
- Identification of risks
Utilities can prioritize tasks and spend every dollar wisely with the help of a satellite-driven model as it helps them identify vegetation risks and reliability impact at any spot, any time.
- Species growth of individual trees
Since each tree species has a different growth pattern, it is possible to keep track of the species growth in a specific geolocation. This means there’s no need to trim 20-mile circuit lengths together. Trim and pay for only what’s needed, while leveraging geo-clustering for efficiency.
- Plan T&D ops with complete visibility
AI models can predict vegetation growth up to 5 years in advance. This will enable utilities to create plans for cycle and mid-cycle trims, hazard tree removals and herbicides well in advance and offer complete visibility of assets and vegetation growth.
- Empower field operators with a user-friendly mobile app
A user-friendly mobile app will help vegetation operators report, prioritize and execute from the field, increasing their productivity and digitize vegetation workflow end-to-end.
- App-based contractor management
Utilities get a single platform to plan, collaborate with contractors and track results. A satellite-based job quality measurement allows them to remotely monitor and inspect trim jobs too.
AiDash is a leading AI-first SaaS company that has transformed vegetation management for several power utilities in the US. AiDash Intelligent Vegetation Management System (IVMS) is a dedicated SaaS product for vegetation management powered by Satellite and AI. IVMS utilizes high-resolution multispectral and SAR data from the world’s leading satellite constellations, to make timely predictions for vegetation management and operations activities. To learn more, log on to www.aidash.com. You can also mail us at firstname.lastname@example.org to request a demo.