Predictive Analytics for Vegetation Management within Power Derived from Data Collected during Pruning Activities: A Strategy Approach to Enhancing Sustainability and Operational Efficiency in the Energy Sector

Advancements in data-driven technologies, particularly in advanced analytics and artificial intelligence, have become essential for improving service quality, operational efficiency, and sustainability across various sectors, including utilities. This study outlines the development of an analytical tool to support the planning and scheduling of vegetation management in electricity distribution networks. The main goal of this tool is to enhance maintenance fleet performance, optimize resource allocation for tree trimming, and reduce the risk of service disruptions caused by vegetation contacting electrical conductors. The presence of trees near distribution lines is a common cause of service interruptions. To address this issue, a new tool has been developed that enables simultaneous analysis across all areas where the network infrastructure is operated and maintained. This tool provides an integrated view of vegetation behaviors across the territory. The development of this tool followed the CRISP-DM (CrossIndustry Standard Process for Data Mining) methodology, which served as the foundation for this study. Additionally, analytical techniques were implemented in a Data Lakehouse environment to improve analysis effectiveness [1]. This strategic approach incorporates geospatial data processing and species-specific growth rates, enabling more accurate predictions of how vegetation dynamics will change over time. The system is designed to accurately identify the optimal timing for interventions in each tree or geographical sector using a prioritized alert scheme organized into four levels. The input data includes georeferenced locations, types of activities performed, pruning dates, the scientific names of the treated species, and other relevant information. Continuous updates ensure the analysis remains current and allow adjustments as vegetation changes and new field activities are conducted. The tool acts as a strategic support system for managing vegetation in the electrical distribution network.