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RESISTO Project: Safeguarding the Power Grid from Meteorological Phenomena

Jacob Rodríguez-Rivero, David López-García, Fermín Segovia, Javier Ramírez, Juan Manuel Górriz, Raúl Serrano, David Pérez, Iván Maza, Aníbal Ollero, Pol Paradell Solà, Albert Gili Selga, José Luis Domínguez-García, A. Romero, A. Berro, Rocío Domínguez, Inmaculada Prieto

Abstract

The RESISTO project, a pioneer innovation initiative in Europe, endeavors to enhance the resilience of electrical networks against extreme weather events and associated risks. Emphasizing intelligence and flexibility within distribution networks, RESISTO aims to address climatic and physical incidents comprehensively, fostering resilience across planning, response, recovery, and adaptation phases. Leveraging advanced technologies including AI, IoT sensors, and aerial robots, RESISTO integrates prediction, detection, and mitigation strategies to optimize network operation. This article summarizes the main technical aspects of the proposed solutions to meet the aforementioned objectives, including the development of a climate risk detection platform, an IoT-based monitoring and anomaly detection network, and a fleet of intelligent aerial robots. Each contributing to the project's overarching objectives of enhancing network resilience and operational efficiency.

RESISTO Project: Safeguarding the Power Grid from Meteorological Phenomena

Abstract

The RESISTO project, a pioneer innovation initiative in Europe, endeavors to enhance the resilience of electrical networks against extreme weather events and associated risks. Emphasizing intelligence and flexibility within distribution networks, RESISTO aims to address climatic and physical incidents comprehensively, fostering resilience across planning, response, recovery, and adaptation phases. Leveraging advanced technologies including AI, IoT sensors, and aerial robots, RESISTO integrates prediction, detection, and mitigation strategies to optimize network operation. This article summarizes the main technical aspects of the proposed solutions to meet the aforementioned objectives, including the development of a climate risk detection platform, an IoT-based monitoring and anomaly detection network, and a fleet of intelligent aerial robots. Each contributing to the project's overarching objectives of enhancing network resilience and operational efficiency.

Paper Structure

This paper contains 13 sections, 4 figures.

Table of Contents

  1. Introduction
  2. Objectives
  3. Project innovations:
  4. Proposed solution
  5. Electrical resilience platform: GridWatch
  6. Automatic detection of operation temperature anomalies using thermal imaging
  7. System architecture
  8. Thermal anomalies detection system.
  9. Fleet of Drones
  10. Discussion
  11. Conclusions
  12. Acknowledgments.
  13. Disclosure of Interests.

Figures (4)

  • Figure 1: GridWatch platform components and external interactions.
  • Figure 2: Thermographic data acquisition architecture.
  • Figure 3: Thermal anomalies detection system diagram.
  • Figure 5: Multi-drone system architecture with the ground segment composed by the Ground Control Station (GCS) and the mission planner module at the bottom, the main software modules on-board the drones in the middle and the drones and their payloads on top.