Extreme weather events are increasing in severity and frequency and exposing utility grids to new and unprecedented threats. We have recently seen Hurricane Laura take out 219 transmission lines and 292 substations across the US while the UK Met Office has revealed that extreme weather is expected to exceed conditions that have already been experienced in the country.
As hazards to power grids grow more numerous, visibility over them has simultaneously become more difficult due to the switch towards renewable power. The decentralization and localization of power through small wind and solar generators, peer-to-peer energy markets, and community power-sharing has led to a fragmentation of energy data and more assets at the edge of the network. While this diversification has its benefits, when grids become decentralized and dispersed, it also makes it difficult to develop a single, up-to-date “Ëœrisk picture’ for local and national networks.
Smart grids have also pushed data to the edges of a network with much real-time grid data held in local sensors or field worker mobile devices. Many grid operators use legacy, centralized Geospatial Information Systems (GIS), proprietary apps, or even paper maps which cannot easily interface with all the sensors and mobile devices in the field. Inflexible, inaccurate network maps delay identification of vulnerabilities or blackout locations and make it difficult for field workers to upload important new network data. This means power companies increasingly lack an accurate and up-to-date view of both grid damage and potential hazards.
This presents an obstacle to effective risk management, which requires utilities to go beyond a reactive “Ëœfire-brigade’ approach to weather hazards and instead proactively predict and prevent threats to create resilient grids. Power companies that have long experienced extreme weather- for example, Japan’s power giant TEPCO – have been harnessing its abundant data to create more resilient and smart grids. The company has been able to weather damage from storms including Typhoon Faxai by harnessing a flexible geospatial data platform that can integrate live network data from automated sensors and smartphones or tablets used by field engineers. This provides a rich, real-time picture of both current damage or degradation and future hazards and threats.
Data from local sensors or technicians in the field can be used to track the real-time position and condition of assets and identify the site and source of potential threats, enabling more proactive hazard prevention and effective actions to mitigate them. When Typhoon Faxai hit Tokyo in September 2019, the system enabled the utility to rapidly view and act upon mission-critical network information such as vulnerable or affected areas.
Using a geospatial dashboard with a Google Maps interface, technicians and construction teams can quickly find and reach unfamiliar locations most in need of restoration. This approach has important implications for network operators in the US: By leveraging the value of open data they have enhanced visibility of grid hazards.
Utilities are already sitting on a rich and abundant array of “field sourced” as-built network data from their engineer teams and IoT devices such as Advanced Metering Infrastructure (AMI), but this data is not being captured and visualized. Utilities need to move away from “Ëœclosed’ complex GIS towards open and decentralized geospatial dashboards that can draw on live data from all locations to help anticipate and avert hazards in advance. These systems need to be able to integrate with proactive network management and other sensors, as well as mobile apps used by field workers. This will give them a live view of the situation on the ground to inform rapid and effective disaster resilience.
Democratizing and sharing geospatial data allows field crews to continuously correct and update network data to constantly improve data accuracy and mitigate risk. This allows grids to become progressively more visible and resilient. The decentralization and digitalization of utility grids means that utilities face a complex landscape in a constant state of flux. Whether facing climate or operational threats, the right geospatial strategy will allow them to create an accurate, comprehensive, and accessible view of their network that will bring massive benefits for the entire organization.