Siemens Energy to conduct AI powered inspection of transmission assets in Germany.

by Jun 10, 2022

German grid operators Schleswig Holstein Netz AG and Bayernwerk Netz GmbH have chosen Siemens Energy to perform inspection of high voltage overhead power transmission lines stretching over 4000 km by utilizing computer vision aided by artificial intelligence (AI). Siemens Energy will examine transmission lines using a helicopter equipped with 19 cameras and 3D laser scanning sensors, capable of capturing 12000 images and performing detailed 3D scanning per km. The collected data will be analyzed by computer vision and AI algorithms to generate insights on the asset’s current condition and allow utilities to do predictive maintenance on assets where a malfunction is likely to develop. Following the same, many other utilities and energy providers have implemented or plan to implement AI to assess their assets and undertake predictive maintenance. Duke Energy, an American utility, used drones to perform AI powered inspection of their solar farms, which have over 3 million units spread across 500 acres, saving more than $74 million in costs and 385,000 man-hours. In the same line, Southern California Edison (SCE) has designed and launched an AI powered airborne remote sensing programme to assess transmission assets by drones. The SCE aims to inspect 20,000 transmission and distribution assets in high-risk locations in order to determine the root cause of the frequent failure situations. The application of AI is a significant advancement in power line inspection. The excellent data quality helps utilities to be more exact and cost-effective, as well as complete the examination more safely. Moreover, asset inspection and predictive maintenance is not only domain where AI is assisting the utilities. The utilities including Electric Ireland (Ireland), Duke Energy (USA), TEPCO (JAPAN), NV Energy (USA), Consolidated Edison (USA), Eversource Energy (USA), AEP (USA), San Diego Gas & Electric (USA), and NYPA (USA) are also activity participating in collecting data through smart meters and assisting their costumers to optimize their electricity usage with the help of AI algorithms. These advancements provide an indication of how AI technology is influencing utilities to improve their efficiency and reliability, but it is still in the early stages of deployment, as in the coming years AI will be assisting utilities to optimize electricity prices through better trading, reduce customer churn, and predict the likelihood of winning customers.

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