Artificial intelligence (AI) is being used in utility applications. While AI is nowhere near a new phenomenon, modern IT systems with superior machine learning algorithms are revolutionizing the sector by bringing analytical skills to potentially enormous, diverse datasets for modeling and administration in near real-time.
Combine this with other current IT advances such as the cloud service, which can provide immediate access to AI capabilities, and edge computing, which provides data handling and latency improvements, and it is no wonder that AI is now increasingly used in electricity sector and commercial utility use cases.
In other circumstances, it is about detecting anomalies in statistics, which is employed in services such as cybersecurity, asset management and other related services. In others, such as meteorology and renewable sources output modeling, it is about identifying trends found in history in order to properly predict future developments.
AI is predicted to drive autonomy in the future, particularly with the rise of 5G and subsequently 6G networks, as well as continued IT innovations, in which technologies such as drones and driverless automobiles, and perhaps the future decentralized electric grid, can run without human interference.
In one case involving the application of renewable sources of energy, NVIDIA collaborated with Zenotech to predict the power generation of massive offshore wind farms. They account for the complex wind movements that develop near wind turbines, as well as the various wind speeds and angles that happen in their wake as they collide.
In another case, Siemens Energy is utilizing NVIDIA’s inferencing capabilities to optimize power plants around the world through analytics for predictive servicing and, eventually, automated power stations.
Opportunities in the electricity sector range from environmental management to remote supervision and inspection of vulnerabilities along transmission lines, all of which can boost utilities’ operational and management practices.