AI can offer invaluable insights from the data generated by various sensors connected to the smart utility grid components.
FREMONT, CA: A smart grid analyzes supply-demand constraints and operates in an efficient way. It represents the advancements over the traditional grid systems as it ensures better utilization of energy and faster restoration after power blackouts. The above functions are carried out with the help of interconnectivity provided by a number of sensors attached to the various utility equipment. Considering the amount of data generated as a result of interaction among the smart utility devices, artificial intelligence (AI) can’t be kept away for too long.
AI has the ability to access and process massive amounts of data sets, thereby extracting meaning from the unstructured data. Thus, it is possible to effectively utilize the utility data generated even at remote places and use it to enhance the overall performance of the system. In the above context, integrated asset management (AMS) is one of the most useful applications of AI. AMS is an essential use case of AI as it allows sharing asset information across the organization. AMS also has significant impacts on reducing operational and maintenance costs for the utility sector.
Distributed energy source systems and renewable energy are also gaining grounds with the help of AI. Various energy companies are deploying AI to counter the growing imbalance in demand and supply. Coupled with other technologies such as cloud, big data, and the internet of things (IoT), AI can assist in the active management of smart grids by enhancing the accessibility of renewable energy sources.
AI can further increase the efficacy of the smart utility grids. It can analyze the data generated by various grid components and offer recommendations for optimized energy usage. Thus, AI must be considered as the world awaits clean and green energy.