Utilities Tech Outlook Weekly Brief
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To make data sets for model development and training available, research institutes are collaborating with utilities and the AI community. It is possible to use these data sets to improve predictive modeling, boost efficiency, and identify equipment problems that should be repaired or replaced.
FREMONT, CA: Companies seek to use all the data gathered through digital tools. Proper use of this data can have a significant impact on the success of firms. Due to the industry's reliance on technology, mobile devices, and the internet of things, utilities may find this particularly difficult.
In other industries, artificial intelligence has enormously affected this. Retailers have used it to assist them in deciding when to replenish, financial institutions have used it to provide individualized customer experiences, and NGOs have used it to maximize fundraising. Like other industries, the energy and utility sector may maximize productivity and streamline processes by utilizing AI.
The sector may employ AI to manage resources, store energy, and boost productivity through predictive analytics. The industry will become more productive and efficient by automating data collection, storage, and management.
The Power of Predictive Analytics
To make data sets for model development and training available, research institutes are collaborating with utilities and the AI community. It is possible to use these data sets to improve predictive modeling, boost efficiency, and identify equipment problems that should be repaired or replaced.
Through Power BI, a collection of business analytics tools, Microsoft has also created a way to assist power companies in improving their predictive analytics. According to the company, data-driven insights will improve and transform sustainable energy management, generating value for producers, suppliers, distributors, and consumers.
Utility companies can predict and plan for customer demand using data analytics tools such as Power BI. Enhanced equipment and resource management in energy production and distribution channels can allow Microsoft to transform reactive decisions into predictive and preventive ones.
Boosting energy efficiency with AI
New-energy storage systems typically last 4 hours or less to meet peaking capacity and other needs. As storage is deployed in the future to replace conventional generation with higher capacity factors, to absorb renewables over long periods, and to support resilience during severe weather events, longer duration storage may be necessary.
