Collaboration is crucial with new analytics providers recruiting a broad network of metering partners focusing on inside-the-meter intelligence.
FREMONT, CA: Most use cases for smart meters were related to lowering utilities' non-revenue electricity through precise and automated meter reading when the concept first gained popularity. Technological advancements are altering this, with the development of new use cases and economic models linked to grid modernization. Utilities are using the growing amount of data from smart meters to improve staff management, billing accuracy, and automate grid services. Although investor-owned utilities receive the majority of the credit for the nation's smart grid development, it is significant to emphasize that midsized utilities have a strong willingness and ambition to make comparable investments in smart metering.
Utilities can improve customer services, accelerate the energy transition, and strengthen the resilience of grid networks against climate change thanks to grid automation, energy efficiency, digital marketplaces, demand analytics, load disaggregation, and customer segmentation. Utilities can now tailor services to individual consumers. For instance, if a consumer's home appliance is consuming excessive amounts of electricity, smart meter data can be utilized to offer advice for energy-saving measures.
Adoption of AI and machine learning
Energy efficiency and demand-side control solutions will drive global spending on smart meter analytics. Energy firms will increase their investments in machine learning- and artificial intelligence-based analytics to ensure the collection, processing, and application of smart meter data for DERs' real-time management and operation. For instance, grid network operators will have to use smart meter analytics to apply demand response to make sure EV charging does not burden the grid as the use of electric vehicles rises over the upcoming years.
Better data management
Although utilities struggle with swings and curtailment, which they may address by leveraging real-time status data about consumer usage to enhance plant performance, solar PV deployment also keeps growing. Digitization alone is no longer enough. Leading utilities are now using AI-powered, forward-looking analytics to alter their companies. Additionally, as the number of units grows and consumer energy usage patterns change, the amount of data utilities receive from smart meters is growing. Energy businesses must adopt sophisticated data management techniques and technologies, such as artificial intelligence (AI) and machine learning, for managing, analyzing, and using the data.