AI-powered Energy Management

AI and advanced data analytics to optimize energy consumption

Energy Infrastructure Operations

Using AI and data analytics, Energy Infrastructure Operations creates energy efficiencies on the radio network. It not only addresses site-related energy savings, but also operational efficiencies to enable less site visits to be performed, ultimately resulting in CO2 emission reduction across multiple layers. Integrated into the Ericsson Operations Engine – the company’s AI-based, data-driven approach to managed services – the new solution enables service providers to reduce OPEX and CO2 emissions from their networks while maximizing site availability.

For many operators, energy consumption has historically been one of the highest operating costs, constituting between 20 – 40% of network operation OPEX. With EIO we are able to achieve efficiencies on reducing energy spent including grid and fuel costs, reduce site visits, maintenance and passive infrastructure expenses, reduce energy related outages and improve operational efficiency. Ultimately these result reduction of CO2 emissions as much as 5 metric tons on average per site per year.

Ruza Sabanovic, CTO, Telenor Group, says: “Telenor Myanmar has worked systematically over the past years to reduce energy consumption and lower carbon emissions. In last 2 years, our per site energy consumption has been reduced by 19%. We’ve taken another positive step by going live with Ericsson’s energy management solution on the Telenor Myanmar network. This enables us to use machine learning and data analytics to optimize energy use and maximize site availability, helping us to continue working towards our climate ambitions.”

Related content