AVA – Energy efficiency

AI models and machine learning predict network traffic and adjust shutdown times dynamically to extend savings windows compared to static schedules, avoiding any degradation of network performance. Supervised learning permanently adjusts predictions based on the latest load and network performance feedback. The AI solution enables differentiated energy saving plans for different areas such as rural or urban. The result is a coherent energy control that dynamically adapts energy consumption to traffic levels while maintaining a premium user experience. We have seen that AI-based solutions achieve two to five times more savings than non-AI systems that perform temporary shutdowns based on fixed schedules.

Dynamically adjusts the azimuth and elevation angle of antennas to reduce energy consumption further at given capacity and coverage requirements. Due to full automation there is no need for personnel to go to the station to adjust the antenna.

Hardware can continue to use power even when it’s not in use unless it’s physically shut off. Hard power saving control makes sure equipment that isn’t needed is fully shut down, which can further increase energy savings by up to 50%. With the accurate predictions of the AI engine the unplugged equipment is powered up right in time when it is again needed.

Telco AI analytics benchmarks energy trends and spots anomalies in the performance of historically “invisible” passive equipment such as batteries or air conditioners that could be draining energy and need to be reconfigured or replaced. Drawing from sources including radio networks, connected devices, weather data, asset databases, energy bills and alarms, Nokia AVA for Energy Efficiency uses advanced analytics to identify patterns and trends and provide benchmarks. This data feeds into a dashboard that displays anomalies such as faulty equipment, leakage or theft.

Intelligent Fresh Air Ventilator exchanging hot and cold air inside and outside the compute room and intelligent air conditioning can massively reduce the operating time of cooling systems throughout the day. This can lead to a 70% reduction of cooling costs which the major energy cost driver of radio sites.

AI models simulate the results of proposed changes to calculate the impact on network energy efficiency and CO2 emissions in advance. The system can make recommendations to correct, upgrade or modernize, and offers advanced simulation capabilities, so you can see how much energy you’ll save by implementing proposed changes.

As software based overlay energy management solution Nokia AVA for Energy minimizes the power consumption of RAN equipment across all layers for all major vendors. There is no dependency on vendor specific hardware.