Two-Stage Robust Optimization of 5G Base
During the intraday stage, based on day-ahead predicted data of renewable energy output and load and errors, the model adjusts the backup
The power consumption of a single 5G station is 2.5 to 3.5 times higher than that of a single 4G station. The main factor behind this increase in 5G power consumption is the high power usage of the active antenna unit (AAU). Under a full workload, a single station uses nearly 3700W.
1. Introduction 5G base station (BS), as an important electrical load, has been growing rapidly in the number and density to cope with the exponential growth of mobile data traffic . It is predicted that by 2025, there will be about 13.1 million BSs in the world, and the BS energy consumption will reach 200 billion kWh .
The 5G BS power consumption mainly comes from the active antenna unit (AAU) and the base band unit (BBU), which respectively constitute BS dynamic and static power consumption. The AAU power consumption changes positively with the fluctuation of communication traffic, while the BBU power consumption remains basically unchanged,, .
The data here all comes from operators on the front lines, and we can draw the following valuable conclusions: The power consumption of a single 5G station is 2.5 to 3.5 times higher than that of a single 4G station. The main factor behind this increase in 5G power consumption is the high power usage of the active antenna unit (AAU).
It also provides a way to solve the problem of 5G energy consumption. This paper puts forward a scheme to install photovoltaic energy storage system for 5G base station to reduce the power supply cost of the base station, compares it with the energy consumption cost of 5G base station in different situations, and analyzes the economy of the scheme.
In 2019, the 5G Power solution won ITU's Global Industry Award for Sustainable Impact. For operators, it provides a replicable power solution that can slash site retrofitting costs. 5G Power is based on intelligent technologies like peak shaving, voltage boosting, and energy storage.

During the intraday stage, based on day-ahead predicted data of renewable energy output and load and errors, the model adjusts the backup
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