Base Station Rectifier Efficiency Mapping Under Dynamic Cell Load
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Solution Overview
Problem
The efficiency of rectifiers in base stations is not always optimal due to dynamic cell loads, leading to suboptimal power consumption and potential power outages during high traffic peaks.
Innovation Solution
An apparatus and method that involve receiving measurement information from a power supply unit about rectifier efficiency and cell load measurements, determining a mapping between cell load and rectifier efficiency, and adjusting the cell load or power supply unit configuration to maintain optimal rectifier efficiency and prevent power outages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the rectifier operates under dynamic cell loads, then the base station can handle varying traffic demands, but the rectifier efficiency becomes suboptimal and power consumption increases
Solution Approach 1:
The system dynamically adjusts the operating point of the rectifier by modifying cell load based on real-time efficiency measurements. The network controller continuously monitors rectifier efficiency and adjusts the cell load to keep the rectifier operating in its optimal efficiency range, thereby adapting to varying traffic demands while maintaining energy efficiency.
Solution Approach 2:
The system implements a feedback mechanism where the network controller receives efficiency measurements from the rectifier, determines the optimal operating point, and adjusts the cell load accordingly. This closed-loop control ensures that the rectifier operates at peak efficiency while still meeting traffic demands through dynamic load management.
2Loss of energy
If the rectifier efficiency is optimized for specific operating conditions, then energy consumption is minimized, but the system cannot adapt to high traffic peaks causing power outages
Solution Approach 1:
The system transitions from static efficiency optimization to dynamic operation by continuously adjusting cell load based on real-time efficiency measurements. This allows the rectifier to maintain optimal efficiency across varying operating conditions including high traffic peaks, thereby preventing power outages while minimizing energy consumption.
Solution Approach 2:
The system changes the operating parameters of the rectifier by adjusting cell load to match the optimal operating point determined from efficiency measurements. This parameter adjustment enables the rectifier to adapt to different traffic conditions while maintaining peak efficiency and preventing power supply failures.
3Productivity
If the cell load is increased to meet high traffic demand, then service capacity is improved, but rectifier efficiency decreases leading to higher power consumption
Solution Approach 1:
The system dynamically balances service capacity and power consumption by adjusting cell load based on real-time rectifier efficiency measurements. When traffic demand increases, the system intelligently modulates the cell load to maintain rectifier operation within the optimal efficiency range, thereby providing improved service capacity without proportionally increasing power consumption.
Solution Approach 2:
The system optimizes the relationship between service capacity and power consumption by changing the cell load parameter to match the rectifier's optimal operating point. This allows the network to handle high traffic demands while maintaining peak rectifier efficiency through dynamic parameter adjustment.
4Loss of energy
If manual optimization of rectifier operating point is performed, then energy efficiency is improved, but the system lacks adaptability to dynamic traffic conditions
Solution Approach 1:
The system replaces manual optimization with an automated feedback mechanism. The network controller continuously receives efficiency measurements from the rectifier, determines the optimal operating point, and adjusts the cell load accordingly. This automated feedback loop maintains high energy efficiency while providing full adaptability to dynamic traffic conditions.
Solution Approach 2:
The system enables self-service optimization where the rectifier and network controller work together autonomously. The rectifier provides efficiency measurements, the controller determines optimal operating points, and automatically adjusts cell load without manual intervention. This self-service mechanism ensures continuous energy efficiency adaptation to changing traffic conditions.
Data Source
AI summary
Disclosed is a method comprising receiving, from a power supply unit of a base station, measurement information for one or more parameters related to an efficiency of a rectifier of the power supply unit; receiving cell load measurements indicative of a cell load of the base station; determining, based on the measurement information and the cell load measurements, a mapping between the cell load and the efficiency of the rectifier; and adjusting, based on the mapping, at least one of: the cell load of the base station, or one or more configuration parameters of the power supply unit.