Energy-saving design and implementation in metro weak current systems: a case study of the Kunming metro system

AbstractWith the accelerated urbanization in China, along with the growing scale of the metro transportation network, the energy consumption of metro systems continues to increase. To face the tough challenge of climate change, China has put forward the goal of peak carbon emissions by 2030 and achieving carbon neutrality by 2060. Energy consumption has become a serious burden for metro operation companies, since 10.2% of the total operational budgets is spent on electricity. Thus the development of methods to realize energy saving and emission reduction has become a major challenge for metros. In this study we conduct an in-depth research and analysis on metro energy load classification and energy management, focusing in particular on the design and usage of power supply systems for metro weak current electromechanical systems, including tunnel fans, station air conditioners, station escalators, automatic ticketing equipment, screen doors, drainage pumps, sewage pumps, platform doors, communication systems, signals, integrated monitoring systems, automatic ticketing and various lighting equipment and facilities. It is proposed that the five weak current systems, namely platform doors, communication systems, signals, integrated monitoring and automatic fare collection, should adopt a backup power supply. In order to ensure the reliable operation of all weak current systems in the station, the traditional decentralized power supply mode is changed to a centralized power supply and uninterruptible power supply (UPS) (1 + 1) parallel double-bus system. At the same time, combined with the data on equipment quantity, station passenger flow and station building floorage, the Boruta algorithm is used to filter out the equipment related to station weak current energy consumption, and a principal component analysis (PCA) algorithm is used to further reduce the dimensions of the filtered features to reduce the algorithm overhead of the subsequent quota analysis model. The XGBoost algorithm is used to establish a prediction model for station weak current system energy consumption. Analysis shows that there is a strong correlation between the energy consumption quota and the equipment quantity as well as station building floorage. By setting different metering instruments for power supply circuits, the main energy consumption data are collected to meet the requirements for graded metering of metro energy consumption, and then the energy consumption quota for the station weak current system is reasonably predicted. By adding metering instruments to the power supply circuits of different areas and equipment, the energy consumption of the weak current system can be measured and monitored in different grades. The combination of the energy management platform and energy consumption quota provides the basis for energy management of each energy-consuming unit, and ultimately realizes energy saving and reduced consumption.