03,20,2026 18views
【Smart CityOnline product review】In the new stage of deep implementation of the "dual carbon" strategy and the green, intelligent, and high-quality development of the urban rail industry, Zhongkong Information relies on its deep cultivation of technology accumulation and digital solution experience in the urban rail field to launch a smart urban rail energy management software. The software is centered around "data-driven, precise analysis, and green operation", deeply integrating with the Internet of Thingsbig dataBy utilizing cutting-edge technologies such as large-scale modeling and intelligent analysis, we aim to create a city rail energy management and control center that integrates real-time energy consumption monitoring, comprehensive energy consumption statistics, in-depth energy consumption analysis, precise energy efficiency evaluation, intelligent energy diagnosis, and intelligent energy assistance. This will effectively solve prominent problems such as insufficient visualization of energy consumption, inaccurate energy efficiency analysis, and lack of control over energy consumption in city rail stations, promote the transformation of city rail operation from "extensive energy consumption" to "refined energy conservation", and build a green and low-carbon energy management digital base for smart stations.
Full dimensional perception, real-time monitoring to grasp the dynamic pulse of energy consumption
The smart urban rail energy management software breaks down the data barriers of various energy consuming equipment such as high and low voltage distribution, ventilation and air conditioning, elevators and escalators, lighting systems, and water supply and drainage in urban rail stations, realizing plug and play access to all types and categories of energy consuming equipment such as electricity, water, and gas, and constructing a global, full-time, and comprehensive energy consumption perception network. The software creates a visual energy consumption monitoring screen, which presents real-time energy consumption data of various systems, regions, and devices in the form of dynamic charts, data dashboards, equipment ledgers, etc. Based on the time series analysis and anomaly detection capabilities of AI models, the system can automatically identify atypical energy consumption patterns such as sudden increases in energy consumption and abnormal nighttime electricity usage, achieving second level updates of energy consumption data and instant warnings. Compared with the traditional manual meter reading mode, the efficiency has been improved by more than 90%. Operations and management personnel can fully grasp the energy consumption dynamics of the entire station without leaving their homes, truly achieving "visible, tangible, and manageable" energy control.
Multi dimensional statistics, in-depth analysis to explore the value of energy consumption data
The software builds a multidimensional and refined energy consumption statistics system, supporting automatic energy consumption data statistics and report generation by time (hour, day, week, month, year), area (station hall, platform, equipment area, entrance and exit), system (environmental control, lighting, power), and equipment (single escalator, single air conditioner). It supports one click export of standardized energy consumption reports, reducing manual statistics workload by more than 80% and improving data accuracy to 99%. The software is equipped with a professional energy consumption analysis model, which conducts in-depth energy consumption trend analysis, year-on-year and month on month analysis, energy consumption proportion analysis, and load characteristic analysis through big data mining, multimodal data fusion, and AI big model analysis technology. Based on the semantic understanding ability of large models, the system can automatically generate energy consumption analysis and interpretation reports, convert complex data analysis results into intuitive business insights, accurately identify station energy consumption patterns, high energy consuming links, and energy-saving potential points, improve analysis efficiency by 70%, and upgrade energy consumption analysis from "simple statistics" to "value insights".
Accurate evaluation, intelligent diagnosis, and targeted energy management pain points
Based on the massive energy consumption data and industry benchmark indicators in the urban rail industry, the software builds a standardized and customized energy efficiency evaluation system. It can accurately evaluate the overall energy efficiency of the station, the energy efficiency of each system, and the energy efficiency level of individual equipment according to different station types, operating scales, and passenger flow characteristics. It automatically generates quantitative energy efficiency evaluation reports, clearly locates energy efficiency gaps, and provides clear direction for energy-saving transformation. The software is equipped with intelligent energy consumption diagnosis algorithms and introduces AI models to conduct in-depth analysis of the correlation between equipment operating parameters and energy consumption data. It automatically diagnoses energy consumption anomalies such as inefficient operation, idle waste, unreasonable parameter settings, and pipeline leakage of station equipment. Based on the knowledge reasoning ability of large models, the system can not only accurately locate the root cause of problems and evaluate energy-saving potential, but also intelligently generate diagnostic conclusions and optimization suggestions, and automatically classify problem levels. The diagnostic accuracy is over 85%, and the time for problem detection has been reduced from several hours to 5 minutes, achieving a full process loop of "automatic problem detection, precise root cause localization, risk grading warning, and intelligent suggestion generation".
Intelligent energy utilization assistance, dynamic regulation to achieve precise matching of energy supply and demand
The software deeply integrates multiple sources of information such as passenger flow data, meteorological data, equipment operation data, and historical energy consumption data to build an accurate energy consumption prediction system. Based on the multimodal data fusion and long-term forecasting capability of AI large models, the system can predict energy demand in different time periods and regions in advance according to real-time passenger flow and outdoor temperature and humidity changes, with an energy load prediction accuracy of over 95%. The system introduces intelligent question answering capabilities driven by large models, allowing operators to query energy consumption data and obtain diagnostic reports through natural language interaction. The query response time has been reduced from an average of 3 minutes to less than 10 seconds, significantly lowering the threshold for system use.
Ecological compatibility, flexible expansion, adapted to the diverse operational needs of urban rail transit
The software adopts a modular architecture and open design, supporting on-demand expansion of functions and continuous algorithm upgrades. It can customize energy management function modules according to the operational needs of different cities' subways and stations, and adapt to full scenario applications from single station management to centralized energy control at the network level. The software provides standard API interfaces and SDK development packages, which can seamlessly integrate with third-party urban rail operation platforms and intelligent energy consuming devices, achieving deep collaboration between energy management and station operations, passenger services, and equipment maintenance. From single station energy conservation to low-carbon network, from data perception to intelligent control, the central control information intelligent urban rail energy management software drives the upgrade of urban rail energy management mode through technological innovation. It not only provides a core lever for urban rail operation enterprises to reduce energy consumption costs and achieve the "dual carbon" goal, but also injects green momentum into the construction of smart urban rail. In the future, Zhongkong Information will continue to deeply cultivate the field of green and intelligent urban rail transit, continuously optimize energy management algorithms and scene adaptation capabilities, and help China's urban rail transit move towards a new journey of high-quality development that is green, low-carbon, intelligent, and efficient.
