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Shaanxi Woxin Electromechanical Engineering Co., Ltd

  • E-mail

    908848989@qq.com

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    13279305858

  • Address

    Linyin Tianxia, No.1 Information Avenue, New Industrial Park, High tech Zone, Xi'an City, Shaanxi Province

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Commercial Complex Energy Loss Management System

NegotiableUpdate on 02/26
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Overview
The energy consumption management system of the commercial complex collects energy consumption data such as water, electricity and gas in real time by integrating sensors, intelligent instruments and edge computing equipment, and helps enterprises accurately identify energy consumption weaknesses, optimize energy consumption structure, and finally achieve energy conservation, consumption reduction and carbon emission control by combining visualization tools and AI algorithms.
Product Details

Commercial Complex Energy Loss Management SystemIt is a comprehensive energy management platform designed for industries, buildings, and transportation, with full process digitization as its core, covering energy data collection, analysis, optimization, and decision support. By integrating sensors, intelligent instruments and edge computing equipment, the system collects energy consumption data such as water, electricity and gas in real time, and combines visualization tools and AI algorithms to help enterprises accurately identify energy consumption weaknesses, optimize energy consumption structure, and ultimately achieve energy conservation, consumption reduction and carbon emission control.

working principle

Data collection layer:

Real time collection of analog signals such as current, voltage, and flow rate through intelligent instruments, sensors, and other devices, and conversion into digital signals for transmission to PLC or edge gateway.

Data processing layer:

PLC/edge computing equipment cleans, calculates and stores the original data to generate energy consumption reports and trend curves. For example, the system can calculate the unit production energy consumption of a certain device and compare it with historical data.

Analysis and decision-making level:

Based on AI algorithms and rule engines, conduct in-depth analysis of energy consumption data to identify energy-saving potential points. For example, the system can establish a mathematical model of energy consumption and production output through regression analysis to predict more optimal energy use solutions.

Control execution layer:

Automatically adjust equipment operating parameters (such as start stop, frequency adjustment) or trigger alarms based on decision results. For example, when the energy consumption of the air conditioning system is abnormal, the system can reduce the fan speed or switch to a backup device.

Commercial Complex Energy Loss Management SystemApplication field

industrial manufacturing

Monitor the energy consumption of production line equipment, identify high energy consuming processes, optimize process parameters (such as adjusting motor speed and heating temperature), and reduce unit product energy consumption.

Based on production plans, dynamically adjust energy supply strategies to avoid cost increases caused by differences in peak and valley electricity prices.

commercial building

Intelligent control of air conditioning, lighting, elevators, and other systems, automatically adjusting their operating status based on factors such as pedestrian flow and time, reducing ineffective energy consumption.

By implementing the household metering function, tenants are incentivized to participate in energy conservation and reduce overall operating costs.

public facilities

Hospitals, schools, and other institutions use systems to monitor heating, water supply, and other systems to prevent pipeline leaks and ensure stable operation of facilities.

Urban street light management achieves on-demand lighting through the system, adjusting brightness according to traffic flow and weather conditions to extend equipment lifespan.

data center

Real time monitoring of energy consumption of servers and cooling systems, optimizing equipment layout and cooling strategies, reducing PUE values (energy efficiency), and improving data center reliability.