Factory energy consumption monitoring system
Energy-saving solution for hydropower and steam meter data visualization
In the process of industrial transformation and intelligent manufacturing , the accurate collection, analysis, and optimization of energy consumption data have become key to reducing costs, increasing efficiency, and achieving sustainable development. To comprehensively understand the consumption patterns of water, electricity, steam, and other energy resources in factories and provide timely warnings of equipment anomalies, this solution, based on the DAQ-IOT technology framework and a professional data acquisition platform, builds an energy consumption monitoring system covering the entire process of "data collection - dynamic monitoring - intelligent analysis - early warning and operation and maintenance," helping factories achieve refined energy management.
1. System construction objectives
This energy consumption monitoring system takes "data-driven energy optimization" as its core goal and achieves the following three core tasks by building a standardized and intelligent monitoring platform:
Full-dimensional data visualization : Real-time collection of factory water, electricity, steam, and key equipment operating data, visually presenting energy consumption trends in the form of dynamic charts and dashboards, achieving three-level energy consumption transparency: "factory - wide-region - equipment"
Proactive prevention and control of abnormal risks : Establish energy consumption thresholds and equipment status early warning mechanisms to issue real-time alerts for abnormal conditions such as equipment offline and excessive energy consumption, reducing energy waste and production losses caused by equipment failures.
Continuous optimization of energy efficiency: Through historical data comparison, trend forecasting, and energy consumption ranking analysis, we identify energy waste points and provide data support for production scheduling adjustments and equipment energy-saving upgrades, ultimately reducing the factory's overall energy consumption and carbon emissions.
2. System Core Architecture and Technical Parameters
(1) Software architecture design
Adopting SCADA+ME+BS hybrid architecture, integrating the advantages of industrial-grade data collection and web/mobile access, it ensures the stability of data collection and the convenience of monitoring.
SCADA layer: Responsible for real-time data collection from underlying devices (water meters, electricity meters, steam meters, and PLC devices), supporting flexible setting of data collection intervals (adjustable from 1 minute to 24 hours) to ensure data timeliness and accuracy;
ME layer: It undertakes data processing and storage functions, realizes the cleaning, integration and backup of energy consumption data, and supports docking with the factory's existing production system to associate energy consumption and output data;
BS layer : Provides web and mobile access portals. Managers can view energy consumption trends, equipment status and alarm information anytime and anywhere through computers and mobile phones without installing dedicated clients.
( 3 ) Hardware configuration standards and field instrument information collection
To ensure stable operation of the system, the hardware configuration strictly follows industrial standards. The core equipment parameters are as follows:
Hardware Type | Model specifications | quantity | Functional use | Remark |
Industrial Computer | 10th Gen Core i7-10700 / 32GB RAM / 500GB SSD + 2TB HDD / 3060 discrete graphics card with 12GB VRAM | 1 set | As the system host computer, it is responsible for data processing, screen display and command issuance |
|
monitor | 21-inch industrial-grade monitor | 1 set | Supporting industrial computer for on-site real-time monitoring |
|
Input devices | keyboard and mouse set | 1 set | Industrial computer operation input |
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switch | Multi-port industrial switches | 1 set | Realize network communication between underlying acquisition equipment and industrial computers |
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Energy meters (water, electricity, gas, etc.) and terminal equipment corresponding PLC and other information collection required on site
(3) System function modules
Data acquisition and storage module
Covering three types of energy media, water, electricity, and steam, as well as key production equipment, it supports real-time collection of energy consumption data (such as accumulated kWh and instantaneous power kW) and equipment operating parameters (such as temperature and pressure);
The data is automatically stored for up to 3 years and can be downloaded in Excel format to meet the needs of energy consumption audits and historical data tracing. It has a data backup function and can be quickly restored through backup files in the event of system abnormalities to ensure that data is not lost.
Dynamic monitoring and visualization module
The main page uses a 2D dynamic screen design and supports three levels of drilling down: "Energy Overview --- Regional Energy Consumption --- Single Device Energy Consumption", which can be displayed in grid format or carousel mode.
The core visual dashboard includes:
Energy consumption trend comparison dashboard: supports switching between the time dimensions of "today - this month - quarter - year", and can be compared with historical data for the same period to intuitively present energy consumption changes;
Carbon emissions dashboard: Calculates CO₂ emissions and standard coal consumption in real time, and simultaneously displays the rate of change in carbon emissions;
Device status matrix: displays the online/offline status of electricity meters and other data collection devices in real time, with offline devices automatically marked in red as a reminder.
Intelligent analysis and prediction module ;
Energy consumption ranking function: Generate energy consumption rankings by "equipment --- region --- time period" dimension, and identify high-energy consumption areas (for example, if the daily energy consumption of power room 1 and power room 2 is both 100kWh, it requires special attention);
Trend forecasting function: Short-term (1 hour to 24 hours) and long-term (1 week to 1 month) energy consumption forecasts, output forecast curves (such as forecast data 7621kWh, 6845kWh, 6234kWh, 5712kWh), to assist in production planning;
Ton consumption analysis function: associates energy consumption data with output data, calculates energy consumption per unit output every hour, and identifies abnormal operating conditions of "high energy consumption and low output".
Alarm and operation and maintenance module
Alarm types cover three categories: device offline, energy consumption exceeding the standard, and parameter abnormality, and support custom alarm thresholds (such as triggering an alarm when the power exceeds 100kW);
Alarm information is pushed to the web and mobile terminals in real time, including the device name, alarm location, and alarm time (such as "Device 11, Wuhan, 2021-01-01 20:00:00, device offline");
Provides guidance on alarm handling procedures, supports alarm record query and statistics, and facilitates analysis of high-frequency fault points.
3. Implementation and Acceptance Criteria
(I) Implementation process
Preliminary research stage: Field test the compatibility of existing hardware (such as switches and data acquisition instruments) with the software, confirm the communication IP and communication stability, and the factory provides energy and equipment-side communication configuration sheets;
Scheme design stage: issue an electronic version of the overall development effect plan, clarify the design details of the 2.5D dynamic display screen (combined with the production site layout), and start development after confirmation by the factory;
Development and debugging phase: Complete software module development, hardware installation, and system integration, focusing on testing data collection accuracy, screen smoothness, and alarm response speed;
Training and delivery phase: Conduct system operation and maintenance training for factory operators, and deliver system backup files, manuals (2 paper copies + 1 electronic copy) and related qualification documents.
(2) Acceptance criteria
Hardware acceptance: The equipment packaging box is not damaged, the electrical components are not worn or deformed, and the parameters of industrial computers, switches and other equipment are consistent with the technical specifications;
Functional acceptance: The data collection interval meets the set requirements, the trend comparison and ranking analysis functions are normal, the alarm response time is ≤ 1 minute, and the 2D screen display is clear;
Document acceptance: Provide complete certificate of conformity, warranty card, operating instructions (including abnormality handling, maintenance cycle table), and list of wearing parts (including brand, specifications, contact information, etc. );
Service acceptance: After training, operators can independently complete daily system operations, and are promised 24 months of free operation and maintenance, with no software usage and maintenance fees during this period.
IV. System Operation, Maintenance and Assurance
Daily maintenance: The factory regularly (once a month) checks the operating status of industrial computers and switches and cleans equipment dust in accordance with the instructions; data is backed up once a quarter to ensure data security;
Troubleshooting: When a system anomaly occurs, the factory can first try to restore it through the backup file; if the problem cannot be solved, the factory can respond and handle it promptly within 2 hours ;
Later expansion: The system can reserve water meters, electricity meters, steam meters and equipment-side collection interfaces, and provide technical support to ensure interface compatibility when new equipment is added later.
This solution utilizes standardized hardware and software configurations, comprehensive functional design, and rigorous acceptance criteria to establish a practical and scalable energy consumption monitoring system. Once operational, the system has effectively improved the factory's energy management efficiency, providing solid data support for green production and cost optimization, helping the factory achieve its sustainable development goals of cost reduction, energy conservation, and carbon reduction.
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