How can industrial energy efficiency management systems change factories from energy consumers to energy-saving pioneers?

Introduction:

At present, as global energy demand continues to rise and the urgency of environmental protection becomes increasingly prominent, industrial enterprises are facing the dual pressure of soaring energy costs and strict carbon emission restrictions. How to cleverly respond, achieve efficient energy utilization, reduce production costs, and alleviate environmental pollution has become a core issue for enterprises to move towards sustainable development. The industrial energy efficiency management system, as a cutting-edge energy management tool, has tailored multi-dimensional energy management solutions for enterprises with its real-time monitoring sensitivity, in-depth data analysis capabilities, and intelligent optimization strategies.

How does Ankerui's EMS3.0 smart energy management solution change factories?

Acrel-EMS3.0, as an industrial energy management system, relies on its excellent data collection efficiency, powerful data analysis capabilities, and flexibilityThe convenient deployment mode plays a crucial role in the field of industrial energy efficiency management. The industrial energy efficiency management system can not only achieve refined and intelligent management of energy use, but also help enterprises optimize production processes, reduce energy consumption, and accelerate operational efficiency through a data-driven decision support system, thus steadily advancing on the path of green development.

1 What are the problems with traditional factory energy consumption systems?

Relying on manual meter reading:Traditional factories mainly rely on manual periodic recording of data such as electricity meters and water meters, with low data collection frequency and inability to reflect energy consumption changes in real time, making it difficult to detect energy consumption anomalies;

Incomplete coverage of monitoring points:The number of monitoring points is limited, mainly concentrated at the main incoming line, lacking energy consumption monitoring for key equipment, production lines, workshops and other sub links, making it difficult to accurately locate energy consumption issues;

Data isolation and dispersion:Energy consumption data is scattered across different systems and departments, lacking a unified management and analysis platform, making it difficult to integrate and correlate data analysis;

Outdated analytical methods:Mainly relying on simple data comparison and trend analysis, lacking in-depth mining and analysis of energy consumption data, it is difficult to discover potential energy-saving space and root causes of problems;

Relying on experience management:Energy management mainly relies on the experience of management personnel and lacks scientific data support, making it difficult to develop effective energy-saving measures;

Lack of warning mechanism:Unable to detect energy consumption anomalies and equipment failures in a timely manner, resulting in energy waste and equipment damage;

System closure and isolation:The energy consumption system is independent of other production management systems, and data cannot be shared, making it difficult to achieve information linkage and collaborative optimization;

Lack of intelligent applications:Unable to utilize technologies such as artificial intelligence and big data for intelligent applications such as energy consumption prediction and optimization control, it is difficult to achieve automation and intelligence in energy management.

II Ankerui EMS3.0 Smart Energy Solution

2.1 Solution Networking Architecture

The system covers the "source grid load storage charging" link of enterprise microgrids, collecting data from measurement and control devices, new energy generation, mains power, energy storage, charging piles, and conventional loads through intelligent gateways. It optimizes control based on load changes and grid scheduling, promoting the consumption of new energy while reducing the demand for the grid, making its operation safer and more efficient.

2.2 Core Value of Solution

★ Comprehensive perception, real-time monitoring:

Install smart meters and sensors:Install smart meters, water meters, flow meters, temperature and humidity sensors and other equipment at various key nodes of the factory to achieve real-time monitoring and data collection of various energy sources such as water, electricity, and gas.

Building an IoT platform:By utilizing IoT technology to connect dispersed smart instruments and sensors, a comprehensive energy IoT platform covering the entire plant is constructed to achieve real-time data transmission and aggregation.

★ Data integration and in-depth analysis:

Establish a unified data platform:Integrate energy consumption data from different systems and devices, establish a unified energy management database, and provide a foundation for data analysis.

Using big data analysis technology:Deeply mine and analyze energy consumption data, identify energy consumption anomalies and waste links, accurately locate high energy consuming equipment and processes, and provide data support for energy-saving transformation.

Visual display:By using charts, dashboards, and other forms, complex energy consumption data can be visually displayed, making it convenient for management personnel to quickly understand the energy consumption situation.

★ Fine management and scientific decision-making:

Develop a scientific energy management system:Based on the results of data analysis, develop targeted energy-saving measures and energy management systems, and implement them in specific departments and personnel.

Implement energy performance assessment:Incorporate energy consumption indicators into the performance evaluation system of various departments and personnel, and enhance the energy-saving awareness of all staff.

Strengthen equipment maintenance and upkeep:Establish a comprehensive equipment maintenance system, regularly maintain and upkeep equipment to improve operational efficiency and reduce energy consumption.

★ Intelligent optimization, continuous improvement:

Application of artificial intelligence technology:Using artificial intelligence algorithms to predict and optimize energy consumption data, automatically adjusting equipment operating parameters, optimizing energy allocation, and improving energy utilization efficiency.

Establish an energy management model:Establish an energy management model based on the actual situation of the factory, simulate the energy consumption under different working conditions, and provide reference for energy-saving transformation.

Continuous improvement:Regularly evaluate and improve the energy management system, continuously optimize system functions, and enhance the level of energy management.

III Software feature interface display

Electricity statistics:Electricity consumption collection, electricity statistics, time-based electricity consumption, line losses, year-on-year and month on month analysis of electricity consumption, grouped electricity consumption statistics, custom compound rates, and time-based collection;

System operation:Instrument communication status, gateway communication status, server operation status, offline events, operation logs, control logs, online user monitoring, visitor records, communication status diagram;

Electrical safety:Leakage and cable temperature measurement, electrical contact temperature measurement, contact temperature monitoring, contact temperature report, insulation monitoring, fiber optic equipment monitoring, fiber optic partition details, real-time partition data;

Power monitoring:Power operation dashboard, distribution room, DC screen monitoring, reactive power compensation cabinet, transformer monitoring, comprehensive protection S0E event, power curve recording, power extreme value report, power operation report, hourly collection report, hourly collection summary table, maximum demand analysis, average power factor, harmonic analysis, harmonic spectrum, circuit monitoring, monthly power operation report, station load history rate, arc protection, partial discharge;

Distributed photovoltaics:Photovoltaic comprehensive dashboard, power station operation monitoring, inverter operation monitoring, power station generation statistics, inverter generation statistics, photovoltaic power station distribution monitoring, inverter curve analysis, photovoltaic panels, multi device curve analysis, dispersion rate report, simulated power generation, inverter parameter alarm;

Power quality:Comprehensive power quality dashboard, steady-state monitoring, harmonic spectrum, steady-state curve, harmonic curve, load curve, transient analysis, power quality SOE event and waveform analysis, power quality analysis, power quality governance, transient analysis report;

Intelligent lighting:Intelligent lighting control, event control, lighting control, scene control, operation recording, scheduled tasks, lighting monitoring;

Energy storage module:Energy storage operation and maintenance screen, energy storage dashboard, energy storage cabinet monitoring, equipment monitoring, statistical revenue report, time-based revenue report, and strategy issuance;

Industrial energy consumption:Industrial energy consumption topology, production time setting, shift setting, trend analysis, carbon emission monitoring, electricity cost analysis, output input, output statistics, product input, unit consumption report, product unit consumption, and unit consumption benchmarking analysis;

Carbon assets:Emission reduction plan, carbon emission analysis, trading records, carbon trading records, carbon accounting inventory, quota accounting, carbon emission report, carbon flow chart, carbon emission assessment;

4 Recommended hardware products

4.1 Monitoring, protection, and governance products

4.2 Charging pile products

5 Conclusion

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