Industrial News

on 29 Oct 2022 11:36

The importance of building industrial energy management systems under the "double carbon" target

I. What is "carbon peak" and "carbon neutral"?
Carbon peak: refers to a region or industry's annual carbon dioxide emissions reach a historical high, and then go through a plateau to enter a continuous decline process, which is the historical inflection point of carbon dioxide emissions from increasing to decreasing, marking the decoupling of carbon emissions from economic development, and the peak target includes the peak year and peak value.
Carbon Neutral: It refers to the direct and indirect carbon dioxide emissions from anthropogenic activities in a certain period of time (usually one year) to achieve "net zero" carbon dioxide emissions.

II. The opportunities and challenges of carbon neutrality and emission peak

1, Forcing industrial transformation and upgrading to improve the quality of economic growth.

2, Accelerate China's energy transformation and energy revolution process
3, Accelerate the pace of high energy consumption, heavy chemical industries and other industries to production capacity and restructuring and integration.
III. Industrial energy management system value for carbon neutrality and emission peak

Digitalization and intelligence have become important means for industrial enterprises to move towards the carbon neutrality and emission peak.

Digital technology will effectively help industrial enterprises to achieve carbon neutrality and emission peak, with data as the core, based on the massive data collected centrally by smart sensors and smart meters, combined with software platforms and big data analysis technology to achieve energy saving and consumption reduction and intelligent management. In terms of energy consumption optimization and emission control, through the use of big data analysis and other technologies, energy consumption supervision is strengthened, energy management systems are improved, energy consumption and emissions of industrial enterprises are intelligently managed, energy efficiency is improved, and unit energy consumption is reduced.

In production operation, the intelligent and digital management is realized through improving software and hardware infrastructure and equipment intellectualization in scenarios such as process optimization, scheduling control, and remote collaboration to promote quality and efficiency in production operation. Empowered by digital technology, the productivity and work efficiency of enterprises are improved, while energy use and carbon emissions are effectively reduced to achieve energy saving and cost reduction.
IV. Functions of industrial energy management system

1. Carbon Emission Management

Accounting carbon emissions of enterprises includes total emissions, each process emission, process unit emission and key equipment emission.
 2. Trend Forecasting
It can help users to judge the electricity consumption in the future period, on the basis of which energy saving management plan can be carried out. The predicted value can be compared with the actual value after the implementation of energy saving management plan. Users can check the deviation value to evaluate the energy saving effect.
 3. Energy monitoring
View real-time data, historical data, event data, harmonic analysis, and meter reading data of smart meters at any time. It helps users to quickly trace the fault occurrence point and grasp the equipment operation status in real time.
4.Alarm Center
Set alarm thresholds to actively grasp the abnormal operation status of equipment to improve the quality of energy consumption. It records alarm information of energy consumption units and can push the alarm information to the recipient through multiple channels in a timely manner.
 5. Report service
Energy consumption unit data reports, daily reports, weekly reports, monthly reports, annual reports, and shift reports can be exported, and users can also customize the report format and content.

V. Benefits of industrial energy management system

1.    Management energy saving
It helps enterprises form a gradual and efficient energy management system, change energy consumption management from disorderly to orderly and fully grasp the flow and utilization efficiency of energy. Also, it reduces the work intensity of operation and maintenance personnel, reduces the rate of errors, and improves the level of operation and maintenance service.

2. Optimize production load
According to the local power company's multi tariff, combined with the actual needs of customers, users can reasonably allocate production personnel and production equipment input, balance production capacity, and reduce production costs with simple management methods.

3. Improve the quality and reliability of energy use
Users can grasp the status of energy-using equipment comprehensively, grasp the abnormal and fault situation of equipment timely, reduce the loss caused by abnormality, and make prediction of potential problems to improve the reliability of energy use and equipment reliability. The system can monitor the energy quality problems, especially the power quality problems, and optimize the power quality in time after the problems are found.

4.Optimize energy-using assets
By recording and analyzing the load characteristics of energy-using equipment, we can discover potential capacity and account for energy consumption to help choose a more economical way to pay for energy bills. For example, "capacity to demand" transformation. At the same time, the structure of fixed assets can be optimized according to the market situation of the enterprise, and redundant equipment can be liquidated.

5. Technical energy-saving transformation
Based on business big data, data model analysis aids decision making, helps discover space for energy-saving transformation and processes optimization, and conducts cost accounting and energy-saving effect assessment. With a basis and supervision, we can reduce the production cost of enterprises through equipment transformation or the use of new energy-saving technologies.