Carbon Emission Reduction Intelligent IOT helps reduce energy and increase efficiency
1. Intelligent control to reduce consumption and increase efficiency
When it comes to IOT, it is easy to associate the word "IOT" in the name with the intelligent picture of interconnection of everything, but we ignore the sense of control behind the interconnection of everything, which is the unique value of IOT and Internet due to the different connection objects. This is the unique value of the Internet of Things and the Internet due to the difference in the connected objects.
Based on this, we then open up the idea of achieving cost reduction and efficiency in production and application through intelligent control of objects/factors of production.
For example, the use of IoT in the field of power grid operation can help grid operators to better control power transmission and distribution and improve the efficiency of power transmission. Through sensors and smart meters to collect data in various aspects, with artificial intelligence, big data analysis to give optimal power consumption recommendations, can save 16% of the next electricity consumption.
In the field of industrial IoT, take Sany's "No. 18 plant" as an example, in the same production area, the capacity of No. 18 plant in 2022 will be increased by 123%, the efficiency of personnel will be increased by 98%, and the unit manufacturing cost will be reduced by 29%. Only 18 years of public data show that the manufacturing cost savings of 100 million yuan.
In addition, the Internet of Things can also play an outstanding energy-saving skills in a number of aspects of smart city construction, such as urban lighting control, intelligent traffic guidance, intelligent waste disposal, etc., through flexible regulation to reduce energy consumption and promote carbon emission reduction.
2. Passive IOT, the second half of the race
It is the expectation of every industry to reduce energy and increase efficiency. But every industry will eventually face the moment when "Moore's Law" fails under a certain technical framework, thus, energy reduction becomes the most secure way of development.
In recent years, the Internet of Things industry has been developing rapidly and improving efficiency, but the energy crisis is also close at hand. According to IDC, Gatner and other organizations, in 2023, the world may need 43 billion batteries to provide the energy required for all online IoT devices to collect, analyze and send data. And according to a battery report by CIRP, global demand for lithium batteries will increase tenfold by 30 years. This will directly lead to an extremely rapid decline in raw material reserves for battery manufacturing, and in the long run, the future of IoT will be full of great uncertainty if it can continue to rely on battery power.
With this, passive IoT can expand a broader development space.
Passive IoT was initially a supplementary solution to traditional power supply methods in order to break the cost limitation in mass deployment. At present, the industry has explored the RFID technology has built a mature application scenario, passive sensors also have a preliminary application.
But this is far from enough. With the implementation of the refinement of the double carbon standard, enterprises for low-carbon emission reduction needs to stimulate the application of passive technology to further develop the scene, the construction of passive IOT system will release the passive IOT matrix effectiveness. It can be said that who can play passive IoT, who has grasped the second half of IoT.
Increase carbon sink
Building a large platform to manage the IOT tentacles
To achieve the dual carbon goal, it is not enough to rely only on "cutting expenditure", but must increase the "open source". After all, China as the world's first country in carbon emissions, a total of one person can reach the second to fifth of the United States, India, Russia and Japan combined. And from the carbon peak to carbon neutral, developed countries promise to complete 60 years, but China only 30 years period, it can be said that the road is long. Therefore, carbon removal must be a policy-driven area to be promoted in the future.
The Guide specifies that carbon removal is mainly through ecological carbon sinks generated by the exchange of carbon and oxygen in the ecosystem and through technology-driven carbon capture.
At present, carbon sequestration and sink projects have been effectively landed, mainly in the types of native woodland, afforestation, cropland, wetland and ocean. From the perspective of the projects that have been announced so far, forest land carbon aggregation has the largest number and the widest area, and the benefits are also the highest, with the overall carbon trading value of individual projects being in the billions.
As we all know, forest protection is the most difficult part of ecological protection, and the smallest trading unit of forestry carbon sink is 10,000 mu, and compared with the traditional disaster monitoring, forestry carbon sink also needs daily maintenance management including carbon sink measurement. This requires a multi-functional sensor device that integrates carbon measurement and fire prevention as a tentacle to collect relevant climate, humidity and carbon data in real time to assist staff in inspection and management.
As the management of carbon sink becomes intelligent, it can also be combined with the Internet of Things technology to build a carbon sink data platform, which can realize the "visible, checkable, manageable and traceable" carbon sink management.
Dynamic monitoring for intelligent carbon accounting
The carbon trading market is generated based on carbon emission quotas, and companies with insufficient allowances need to buy the extra carbon credits from companies with surplus allowances to achieve annual carbon emission compliance.
From the demand side, the TFVCM working group predicts that the global carbon market could grow to 1.5-2 billion tons of carbon credits in 2030, with a global spot market for carbon credits of $30 to $50 billion. Without supply constraints, this could increase up to 100 times to 7-13 billion tons of carbon credits per year by 2050. The market size would reach US$200 billion.
The carbon trading market is expanding rapidly, but the carbon calculation capacity has not kept up with the market demand.
At present, China's carbon emission accounting method is mainly based on calculation and local measurement, with two ways: government macro measurement and enterprise self-reporting. Enterprises rely on manual collection of data and supporting materials to report regularly, and government departments carry out verification one by one.
Secondly, the government's macro theoretical measurement is time-consuming and usually published once a year, so enterprises can only subscribe to the cost outside the quota, but cannot adjust their carbon reduction production timely according to the measurement results.
As a result, China's carbon accounting method is in general crude, lagging and mechanical, and leaves room for carbon data falsification and carbon accounting corruption.
Carbon monitoring, as an important support for the auxiliary accounting and verification system, is the basis for ensuring the accuracy of carbon emission data, as well as the basis for the evaluation of greenhouse effect and the yardstick for the formulation of emission reduction measures.
At present, a series of clear standards for carbon monitoring have been proposed by the state, industry and groups, and various local government agencies such as by Taizhou City in Jiangsu Province have also set up the first municipal local standards in the field of carbon emission monitoring in China.
It can be seen that based on intelligent sensing equipment to collect the key index data in enterprise production in real time, the comprehensive use of blockchain, Internet of Things, big data analysis and other technologies, the construction of enterprise production and carbon emissions, pollutant emissions, energy consumption integrated dynamic real-time monitoring index system and early warning model has become inevitable.
Post time: May-17-2023