Is the energy system in China ready for the mutation of artificial intelligence? | Opinion Environmental works

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🚀 Learn about Is the energy system in China ready for the mutation of artificial intelligence? | Opinion Environmental works

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In early June, I traveled to Guyang in Guizhou County in southwestern China to visit the Data Data Center in China Mobile, which was appointed “National Center for Green Data”. The attachment is located in a group of modern buildings in the new Gui’an region. Since 2021, this group has become center Among the Internet infrastructure in China, it hosts the databases run by major technology companies.

Engineer Jian Chonghai walked in energy-saving innovations at the center-normative cooling cabinets, or Maglev air conditioning system. Unlike traditional AC, Maglev air conditioners eliminate friction in the compressors, which achieves the same cooling effect with 30-40 percent of electricity.

Jian’s focus on energy efficiency is driven by an ambitious expansion plan. The director of the product Li Haiyan also told me, training and managing artificial intelligence models will become part of their business – which may lead to high electricity consumption, carbon emissions and operating costs.

China Mobile is not alone. From large technology companies such as Alibaba, Tensent and Huawei to startups such as Deepseek, Chinese companies are imprisoned Fierce To develop artificial intelligence services.

This is a new challenge for China, especially since experts believe that Amnesty International will become one of the most intense energy -used industries in the country. The central challenge of China is how to become the world’s leading pioneer in artificial intelligence services while not endangering the climate’s work goals.

Electricity and Computing are seen as general services-which means that it should be accessed that it is easy to reach the low cost. But to strike the climate targets in the country, it also needs to be clean and green. The big question is: How can it become reasonable and sustainable at the same time?

While the improvements of efficiency and artificial intelligence capabilities to help other sectors to remove carbons faster, building a new energy system gives priorities for renewable energy sources and meeting computing needs is very important.

Increased appetite

Electricity is expected to increase for data centers in China 170 percent Between 2024 and 2030, according to the International Energy Agency (IEA).

Last year, databases around the world consumed about 1.5 percent of the total generated electricity, a recent report of the European Union Estimates. This class grows quickly. Mainly driven by prosecution servers, the use of electricity in data centers rises by about 12 percent annually. This is four times the pace of the total order of electricity.

The report predicts that by 2030, China and the United States will see approximately 80 percent of energy growth in the global data center.

Wang Young, Associate Professor at the Beijing Institute of Technology, told me that he considers data centers one of the intensive capacitance industries in China-along with steel, cement and petrochemical.

he Estimates By 2030, Chinese data centers will demand about 105 GB of electricity, use 26.3 billion liters of water, and emit 310 million metric tons of carbon dioxide.

This amount of electricity is more than half of the demand for residential electricity in China in 2024.

East data, Western computing

In 2022, China launched an initiative called East data, Western computing. Under the plan, provinces and western regions such as Guizhou, Inner Mongolia, Gansu and Ningxia are assigned to deal with computerized functions such as artificial intelligence training and data storage-work burdens that do not require actual time response.

Meanwhile, groups in areas such as Beijing Tyanjin-Habi, the Yangtisi River, Chong and Chongqing, and the Great Gulf region focus on actual time services such as video flow and AI Chatbot.

one Big goal From this initiative is to reduce energy consumption by taking advantage of the climate favorable in Western Chinese and abundant renewable energy. For example, the average annual temperature of Guyang of 18-20 ° C is naturally reduced from cooling needs, while internal Mongolia provides wind resources and rich solar energy.

By the end of this year, newly built data centers are expected to be operated 80 percent Renewable strength, according to the plan. Solar areas, wind, or powerful electrical energy will build low -carbon databases that deal with intense computing but less sensitive time.

Wang Yongzhen notes that green computing power is not only compatible with national strategies, but also provides concrete economic benefits to companies. He said that making data centers more efficient in energy use means smaller electrical bills.

When artificial intelligence meets the network

One of the important parties to the puzzle is the national integrated computing network, which the government is developing to collect public and private cloud computing resources on one platform. It was highlighted in a recent report by Rand Research Organization, entitled “”The advanced Chinese industrial policy of Amnesty International“.

Kyle Chan of Princeton University, author of the report, is like the network to a “general benefit” model for artificial intelligence account resources – an approach that repeats the model infrastructure development strategies in China that aims to reduce regional inequality.

The network is in line with another major initiative to build a “clean, effective, flexible and smart energy system. From 2024 to 2027, China plans to build a “new power system” that depends on various renewable sources and smart technologies such as artificial intelligence.

Under these two initiatives, electricity and computing are seen as general services-which means that it must be accessed that it is easy to access and low cost. But to strike the climate targets in the country, it also needs to be clean and green. The big question is: How can it become reasonable and sustainable at the same time?

Wang Yongzhen imagines that computing and electricity power will create synergy. “One of the main objectives is to increase the green electricity share used in data centers. The second is to reduce energy consumption-not only with isolated technology upgrades, but through improved system efficiency. The third is to enable data centers to interact with the power network.”

Simply put, when the regions face narrow power supply, computing tasks can turn into data centers that meet the requirements of speed but cost less, using immediate electricity market prices as instructions. This approach promotes the reliability of the artificial intelligence of customers while reducing local energy screams.

“When facing cutting and chopped solar energy supply, data centers can also act as temporary stores by” running “some computing tasks such as artificial intelligence training during excess display periods.”

Wang also indicated that data centers can be coordinated to allow the network to take advantage of their energy storage systems during emergency situations. This is often shared with the model of the car to the network that believes that electric cars restore energy to the network during the peak in the demand.

However, the challenges remain.

First of all, synergy between computing networks and power networks that Wang described as intense format – across different parties, government agencies, and even at the level of employees. It should also be tested through different scenarios over a long period.

Wang Young Steven said he noticed a communication gap between employees in data centers, between IT engineers such as Lee Hayan and operating staff such as Jian Chonghai. This gap can become the main bottleneck in the future. “They need to stay at the head of both computing and energy systems if they want to make seeing this very coordinated network a reality.”

Another challenge is the market design.

China Academy of Information and Communications Technology Note that The system of green electricity certificates, which tracks and is achieved from renewable energy generation, is still in line with the market demand. In 2023, only 1.5 million megawatts (MWH) of the green power of 3.8 million megawatts circulated included the certificates.

This can hinder data centers that want to buy more green electricity or track the green power share in using their energy.

Amnesty International Marches on

State Council for the year 2017 document Set a goal for China to become a world leader in artificial intelligence theory, technology and application by 2030. It shows that the development of artificial intelligence in China will not slow down despite the pressure on energy, climate goals and other countries such as the United States.

Kyle Chan notes that for China, the goal is not only “winning the race” with the United States, but also building “the flexible Amnesty International industry that will enhance productivity across sectors – from manufacturing and health care to education and governance.”

Although progress in artificial intelligence leads a demand for energy from databases, increased computing power also helps in support of carbon removal efforts in other sectors, “says Wang Young Hong. Therefore, when considering consuming artificial intelligence energy in the broader context of community carbon removal, excessive simplicity is equal to the use of increased energy with a relapse of climate goals.

One of the biggest obstacles to the efforts made to build the National Management System He told me In podcast. Full carbon accounting requires following everything from suppliers to delivery. Many companies are afraid to expose trade secrets.

As a host of neutral data, an intelligent power -powered agent can store emissions data safely and grant access to organizers with secrecy protection. In this way, artificial intelligence becomes a critical tool for reducing industrial emissions.

But these ideas are still in the experimental stage, and it will take some time to see tangible results on how artificial intelligence – or if – is – from artificial intelligence already, or reduces emissions.

Returning to the Gui’an Data Center, Li Haiyan resembles artificial intelligence models prevailing in university students. In the future, engineers will train more specialized artificial intelligence models that focus on the field-for postgraduate, doctoral and post-PhD studies-which can provide more targeted and practical solutions. It believes that this shift will also reduce the demand for chips used in both training and artificial intelligence models, and this is likely to reduce the demand for energy to operate and cool them.

This article was originally published on Earth dialogue Under the creative public license.

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