{"id":60133466,"date":"2026-05-18T18:21:27","date_gmt":"2026-05-18T17:21:27","guid":{"rendered":"https:\/\/dialogue.earth\/?p=60133466"},"modified":"2026-05-19T15:41:58","modified_gmt":"2026-05-19T14:41:58","slug":"how-far-can-ai-improve-chinas-power-grid","status":"publish","type":"post","link":"https:\/\/dialogue.earth\/en\/energy\/how-far-can-ai-improve-chinas-power-grid\/","title":{"rendered":"How far can AI improve China\u2019s power grid?"},"content":{"rendered":"\n

This is the third year<\/a> that China\u2019s annual Government Work Report has mentioned artificial intelligence, with the language used becoming more concrete and specialised.<\/p>\n\n\n\n

In the energy sector, there is particular focus on AI for electricity grids. The National Development and Reform Commission has said<\/a> that by 2027 at least five specialised large language models will be deeply embedded in the power grid, power generation and other fields.<\/p>\n\n\n\n

However, AI could be a double-edged sword for China\u2019s transition to clean energy.<\/p>\n\n\n\n

On one hand, the country has high hopes for the technology: in Shanghai, Xinjiang and Beijing AI models and algorithms are being used to predict renewable energy output and to optimise and secure grids. Data centres, meanwhile, could in theory<\/a> help use up green electricity that would otherwise be wasted and add flexibility to the grid.<\/p>\n\n\n\n

But the data centres on which AI relies are energy hungry. They are predicted to use 3-5%<\/a> of all China\u2019s electricity generation by 2030<\/a> \u2013 against residential consumption of 15%. Generative AI and other advanced services can cause short-term spikes in electricity consumption and there are already examples of that affecting grid security<\/a>.<\/p>\n\n\n\n

So, what can AI and the data centres that power it do to make China\u2019s grids more efficient, keep those grids stable, and make use of green electricity? Dialogue Earth spoke to the experts.<\/p>\n\n\n\n

The rise of AI in grid applications<\/h2>\n\n\n\n

The International Energy Agency predicts<\/a> that AI-powered algorithms could optimise grid operations, improve the integration of wind and solar output and cut unexpected outages by up to 50%. \u201cIf scaled up, existing AI-led interventions could lead to global electricity savings of around 300 terawatt-hours\u201d. That\u2019s more than twice the amount of power Beijing uses in a year.<\/p>\n\n\n\n

Many of China\u2019s electricity suppliers and research organisations are working on<\/a> AI tools for their own specific needs. The China Southern Power Grid, for example, says<\/a> it has developed a precise power forecasting system which can support the trading of electricity and improve both the security and cost efficiency of the grid.<\/p>\n\n\n\n

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AI is beginning to be involved with virtual power plants (VPPs) which are aggregations of distributed energy resources managed collectively to behave like a single power plant. Early this year, Shanghai Securities News reported<\/a> on how AI had helped a local VPP cope with a cold snap. On receiving the weather forecast, the VPP told a manufacturer to reduce consumption. The article describes AI as the \u201cbrain\u201d of VPPs, able to reduce inaccuracy in real-time consumption estimates to under 3%, and make 85% accurate prediction of mid- and long-term spot market prices.<\/p>\n\n\n\n

Shanghai<\/a>, Jiangsu<\/a> and Guangdong<\/a> are using data centre energy storage facilities in provincial VPPs, according to state media outlets, with AI predicting electricity demand, dispatching power and steering consumers to switch demand from peak times to quieter periods, so reducing pressure on the grid. This is expected to shave \u201c3.5 gigawatts\u201d off peak demand in 2026, according to business outlet Qianjia<\/a>.<\/p>\n\n\n\n

According to a list<\/a> compiled by Deben Consulting, China\u2019s grids will use AI to check for faults, predict risks and support \u201cdemand response\u201d. This means encouraging consumers to shift their electricity use to times when it is more plentiful or general demand is lower, something which can also support greater use of renewable power.<\/p>\n\n\n\n

Although, as the International Energy Agency states<\/a>, AI is already being deployed to \u201ctransform and optimise energy and mineral supply, electricity generation and transmission, and energy consumption,\u201d some experts are dubious that it can make a useful contribution to China\u2019s energy grids as they exist today.<\/p>\n\n\n\n

How far can AI improve China\u2019s grids?<\/h2>\n\n\n\n

Gao Hongchao, chief scientist assistant for the National Key Project on Virtual Power Plants, said that \u201cin engineering terms, the integration of AI into virtual power plants is at a very early stage. You could even say that current projects haven\u2019t seen very good or real applications and outcomes.\u201d<\/p>\n\n\n\n

Gao told Dialogue Earth a key issue is that the current legislation isn\u2019t able to assign responsibility for any errors made by the tools. \u201cIn a grid like China\u2019s, which prioritises reliability, you can\u2019t make full use of AI for dispatch. Mostly it\u2019s used to assist in decision-making.\u201d<\/strong><\/p>\n\n\n\n

Zhang Shuwei, chief economist at the Draworld Centre think-tank, told Dialogue Earth that AI can only have a limited impact, even in a supporting role.<\/p>\n\n\n\n

He said that China\u2019s grids are focused on maintaining stable supplies<\/a>, and so AI is mainly used to that end, rather than for improving efficiency, as in the west.<\/p>\n\n\n\n

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Staff at work at an electrical substation of the State Grid Xiong’an New Area Power Supply Company (Image: Mu Yu \/ Xinhua \/ Alamy)<\/div><\/div><\/div><\/div>\n\n\n\n

For example, in 2019<\/a> the National Energy Administration required<\/a> that dispatch operations should consider seasonal conditions and set \u201cstable operation quotas\u201d and \u201ccalculate and analyse stability of trunk lines and localities.\u201d<\/p>\n\n\n\n

Zhang explained that Chinese generators all stand ready to respond to dispatch orders, bringing capacity on or offline as required. \u201cIn a system like that, you don\u2019t get big price fluctuations across time,\u201d he said.<\/p>\n\n\n\n

\u201cIf all dispatch-ready generators are running steadily, there\u2019s no scope for price changes. But price changes are essential for advanced grid-control technologies like AI to play their role, as they profit from price differences across generators and consumers.\u201d With no financial incentive to provide more accurate predictions, it will be hard to apply AI for greater efficiency.<\/p>\n\n\n\n

However, AI tools are being used to shave peak demand. In Shenzhen, the technology was used<\/a> over 150 times between 2023 and 2025 to reduce load at peak times, according to Science and Technology Daily.<\/p>\n\n\n\n

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But Zhang Shuwei thinks it\u2019s hard to use data to decide when peak shaving is necessary and fair \u2013 and AI won\u2019t help.<\/p>\n\n\n\n

\u201cWhen demand is 1,000 kilowatt-hours and you have supply of 800, you need to drop 200. But deciding where is a value judgement. That\u2019s not going to change just because you use AI. AI can\u2019t bring about fairer or more efficient allocations \u2013 all it does is amplify the (existing) system\u2019s imbalances.\u201d<\/p>\n\n\n\n

Anders Hove, a senior research fellow at the Oxford Institute for Energy Studies, agrees that flexibility is a problem, saying the use of AI for peak shaving in Shanghai is not a typical example. The biggest bottleneck for China\u2019s grids, he says, and for the use of AI in grid operations, remains a lack of flexibility.<\/p>\n\n\n\n

He said that overall, China\u2019s peaks in demands are \u201cmuch more modest\u201d than those seen in the west. \u201cChina’s power system has a higher proportion of industrial demand than in North America or Europe, hence it has somewhat more stable load. However, peak load is growing rapidly, and this is a serious concern for grid officials, along with the problem of the \u2018duck curve<\/a>\u2019 due to high solar output at midday, high peak demand in late afternoon\/early evening, leading to fast ramping requirements. Flexibility is needed to handle such peaks.\u201d<\/p>\n\n\n\n

However, in China \u201cmost electricity trading is on a monthly or annual basis. In particular, intra-province trading and inter-province transfers are almost always done on long-term contracts concluded far in advance.\u201d Although the government often \u201ctalks about how important inter-provincial trades are\u201d and offers examples of flexibility, those cases are the exceptions.<\/p>\n\n\n\n

In fact, China\u2019s transmission lines \u201cdo not, like those in North America and Europe, send electricity back and forth according to demand,\u201d he said. \u201cGovernment policy makes clear that the goal is for 90% of electricity transfers to be done under long-term contracts \u2013 which runs contrary to the idea of flexibility.\u201d<\/p>\n\n\n\n

This means that even if data centres and AI can predict gaps in supply and demand, they cannot flexibly and promptly deliver power to where it is needed, Hove said.<\/p>\n\n\n\n

\u201cEastern Data, Western Compute\u201d and \u201cCompute\/Electricity Coordination\u201d<\/h2>\n\n\n\n

In 2022, China launched a project<\/a> to meet computational demands arising in the east of the country in new data centres to the west, where there are ample supplies of wind, solar and other clean sources of energy.<\/p>\n\n\n\n

Anders Hove said that while there is research<\/a> showing data centres can be a source of flexibility in the system rather than a constant source of load, the reality is that most such facilities in China are still located in the east<\/a>.<\/p>\n\n\n\n

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\u201cFlexibility across time and place is only practical for a very small part of their operations,\u201d he said. \u201cMore important are economic factors. Customers don\u2019t tell them which tasks can wait till later, nor do they care where and when the tasks are done. They just pay for speed and reliability.\u201d The need to provide customers with immediate responses means that while data centres in the east may send some tasks to facilities in the west of China, they will not relocate there.<\/p>\n\n\n\n

However, data centres can also encourage the development of clean energy. Last month the government introduced the idea of coordinating the power and data centre sectors<\/a>, with the centres to shift from being major power consumers to aiding in grid management.<\/p>\n\n\n\n

The policy will see data centres integrated into power allocation, so they use as much green electricity as possible where it is available. For example, bright and sunny Ningxia\u2019s \u201ccompute and power integration<\/a>\u201d project has hooked its 500-megawatt solar power farm<\/a> up to the grid.<\/p>\n\n\n\n

According to Xinhua<\/a>, the National Data Administration has said new computing facilities built at eight national computing hubs must draw 80% of their power from green electricity.<\/p>\n\n\n\n

Zhang Shuwei said this is a positive signal for \u201cadditionality\u201d: if data centres can, through power purchase agreements and contractual arrangements, promote new investment in wind and solar power and help build their own power supplies, \u201cthat\u2019s good news for the climate\u201d.<\/p>\n","protected":false},"excerpt":{"rendered":"

Experts think a lack of flexibility in China\u2019s grids could undercut potential efficiency gains from artificial intelligence<\/p>\n","protected":false},"author":50000909,"featured_media":60133486,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[757],"tags":[40027749,17073,597],"hashtags":[],"country":[20000110],"class_list":["post-60133466","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-energy","tag-big-data","tag-energy-transition","tag-technology","country-china"],"acf":[],"yoast_head":"\nHow far can AI improve China\u2019s power grid? | Dialogue Earth<\/title>\n<meta name=\"description\" content=\"Experts think a lack of flexibility in China\u2019s grids could undercut potential efficiency gains from artificial intelligence\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dialogue.earth\/en\/energy\/how-far-can-ai-improve-chinas-power-grid\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"How far can AI improve China\u2019s power grid?\" \/>\n<meta property=\"og:description\" content=\"Experts think a lack of flexibility in China\u2019s grids could undercut potential efficiency gains from artificial intelligence\" \/>\n<meta property=\"og:url\" content=\"https:\/\/dialogue.earth\/en\/energy\/how-far-can-ai-improve-chinas-power-grid\/\" \/>\n<meta property=\"og:site_name\" content=\"Dialogue Earth\" \/>\n<meta property=\"article:published_time\" content=\"2026-05-18T17:21:27+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-05-19T14:41:58+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/dialogue.earth\/content\/uploads\/2026\/05\/The-power-dispatching-center-in-the-Xiongan_Yang-Shiyao_Xinhua_Alamy_3E4033T-1200px-copy.jpeg\" \/>\n\t<meta property=\"og:image:width\" content=\"1200\" \/>\n\t<meta property=\"og:image:height\" content=\"792\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Wanyuan Song\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/dialogue.earth\/en\/energy\/how-far-can-ai-improve-chinas-power-grid\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/dialogue.earth\/en\/energy\/how-far-can-ai-improve-chinas-power-grid\/\"},\"author\":{\"name\":\"Wanyuan Song\",\"@id\":\"https:\/\/dialogue.earth\/en\/#\/schema\/person\/f89935c48ae2e2bbfe06460d01be91d5\"},\"headline\":\"How far can AI improve China\u2019s power grid?\",\"datePublished\":\"2026-05-18T17:21:27+00:00\",\"dateModified\":\"2026-05-19T14:41:58+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/dialogue.earth\/en\/energy\/how-far-can-ai-improve-chinas-power-grid\/\"},\"wordCount\":1632,\"publisher\":{\"@id\":\"https:\/\/dialogue.earth\/en\/#organization\"},\"image\":{\"@id\":\"https:\/\/dialogue.earth\/en\/energy\/how-far-can-ai-improve-chinas-power-grid\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/dialogue.earth\/content\/uploads\/2026\/05\/The-power-dispatching-center-in-the-Xiongan_Yang-Shiyao_Xinhua_Alamy_3E4033T-1200px-copy.jpeg\",\"keywords\":[\"Big data\",\"Energy transition\",\"Technology\"],\"articleSection\":[\"Energy\"],\"inLanguage\":\"en\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/dialogue.earth\/en\/energy\/how-far-can-ai-improve-chinas-power-grid\/\",\"url\":\"https:\/\/dialogue.earth\/en\/energy\/how-far-can-ai-improve-chinas-power-grid\/\",\"name\":\"How far can AI improve China\u2019s power grid? 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In recent years, the power grid construction in the Xiong'an New Area has been striving for higher standards and reliability. Guided by the concept of green, innovative and smart development, the Xiong'an New Area has actively developed an AI-based smart grid dispatching system using AI technology. 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