Community Blog Frontier Technology | Practice Low Carbon with Green AI

Frontier Technology | Practice Low Carbon with Green AI

This article discusses the importance of large-scale development and utilization of green energy as the main direction of energy development worldwide.

By Alibaba DAMO Academy


Green energy (such as wind power and photovoltaic)has developed rapidly over the past few years. Developed countries (including Germany) have benefited from this. The energy structure of many developing countries has also begun to be reconstructed. Seven years ago, King Abdullah II of Jordan first came to China while planning the country's future energy strategy. He hoped to find inspiration from China's fast-growing new energy industry.

China is constantly touching, exploring, and solving many cutting-edge problems in new energy, one of which is the phenomenon of wind curtailment and light curtailment caused by the difficulty of new energy grid connections and low consumption rate. The core reason for these problems is that green energy has the characteristics of volatility, randomness, and anti-peak shaving. Large-scale grid connections may affect the safe and stable operation of the power grid.

The application of artificial intelligence technology will effectively improve the ability of power grids and other energy systems to absorb diversified power sources and coordinate multiple energy sources. It has become the technical support for improving energy utilization and stability and has promoted the process of carbon neutrality. It is expected that in the next three years, artificial intelligence will help the power system achieve large-scale green energy consumption and realize the safe, efficient, and stable operation of the power system.

Development and Evolution of Green AI

In 1839, 19-year-old French scientist Becquerel slowly inserted two platinum metal electrodes into an acidic solution of silver chloride in his father's laboratory. This is an incorrect operation, but he accidentally opened the door to an unknown world. When measuring the current between the electrodes, Becquerel found that the current in the light is slightly greater than the current in the dark. He called this phenomenon the photovoltaic effect, but it became the Becquerel effect many years later.

As the United States used photovoltaic cells in its second artificial satellite launched in 1957, photovoltaic technology finally entered the industry from the laboratory after a hundred years. After decades of development, as climate change began to become a hard constraint on the development of human society, people suddenly realized that new energy represented by photovoltaic and wind power is the most important support for humankind to get rid of fossil energy dependence and achieve carbon neutrality in the foreseeable future.


Application of Green AI

After the large-scale grid connection of green energy, the volatility, randomness, and anti-peak shaving characteristics of wind power and photovoltaic power generation will have an impact on the stability and controllability of the power grid. Green energy is connected to the grid, transmission, consumption, and safe operation. The ability urgently needs to be improved. It is of special significance to the realization of China's dual-carbon strategy.

According to the calculation of China's National Energy Administration, China's unified renewable energy power consumption responsibility weight needs to be increased from 28.7% (in 2021) to 40% (by 2030). The total installed capacity of wind power and solar power generation will reach more than 1.2 billion kilowatts. However, it will face a series of difficulties to continue to increase the proportion of renewable energy, which also lays the foundation for the application of artificial intelligence technology.


Artificial intelligence will play an irreplaceable role in the accurate prediction of power generation, optimized power dispatch, power station performance evaluation, fault monitoring, and risk management and bring three breakthroughs.

Accurate Power Prediction

The algorithm application of big data and neural networks will improve the accuracy of the weather forecast and reduce the error of new energy power generation prediction. Artificial intelligence adjusts the power generation through the prediction and analysis of power weather forecasts, dynamically optimizes the power system power generation strategy, and ensures the stable operation of the power grid, especially in the long-distance and cross-regional green energy consumption.

Intelligent Scheduling Control

At the power dispatch end, the integration of deep learning, big data drive technology, and mechanism simulation technology will help the power scheduling system continuously optimize control strategies. It can enhance the multi-energy coordination capabilities of wind power, photovoltaics, hydropower, and energy storage and achieve multi-energy complementarity. It can also solve the problem of unbalanced power output during peak and trough periods. The large-scale grid connection of green energy also puts forward higher requirements for the flexible reconstruction, operation optimization, decision-making of the hybrid AC/DC transmission grids, and source network load storage interaction. In the future, artificial intelligence will support China's green energy into the incremental main stage.

Automated Fault Response

Real-time monitoring of power grid equipment based on big data and deep learning helps quickly extract fault features and significantly improve the fault identification capability and response speed of the power system. With the deepening of technology integration, it is expected to achieve millisecond-level automatic early warning monitoring and control in the future.


The large-scale development and utilization of green energy have become the main direction of energy development in the world today. Under the trend of connecting a high proportion of green energy to the grid, it is difficult for traditional power systems to cope with the uncertainty of power issued by green energy in strong winds, heavy rains, thunder, and lightning, including the ability to respond to complex faults on time. In the process of operation monitoring, parameter verification and fault monitoring still need a large number of manual participation. It is difficult to make fault feature extraction and identification. The artificial intelligence-based new generation technology will provide technical support and strong support for the overall efficient and stable operation of the energy system to address the various challenges faced by large-scale green energy grid connection in stability, operation, and planning.


The deep integration of artificial intelligence and energy will promote large-scale new energy power generation, grid connection, transmission, consumption, and safe operation and complete the upgrading and transformation of the energy system. We expect that artificial intelligence will help the power system achieve large-scale green energy consumption in the next three years. Energy supply can be interconnected in time and space. Coordinated development of network sources and flexible dispatching can realize the safe, efficient, and stable operation of the power system.

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