IDC: The market size of big data platform+application solutions for China's power industry will exceed 1.8 billion yuan in 2023

The Zhitong Finance App learned that according to IDC data, China's big data market reached 17.93 billion yuan in 2023, an increase of 24.6% over 2022. Among them, the big data market in the power industry also showed a growing trend compared to 2022. In 2023, China's power industry big data platform+ application solution market exceeded 1.8 billion yuan. Real-time data processing, streaming data processing, big language models, other AI-based applications, and the trend of increasingly refined management in the power industry are key drivers of this market. Generative AI-driven big data platforms are a new opportunity in this market.

5 stages of the evolution of big data technology in the power industry

IDC research found two major trends in the big data market in the power industry:

On the one hand, with the upgrading of the digital and refined management of the power industry, the amount of data is also growing exponentially and showing a high level of concurrency, which makes the power industry more dependent on data-driven intelligent decisions.

On the other hand, electricity is the only traded product that cannot be stored for a long time. Therefore, the power industry has extremely high requirements in terms of safety and supply. Artificial intelligence algorithms and data-driven intelligent decision-making can reduce a large amount of unplanned downtime for the industry and improve power supply efficiency. Coupled with the gradual spread of generative AI technology to the power industry, IDC predicts that there is still plenty of room for growth in the power industry's big data market in the future.

Market competition is mainly dominated by comprehensive cloud vendors and big data vendors in the field of specialized technology. In terms of market share, HUAWEI CLOUD, Zhongneng Shibai, and Langxin Technology rank in the top three, and are the main players in this market. Zhixiang Technology, Merrill Lynch Data, and Starlink Technology ranked fourth to sixth in the market.

IDC's recommendations for technology vendors:

Customer demand is in a stable window

Central enterprises in the energy and power industry will continue to open up the construction window for data governance and big data platforms, and there is a trend of gradually expanding from group integration to self-construction by second-level and third-level units. Many big data vendors have focused their business development on the energy and power industry this year. Moreover, most first-line manufacturers still have problems such as poor data quality, low degree of data integrity and consistency, chaotic data storage architectures, and insufficient talent in big data or AI, which require professional big data vendors to work with customers to co-build in-depth scenarios.

Customers need long-term stable big data services

Due to the special nature of the power industry, the operation process is often accompanied by dangerous production environments, and once an accident occurs, serious consequences will occur. Therefore, power generation, power grid, and power supply companies attach great importance to production and transmission safety. In addition, unplanned shutdowns can also reduce production volumes, disrupt production schedules, etc., and cause huge losses. Therefore, end users need the manufacturer's products with stable performance and strong scalability to cope with the massive data access and processing capabilities that may increase exponentially in the future, while supporting the linear expansion of subsequent platforms. For example, if the State Grid increases the precise management of power grid scheduling, it is necessary to raise the original ten-minute power transmission judgment to the second level to improve fault handling efficiency and shorten power outages, so the amount of data will increase dramatically; in addition, with the increase in the share of new energy sources and the explosive growth of energy storage and controllable load decision targets, the computational complexity of power grid optimization will also increase exponentially. These trends all need to be supported by stable and expandable big data services.

Adapt to the increasingly fierce competition among manufacturers in the power big data industry

Central enterprises in the energy and power industry have long-term digital infrastructure upgrade needs and stable cash flow, and many big data vendors have placed the energy and power industry as one of the key directions for business development. However, the difficulty is that most professional big data vendors have insufficient know-how in the power industry. Furthermore, end users in the power industry have extremely high data security requirements and aversion to the risk of downtime. Manufacturers need to show a differentiated advantage on these two points in order to cope with competition among friends and merchants under the industry category.

Zhou Qishan, China Energy Industry Research Manager at IDC, said that central state-owned enterprises have characteristics such as stable cash flow, large project size, and long-term digital infrastructure upgrades. Central and state-owned enterprises in the power industry have set goals and paths for digital transformation. Among them, big data platforms and applications are an essential part of this, and there is a trend of gradually expanding from group integration to self-construction by level 2 and 3 units. At the same time, industry end users are actively releasing signals for the construction and testing of industry-specific large-scale models. Generative AI requires large amounts of high-quality data to train models, which will accelerate the demand for mass data collection, storage, and processing. In particular, when training large multi-modal models, the requirements for data diversity are high, which will stimulate the industry's demand for the collection, storage and processing of multi-dimensional complex data such as text, images, video, and speech. In terms of predictive equipment maintenance and fault handling, it will also promote the industry's demand for accumulated positive and negative sample data on equipment and operation, thereby driving the development of the industry's vertical big data market.