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Qingdao Energy Group's subsidiary, Taineng Natural Gas Co., Ltd., has vigorously promoted ubiquitous integrated energy supply solutions based on natural gas and coupled with solar energy, air source, sewage source heat pumps, etc., achieving remarkable results. This project renovation integrates the automation systems of various stations, including station control, air conditioning, and boilers, enabling automatic operation and remote monitoring of each system. It supports Taineng Company in coordinating and optimizing clean energy production operations, improving energy utilization efficiency and user experience, and quickly capturing the local integrated energy service market.

Jinyu Jidong Cement has an annual clinker production capacity of 117 million tons, cement production capacity of 170 million tons, ready-mixed concrete production capacity of 78 million cubic meters, and waste heat power generation installed capacity of 547.7 MW. It is China's third-largest and the world's fifth-largest cement enterprise, as well as the country's largest comprehensive building materials company. Our company has implemented a highly integrated, digitalized, and visualized production and energy efficiency management system for 36 factories under Jidong. It has brought direct economic benefits exceeding 56 million yuan, and more importantly, fundamentally driven a qualitative leap in the management level of cement enterprises.

Since Hisense Group initiated the construction of "smart factories" in 2018, all related functional modules have been independently developed by its IT team. For the energy management part, after thorough research and repeated comparisons, the group headquarters signed a smart energy management system advancement agreement with our company. This agreement involves the phased implementation of energy management systems across all factories in 29 industrial parks, including Qingdao and Shunde, effectively supporting and guiding each factory's low-carbon innovation and green production, and solidly achieving the group's development goals of "health, intelligence, and energy conservation".

The power prediction system deployed at a PV power station in Guizhou integrates meteorological satellite data, ground monitoring station data, and historical power generation data of the PV power station. Through AI algorithms, it achieves precise prediction of the power station's power generation for the next few hours or even days. Precise power prediction helped the power station optimize its power generation plan, reduce power fluctuations caused by weather changes, and improve power generation efficiency by approximately 15%. Simultaneously, it increased grid connection capability. Precise power prediction improved the grid's acceptance capacity for PV power stations, reduced curtailment due to inaccurate prediction, and increased online power generation by approximately 410,000 kWh within three months, enhancing economic benefits.

The E-text data governance technology equipped in the system has been implemented in 32 renewable energy stations in Yunnan. This technology efficiently manages and accurately analyzes massive renewable energy data through advanced data processing algorithms and intelligent analysis models. The operational results indicate that within three months, the customer reduced assessment costs for data qualification rate by 4.3 million yuan. Accurate available power calculations not only helped the station pass the available power retest smoothly but also reduced assessment expenditures due to inaccurate calculations. Additionally, the E-text data governance technology significantly enhanced data accuracy and reliability, optimized station operational efficiency, and provided robust support for the intelligent management and decision-making of new energy stations. Through the application of this technology, new energy stations in Yunnan achieved significant success in data governance and power prediction, establishing a solid foundation for promoting high-quality development of the regional new energy industry.

The system integrates operation data and terrain data of new energy stations to create a new energy power prediction model, which was implemented at a wind farm in Guangxi in July 2024. Within six months, the wind farm's power prediction assessment costs decreased by 30% year-on-year. Accurate power prediction has brought comprehensive optimization to the wind farm. By accurately forecasting wind power output in advance, the wind farm can better coordinate with grid dispatch and optimize electricity trading strategies, thereby securing a more favorable position in the market. Additionally, precise prediction has reduced grid operation risks caused by power fluctuations, enhancing the stability and reliability of the wind farm.