Based on the background of new engineering construction, this article focuses on the practical dilemma that the traditional teaching mode lags behind the technical iteration in talent cultivation in the field of electric power intelligent operation and maintenance. By using system theory and other methods, this article deeply analyzes the requirements of the digital transformation of industry for the remolding of engineers' literacy, and constructs a talent training coupling model with three-tier structure: value leading, ability support and collaborative guarantee. This article systematically explains the internal coupling logic of education chain, industrial chain and innovation chain, reveals the knowledge explicit mechanism of transforming real projects of enterprises into teaching resources, and puts forward an ecosystem guarantee framework covering multi-subject incentive compatibility and institutional environment optimization. It is proved that breaking organizational boundaries and establishing a resource sharing platform with symmetrical information are effective ways to reduce the cost of cooperation, and the core role of process evaluation and third-party feedback in quality control is emphasized. At the same time, the article emphasizes the goal shift from instrumental rationality to humanistic rationality, and establishes engineering ethics as the foundation of collaborative education. This article aims to provide a paradigm reference for educational reform, promote the integration of resources, and realize the long-term dynamic balance between talent training and industrial demand.

Yanliang Zhou. Research on the Education Mode of Electric Power Intelligent Operation and Maintenance Technology Teaching and Industry-Education Cooperation from the Perspective of New Engineering. Frontiers in Educational Research (2026), Vol. 9, Issue 7: 117-122. https://doi.org/10.25236/FER.2026.090715.

[1] Xu Ying, Hao Zhenghang, Li Qingsheng, et al. Research on Microgrid Simulation Experiment Platform Based on the Concept of Emerging Engineering Education[J]. Intelligent Computer and Applications, 2023, 13(10): 92-97.

[2] Ojadi J O, Odionu C S, Onukwulu E C, et al. AI-enabled smart grid systems for energy efficiency and carbon footprint reduction in urban energy networks[J]. International Journal of Multidisciplinary Research and Growth Evaluation, 2024, 5(1): 1549-1566.

[3] zur Heiden P, Priefer J, Beverungen D. Predictive maintenance on the energy distribution grid–design and evaluation of a digital industrial platform in the context of a smart service system[J]. IEEE transactions on engineering management, 2024, 71: 3641-3655.

[4] Agata Y, Tanaka T, Teshima T, et al. Intelligent solution TOMONI® for advanced maintenance and operation of critical infrastructure[J]. Mitsubishi Heavy Industries Technical Review, 2022, 59(3): 7-8.

[5] Yan W, Liu H, Han B. Industry–university–research knowledge flow in energy subjects: evolution of network structure in collaborative photovoltaic innovations[J]. Frontiers in Energy Research, 2023, 11: 1198998.

[6] Liu Yuqin, She Daoming. A Preliminary Exploration of Teaching Method Reform for Application-Oriented Courses under the Background of "Emerging Engineering Education" — Taking the Course "Principles and Applications of Microcontrollers" as an Example[J]. Light Industry Science and Technology, 2022, 38(05): 153-155+191.

[7] Zhang Jiarui, Wang Wei, Lin Xing Research on Blended Teaching Practice Based on BOPPPS and PBL - Taking Linux Programming as an Example [J]. Information and Computer, 2025 (21): 215-217.

[8] Liu Bo, Zhai Wensong. Research and Application of Artificial Intelligence Technology in Power Equipment Operation and Maintenance[J]. Industrial Science and Technology Innovation, 2024, 6(04): 47-50.