数智化转型为破解传统新能源电站运维模式局限性提供了新路径。研究系统阐述了全生命周期数据感知与融合技术、人工智能发电效能预测与优化模型在新能源发电领域的应用机制，揭示了数智化技术通过提升可再生能源资源评估精度、实现设备预测性维护、促进源网荷储协同优化，有效平抑发电波动性，提高电能消纳水平的作用机理。同时，构建数据驱动的产业链协同生态、培养复合型科技人才、加强知识产权布局与标准化建设是推动数智化转型的关键举措，对促进新能源产业高质量发展具有重要实践意义。
The research systematically expounds the application mechanism of full life cycle data perception and
fusion technology, as well as artificial intelligence-based power generation efficiency prediction and optimization
models in the field of new energy power generation. It reveals the functional mechanism of digital intelligence
technology in enhancing the accuracy of renewable energy resource assessment, achieving predictive maintenance of
equipment, promoting the coordinated optimization of source-grid-load-storage, effectively mitigating the volatility of
power generation, and improving the level of power consumption.
