Development and Application of Post-Evaluation System for the Entire Life Cycle of New Energy Projects

To comprehensively and objectively assess the advantages and disadvantages of renewable energy projects, enhance operational efficiency, and address issues during operation, this paper proposes the development of a postevaluation software system for renewable energy projects. This system is based on large language models and integrates multiple technologies to achieve a thorough and objective post-evaluation of the entire project lifecycle. The system consists of three main components: PaddleOCR for text recognition and classification, RAG and AI Flow-based information extraction, and NLG for report generation. PaddleOCR is used to recognize and classify text data, which is then transmitted to the information extraction module. The key information is extracted using RetrievalAugmented Generation (RAG) technology and an AI workflow orchestration system based on large language models. Finally, the key information is visualized and automatically generated into a report. The renewable energy project post-evaluation software system, through technological innovation and process optimization, enhances the efficiency and accuracy of project evaluation, providing strong technical support for the renewable energy industry. The successful implementation of this system is not only applicable to the renewable energy sector but also holds broad cross-industry application potential.