To address the issues of low efficiency and insufficient standardization in renewable energy design document preparation, this paper designs and implements an automated renewable energy design document generation tool. First, following the design methodology of the common information model (CIM), a renewable energy design document information model is constructed, covering cross-disciplinary elements such as renewable energy generation systems, primary electrical systems, and secondary electrical systems. Second, to facilitate future web-based extensions, the renewable energy design document information model is designed in JSON format to create a project configuration file. Concurrently, chapter elements of renewable energy design documents are also structured in JSON format to form a document template configuration file, which uses curly braces as placeholders to reference information from the project configuration file. Finally, a recursive parsing algorithm is implemented for multi-level placeholder substitution, combined with dynamic expression evaluation techniques to handle operations such as sum/len. The integration of the python-docx library and GPT APIs enables automated technical document generation. Experimental results demonstrate that this tool significantly reduces document preparation time and minimizes errors.