Large language models (LLMs) as ChatBots have drawn remarkable attention thanks to their versatile capability in natural language processing as well as in a wide range of tasks. While there has been great enthusiasm toward adopting such foundational model-based artificial intelligence tools in all sectors possible, the capabilities and limitations of such LLMs in improving the operation of the electric energy sector need to be explored, and this commentary identifies fruitful directions in this regard. Key future research directions include data collection systems for fine-tuning LLMs, embedding power system-specific tools in the LLMs, and retrieval augmented generation (RAG)-based knowledge pool to improve the quality of LLM responses and LLMs in safety-critical use cases.

像聊天机器人这样的大型语言模型（LLMs）由于其在自然语言处理以及广泛任务中的多功能能力而引起了人们的广泛关注。虽然人们对在所有可能的领域采用这种基于模型的基础人工智能工具抱有极大的热情，但需要探索这种LLMs在改善电力能源行业运营方面的能力和局限性，这评论指出了这方面富有成果的方向。未来的主要研究方向包括用于微调LLMs的数据收集系统、在LLMs中嵌入电力系统特定工具以及基于检索增强生成（RAG）的知识库以改进安全关键用例中 LLM 响应和 LLMs 的质量。