Prompts of Large Language Model for Commanding Power Grid Operation

Abstract

Large Language Models (LLMs) like ChatGPT can assist people’s general workflows, where the prompt is necessary to inspire the potential of LLMs to solve problems from specified or professional domains like robotics. In the electrical engineering subject or the electric power utility industry, experienced operators and professional experts monitor power grid operation statuses and interact with the grid via human commands on the screen, and components in the grid execute the commands to keep the complex grid safe and economical operation. In this process, human experts edit commands to operate the corresponding software. Human commands are the natural language that the LLM can process. The power grid is composed of generation, transmission, distribution, and other components. Therefore, we redesign the human-computer interaction frame between practitioners and the grid via recurrent prompts to apply the LLM to generate computer programming instructions from the multi-step natural language commands. The programming instruction is executed on system components after being confirmed or revised by human experts, and the quality of generated programs will be gradually improved through human feedback. The idea of this study is originally inspired by studies on controlling individual robotic components by ChatGPT. In the future, we will apply the designed prompt templates to drive the general LLM to generate desired samples which could be used to train an LLM professional in the domain knowledge of electrical engineering to operate multiple types of software for power grid operators.