The rapid digitalization of power systems has led to a significant increase in coding tasks for power engineers. This research article explores how ChatGPT, an advanced AI language model, can assist power engineers and researchers in a range of coding tasks. From simple to complex, we present three case studies to illustrate the benefits of ChatGPT in various coding scenarios. For routine tasks such as daily unit commitment, ChatGPT can increase efficiency by directly generating batch number of codes and reducing repetitive programming and debugging time for power engineers. For complex problems such as decentralized optimization of mul-ti-vector energy systems, ChatGPT can reduce the learning cost of power engineers on problem formulation and the choice of numerical solvers. For new problems without readily avaliable solutions such as ultra-fast unit commitment, ChatGPT can organize technology roadmap, gen-erate data and develop model and code. Furthermore, this paper discuss generic prompt ap-proaches for different tasks in power systems, providing insights for power engineers and re-searchers seeking to harness ChatGPT in terms of auto coding, new knowledge learning and new problem solving. The findings demonstrate the potential of ChatGPT as a powerful tool in the domain of power system engineering.

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