A Trustworthy Framework of Artificial Intelligence for Power Grid Dispatching Systems
Kelly Zhang, Peidong Xu, Tianlu Gao, Jun Jason Zhang · 2021 IEEE 1st International Conference on Digital Twins and Parallel Intelligence (DTPI) · 2021
With the widespread application of artificial intelligence (AI) technologies in power systems, the properties of lack of reliability and transparency for AI technologies have revealed gradually. Here, how to build a trustworthy-AI framework based on the power system is the focus. Due to the multidimensional and heterogeneous information of power grid data, the heterogeneous graph attention network (HGAT) model of power grid dispatching is established, and the corresponding explainer (HGAT-Explainer) for the model of power equipment faults is proposed to provide more favorable support for the trustworthy-AI systems.