A Review of Data-Driven Methods for Power Flow Analysis

This paper presents a comprehensive review of the existing methodologies of data-driven power flow analysis. It begins by discussing the fundamental concepts of power flow analysis and highlighting the challenges faced by conventional methods in solving power flow. Subsequently, it presents the key principles and techniques underlying data-driven approaches. Then, it overviews and classifies different machine learning models that have been employed in the literature to solve the power flow problem. Further, the challenges faced by these approaches in solving the power flow are explored. Finally, the paper concludes by discussing future research directions and potential advancements in data-driven approaches in power flow solutions.