Fast Heuristic AC Power Flow Analysis with Data-Driven Enhanced Linearized Model

• Main Author: Xingpeng Li
• Format: Article
• Language: English
• Published: MDPI AG 2020-06-01
• Series: Energies
• Subjects: Data-driven; linearization; regression analysis; power flow; power system operations
• Online Access: https://www.mdpi.com/1996-1073/13/13/3308

Though<b> </b>the<b> </b>full AC power flow model can accurately represent the physical power system, the use of this model is limited in practice due to the computational complexity associated with its non-linear and non-convexity characteristics. For instance, the AC power flow model is not incorporated in the unit commitment model for practical power systems. Instead, an alternative linearized DC power flow model is widely used in today’s power system operational and planning tools. However, DC power flow model will be useless when reactive power and voltage magnitude are of concern. Therefore, a linearized AC (LAC) power flow model is needed to address this issue. This paper first introduces a traditional LAC model and then proposes an enhanced data-driven linearized AC (DLAC) model using the regression analysis technique. Numerical simulations conducted on the Tennessee Valley Authority (TVA) system demonstrate the performance and effectiveness of the proposed DLAC model.