Advancing Distributed AC Optimal Power Flow for Integrated Transmission-Distribution Systems
Xinliang Dai, Junyi Zhai, Yuning Jiang, Yi Guo, Colin N. Jones, Veit Hagenmeyer
TL;DR
This paper tackles privacy-preserving coordination of integrated transmission-distribution (ITD) systems under the nonconvex AC OPF, proposing a refined ALADIN-based distributed solver with a second-order correction (aladincor). By combining affine consensus modeling, selective conic relaxation for distribution subproblems, and a corrective step that offsets linearization errors, the approach achieves local quadratic convergence and robust performance across diverse ITD topologies. Theoretical analysis establishes convergence guarantees, while extensive case studies demonstrate faster convergence, better scalability, and higher accuracy than competing methods, including two-layer DCC and standard ALADIN. The proposed framework enables secure, efficient, and adaptable ITD optimization with minimal data sharing, offering a practical pathway for real-time, privacy-aware power-system operation.
Abstract
This paper introduces a distributed operational solution for coordinating integrated transmission-distribution (ITD) systems regarding data privacy. To tackle the nonconvex challenges of AC optimal power flow (OPF) problems, our research proposes an enhanced version of the Augmented Lagrangian based Alternating Direction Inexact Newton method (ALADIN). This proposed framework incorporates a second-order correction strategy and convexification, thereby enhancing numerical robustness and computational efficiency. The theoretical studies demonstrate that the proposed distributed algorithm operates the ITD systems with a local quadratic convergence guarantee. Extensive simulations on various ITD configurations highlight the superior performance of our distributed approach in terms of convergence speed, computational efficiency, scalability, and adaptability.