Advancing Distributed AC Optimal Power Flow for Integrated Transmission-Distribution Systems

IF 6.7 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2025-01-09 DOI:10.1109/TNSE.2025.3526206

Xinliang Dai;Junyi Zhai;Yuning Jiang;Yi Guo;Colin N. Jones;Veit Hagenmeyer

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引用次数: 0

Abstract

This paper introduces a distributed operational solution for integrated transmission-distribution (ITD) system management. A fundamental challenge in designing distributed approaches for AC optimal power flow (OPF) problems in ITD systems is the nonconvexity and nonlinearity of the optimization problems for both transmission and distribution systems. To tackle the challenges, our research introduces an enhanced version of the Augmented Lagrangian based Alternating Direction Inexact Newton method (aladin), which incorporates a second-order correction strategy and convexification. The former improves the algorithm's ability to follow curved trajectories effectively with minimal additional computational demand, while the latter simplifies the decoupled subproblems without introducing the combinatory complexity typically associated with additional inequality constraints. 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.

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来源期刊

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.