A Real-Time Alternating Direction Method of Multipliers Algorithm for Nonconvex Optimal Power Flow Problem

• Published in: IEEE transactions on industry applications Vol. 57; no. 1; pp. 70 - 82
• Main Authors: Lu, Xi, Yin, Hao, Xia, Shiwei, Zhang, Dongying, Shahidehpour, Mohammad, Zhang, Xian, Ding, Tao
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Alternating direction method of multipliers; Basic converters; Convex functions; Distributed algorithms; Electronic devices; Load flow; Minimization; Multipliers; optimal power flow (OPF); Optimization; Power flow; proximal alternating minimization; Real time; real-time operation; Real-time systems; Scheduling
• ISSN: 0093-9994; 1939-9367
• DOI: 10.1109/TIA.2020.3029549

The high penetration rate of smart devices such as storage elements brings new challenges to the optimal power flow (OPF) problem in power systems, which is generally nonconvex and difficult to be solved in real time. This article proposes a set of two fully distributed algorithms by combining the alternating direction method of multipliers and proximal alternating minimization techniques. The first one is a basic distributed algorithm for offline scheduling of 24-h ahead OPF. The other extended one is the warm-starting algorithm by using the offline scheduling solution as the initial point, and the warm-starting algorithm can get converged faster than the basic algorithm. Both algorithms aim to provide a highly feasible solution for the nonconvex OPF problem, and simulation conducted on four radial power systems with batteries has validated the performance of these two algorithms.