Collaborative Distributed AC Optimal Power Flow: A Dual Decomposition Based Algorithm  

作　　者：Zheyuan Cheng Mo-Yuen Chow 

机构地区：[1]IEEE [2]Department of Electrical and Computer Engineering,North Carolina State University

出　　处：《Journal of Modern Power Systems and Clean Energy》2021年第6期1414-1423,共10页现代电力系统与清洁能源学报（英文）

基　　金：supported by the National Science Foundation (No. CNS-1505633)。

摘　　要：We propose a dual decomposition based algorithm that solves the AC optimal power flow(ACOPF) problem in the radial distribution systems and microgrids in a collaborative and distributed manner. The proposed algorithm adopts the second-order cone program(SOCP) relaxed branch flow ACOPF model. In the proposed algorithm, bus-level agents collaboratively solve the global ACOPF problem by iteratively sharing partial variables with its 1-hop neighbors as well as carrying out local scalar computations that are derived using augmented Lagrangian and primal-dual subgradient methods. We also propose two distributed computing platforms, i. e., high-performance computing(HPC) based platform and hardware-in-theloop(HIL) testbed, to validate and evaluate the proposed algorithm. The computation and communication performances of the proposed algorithm are quantified and analyzed on typical IEEE test systems. Experimental results indicate that the proposed algorithm can be executed on a fully distributed computing structure and yields accurate ACOPF solution. Besides, the proposed algorithm has a low communication overhead.

关 键 词：Distributed convex optimization distributed en-ergy management system optimal power flow primal-dual de-composition 

分 类 号：TM744[电气工程—电力系统及自动化]