A Consensus-Based Distributed Primal-Dual Perturbed Subgradient Algorithm for DC OPF

被引:0
|
作者
Yang, Zhongyuan [1 ]
Zou, Bin [1 ]
Zhang, Junmeng [1 ]
机构
[1] Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai 200072, Peoples R China
关键词
Distributed optimization; Multi-agent systems; Consensus protocols; DC optimal power flow; Smart grid;
D O I
10.1007/978-981-10-6364-0_50
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, an consensus-based distributed primal-dual perturbed subgradient algorithm is proposed for the DC Optimal Power Flow (OPF) problem. The algorithm is based on a double layer multi-agent structure, in which each generator bus and load bus in electric power grid is viewed as bus agent and connects with the grid by a network agent. In particular, network agents employ the average consensus method to estimate the global variables which are necessary for bus agents to update their generation using a local primal-dual perturbed subgradient method. The proposed approach is fully distributed and realizes the privacy protection. The employment of primal-dual perturbation method ensuring the convergence of the algorithm. Simulation results demonstrate the effectiveness of the proposed distributed algorithm.
引用
收藏
页码:497 / 508
页数:12
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