Multi-source distributed optimization strategy for smart distribution systems based on local reweighted method

被引：0
|
作者：
Li J. [1 ]
Shen C. [1 ]
Wei W. [2 ]
Dai W. [1 ]
机构：
[1] School of Information & Electronic Engineering, Zhejiang Gongshang University, Hangzhou
[2] College of Electrical Engineering, Zhejiang University, Hangzhou
来源：
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2016年 / 40卷 / 21期
基金：
中国国家自然科学基金;
关键词：
Distributed generator (DG); Distributed optimization; Linear conic programming; Optimal power flow; Smart distribution system;
D O I：
10.7500/AEPS20160104006
中图分类号：
学科分类号：
摘要：
In order to maximize the utilization of large-scale intermittent renewable energy, this paper proposes an area-distributed strategy for active and reactive power optimization in the smart distribution system with a large number of distributed generators. Firstly, the linear conic programming of the multi-period optimal power flow is developed. Then, some ancillary variables at the junction bus are introduced to decompose the distribution system into several separate subsystems. Moreover, the distributed optimization algorithm based on the local reweighted augmented Lagrangian method is proposed to realize the active and reactive power optimization in the whole network. Each subsystem only exchanges partial messages with its neighbors and solves the individual sub-optimization problem by itself in fully distributed manner without global coordinators. Communication complexity is reduced by the algorithm, and the independence of each subsystem is retained as much as possible. The simulation results show that the proposed strategy is of high calculating efficiency and good performance on convergence. © 2016 Automation of Electric Power Systems Press.
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页码：146 / 153
页数：7
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