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Title: Hierarchical Distributed Voltage Regulation in Networked Autonomous Grids

Abstract

We propose a novel algorithm to solve optimal power flow (OPF) that aims at dispatching controllable distributed energy resources (DERs) for voltage regulation at minimum cost. The proposed algorithm features unprecedented scalability to large distribution networks by utilizing an information structure based on networked autonomous grids (AGs). Specifically, each AG is a subtree of a large distribution network that has a tree topology. The topology and line parameters of each AG are known only to a regional coordinator (RC) that is responsible for communicating with and dispatching the DERs within this AG. The reduced network, where each AG is treated as a node, is managed by a central coordinator (CC), which knows the topology and line parameters of the reduced network only and communicates with all the RCs. We jointly explore this information structure and the structure of the linearized distribution power flow (LinDistFlow) model to derive a hierarchical, distributed implementation of the primal-dual gradient algorithm that solves the OPF. The proposed implementation significantly reduces the computation burden compared to the centrally coordinated implementation of the primal-dual algorithm. Numerical results on a 4,521-node test feeder show that the proposed hierarchical distributed algorithm can achieve an improvement of more than tenfoldmore » in the speed of convergence compared to the centrally coordinated primal-dual algorithm.« less

Authors:
 [1];  [2];  [3]; ORCiD logo [1];  [1];  [2]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
  2. University of Colorado
  3. New York University
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
OSTI Identifier:
1569445
Report Number(s):
NREL/CP-5D00-75056
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the 2019 American Control Conference (ACC), 10-12 July 2019, Philadelphia, Pennsylvania
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; hierarchical; distributed; voltage; regulation; autonomous grid

Citation Formats

Zhou, Xinyang, Liu, Zhiyuan, Wang, Wenbo, Zhao, Changhong, Ding, Fei, and Chen, Lijun. Hierarchical Distributed Voltage Regulation in Networked Autonomous Grids. United States: N. p., 2019. Web.
Zhou, Xinyang, Liu, Zhiyuan, Wang, Wenbo, Zhao, Changhong, Ding, Fei, & Chen, Lijun. Hierarchical Distributed Voltage Regulation in Networked Autonomous Grids. United States.
Zhou, Xinyang, Liu, Zhiyuan, Wang, Wenbo, Zhao, Changhong, Ding, Fei, and Chen, Lijun. Thu . "Hierarchical Distributed Voltage Regulation in Networked Autonomous Grids". United States.
@article{osti_1569445,
title = {Hierarchical Distributed Voltage Regulation in Networked Autonomous Grids},
author = {Zhou, Xinyang and Liu, Zhiyuan and Wang, Wenbo and Zhao, Changhong and Ding, Fei and Chen, Lijun},
abstractNote = {We propose a novel algorithm to solve optimal power flow (OPF) that aims at dispatching controllable distributed energy resources (DERs) for voltage regulation at minimum cost. The proposed algorithm features unprecedented scalability to large distribution networks by utilizing an information structure based on networked autonomous grids (AGs). Specifically, each AG is a subtree of a large distribution network that has a tree topology. The topology and line parameters of each AG are known only to a regional coordinator (RC) that is responsible for communicating with and dispatching the DERs within this AG. The reduced network, where each AG is treated as a node, is managed by a central coordinator (CC), which knows the topology and line parameters of the reduced network only and communicates with all the RCs. We jointly explore this information structure and the structure of the linearized distribution power flow (LinDistFlow) model to derive a hierarchical, distributed implementation of the primal-dual gradient algorithm that solves the OPF. The proposed implementation significantly reduces the computation burden compared to the centrally coordinated implementation of the primal-dual algorithm. Numerical results on a 4,521-node test feeder show that the proposed hierarchical distributed algorithm can achieve an improvement of more than tenfold in the speed of convergence compared to the centrally coordinated primal-dual algorithm.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {8}
}

Conference:
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