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Title: Dynamic ADMM for Real-Time Optimal Power Flow: Preprint

Abstract

This paper considers distribution networks featuring distributed energy resources (DERs), and develops a dynamic optimization method to maximize given operational objectives in real time while adhering to relevant network constraints. The design of the dynamic algorithm is based on suitable linearizations of the AC power flow equations, and it leverages the so-called alternating direction method of multipliers (ADMM). The steps of the ADMM, however, are suitably modified to accommodate appropriate measurements from the distribution network and the DERs. With the aid of these measurements, the resultant algorithm can enforce given operational constraints in spite of inaccuracies in the representation of the AC power flows, and it avoids ubiquitous metering to gather the state of non-controllable resources. Optimality and convergence of the propose algorithm are established in terms of tracking of the solution of a convex surrogate of the AC optimal power flow problem.

Authors:
 [1];  [2];  [2]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
  2. Iowa State 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), NREL Laboratory Directed Research and Development (LDRD); USDOE Advanced Research Projects Agency - Energy (ARPA-E)
OSTI Identifier:
1423433
Report Number(s):
NREL/CP-5D00-68625
DOE Contract Number:
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the 2017 5th IEEE Global Conference on Signal and Information Processing (GlobalSIP), 11-16 November 2017, Montreal, Canada
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; distribution systems; alternating direction method of multipliers; ADMM; real-time optimization; feed-back control; distributed energy resources; DERs; power flow

Citation Formats

Dall-Anese, Emiliano, Zhang, Yijian, and Hong, Mingyi. Dynamic ADMM for Real-Time Optimal Power Flow: Preprint. United States: N. p., 2018. Web.
Dall-Anese, Emiliano, Zhang, Yijian, & Hong, Mingyi. Dynamic ADMM for Real-Time Optimal Power Flow: Preprint. United States.
Dall-Anese, Emiliano, Zhang, Yijian, and Hong, Mingyi. Fri . "Dynamic ADMM for Real-Time Optimal Power Flow: Preprint". United States. doi:. https://www.osti.gov/servlets/purl/1423433.
@article{osti_1423433,
title = {Dynamic ADMM for Real-Time Optimal Power Flow: Preprint},
author = {Dall-Anese, Emiliano and Zhang, Yijian and Hong, Mingyi},
abstractNote = {This paper considers distribution networks featuring distributed energy resources (DERs), and develops a dynamic optimization method to maximize given operational objectives in real time while adhering to relevant network constraints. The design of the dynamic algorithm is based on suitable linearizations of the AC power flow equations, and it leverages the so-called alternating direction method of multipliers (ADMM). The steps of the ADMM, however, are suitably modified to accommodate appropriate measurements from the distribution network and the DERs. With the aid of these measurements, the resultant algorithm can enforce given operational constraints in spite of inaccuracies in the representation of the AC power flows, and it avoids ubiquitous metering to gather the state of non-controllable resources. Optimality and convergence of the propose algorithm are established in terms of tracking of the solution of a convex surrogate of the AC optimal power flow problem.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Feb 23 00:00:00 EST 2018},
month = {Fri Feb 23 00:00:00 EST 2018}
}

Conference:
Other availability
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