Distributed Optimal Power Flow Algorithm for Radial Networks, I: Balanced Single Phase Case

The optimal power flow (OPF) problem determines a network operating point that minimizes a certain objective such as generation cost or power loss. Traditionally, OPF is solved in a centralized manner. With increasing penetration of renewable energy in distribution system, we need faster and distrib...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on smart grid 2018-01, Vol.9 (1), p.111-121
Hauptverfasser: Qiuyu Peng, Low, Steven H.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 121
container_issue 1
container_start_page 111
container_title IEEE transactions on smart grid
container_volume 9
creator Qiuyu Peng
Low, Steven H.
description The optimal power flow (OPF) problem determines a network operating point that minimizes a certain objective such as generation cost or power loss. Traditionally, OPF is solved in a centralized manner. With increasing penetration of renewable energy in distribution system, we need faster and distributed solutions for real-time feedback control. This is difficult due to the nonlinearity of the power flow equations. In this paper, we propose a solution for balanced radial networks. It exploits recent results that suggest solving for a globally optimal solution of OPF over a radial network through the second-order cone program relaxation. Our distributed algorithm is based on alternating direction method of multiplier (ADMM), but unlike standard ADMM-based distributed OPF algorithms that require solving optimization subproblems using iterative method, our decomposition allows us to derive closed form solutions for these subproblems, greatly speeding up each ADMM iteration. We illustrate the scalability of the proposed algorithm by simulating it on a real-world 2065-bus distribution network.
doi_str_mv 10.1109/TSG.2016.2546305
format Article
fullrecord <record><control><sourceid>crossref_RIE</sourceid><recordid>TN_cdi_crossref_primary_10_1109_TSG_2016_2546305</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>7440858</ieee_id><sourcerecordid>10_1109_TSG_2016_2546305</sourcerecordid><originalsourceid>FETCH-LOGICAL-c356t-c1131d9a6d22546f1aa3749396e640fc34ce5f9336c6974b06366575f3a95ed33</originalsourceid><addsrcrecordid>eNo9UMFOAjEQbYwmEuRu4qXx7GK703apN0RBEiJE8OShKd0uVBeWtDXEv7cEwmQyM8m8N3nzELqlpEspkY-L-aibEyq6OWcCCL9ALSqZzIAIenmeOVyjTgjfJAUAiFy20NeLC9G75W-0JZ7uotvoGs-avfV4WDd73K9XjXdxvcFV4_GHLl3av9u4b_xPeMDjJ_ysa701iT1321Vt8Wytg8WDVG7QVaXrYDun3kafw9fF4C2bTEfjQX-SGeAiZoZSoKXUoswP8iuqNRRMghRWMFIZYMbySibBRsiCLYkAIXjBK9CS2xKgje6Pd5sQnQrGRWvWptlurYmKcpZSJhA5goxvQvC2UjufnvV_ihJ1MFElE9XBRHUyMVHujhRnrT3DC8ZIj_fgH53ea2k</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Distributed Optimal Power Flow Algorithm for Radial Networks, I: Balanced Single Phase Case</title><source>IEEE Electronic Library (IEL)</source><creator>Qiuyu Peng ; Low, Steven H.</creator><creatorcontrib>Qiuyu Peng ; Low, Steven H. ; California Inst. of Technology (CalTech), Pasadena, CA (United States) ; Los Alamos National Lab. (LANL), Los Alamos, NM (United States)</creatorcontrib><description>The optimal power flow (OPF) problem determines a network operating point that minimizes a certain objective such as generation cost or power loss. Traditionally, OPF is solved in a centralized manner. With increasing penetration of renewable energy in distribution system, we need faster and distributed solutions for real-time feedback control. This is difficult due to the nonlinearity of the power flow equations. In this paper, we propose a solution for balanced radial networks. It exploits recent results that suggest solving for a globally optimal solution of OPF over a radial network through the second-order cone program relaxation. Our distributed algorithm is based on alternating direction method of multiplier (ADMM), but unlike standard ADMM-based distributed OPF algorithms that require solving optimization subproblems using iterative method, our decomposition allows us to derive closed form solutions for these subproblems, greatly speeding up each ADMM iteration. We illustrate the scalability of the proposed algorithm by simulating it on a real-world 2065-bus distribution network.</description><identifier>ISSN: 1949-3053</identifier><identifier>EISSN: 1949-3061</identifier><identifier>DOI: 10.1109/TSG.2016.2546305</identifier><identifier>CODEN: ITSGBQ</identifier><language>eng</language><publisher>United States: IEEE</publisher><subject>Closed-form solutions ; Convergence ; Distributed algorithms ; Engineering ; Indexes ; Mathematical model ; nonlinear systems ; Optimization ; Power distribution ; power system control ; Scalability</subject><ispartof>IEEE transactions on smart grid, 2018-01, Vol.9 (1), p.111-121</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c356t-c1131d9a6d22546f1aa3749396e640fc34ce5f9336c6974b06366575f3a95ed33</citedby><cites>FETCH-LOGICAL-c356t-c1131d9a6d22546f1aa3749396e640fc34ce5f9336c6974b06366575f3a95ed33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/7440858$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>230,314,776,780,792,881,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/7440858$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttps://www.osti.gov/biblio/1541549$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Qiuyu Peng</creatorcontrib><creatorcontrib>Low, Steven H.</creatorcontrib><creatorcontrib>California Inst. of Technology (CalTech), Pasadena, CA (United States)</creatorcontrib><creatorcontrib>Los Alamos National Lab. (LANL), Los Alamos, NM (United States)</creatorcontrib><title>Distributed Optimal Power Flow Algorithm for Radial Networks, I: Balanced Single Phase Case</title><title>IEEE transactions on smart grid</title><addtitle>TSG</addtitle><description>The optimal power flow (OPF) problem determines a network operating point that minimizes a certain objective such as generation cost or power loss. Traditionally, OPF is solved in a centralized manner. With increasing penetration of renewable energy in distribution system, we need faster and distributed solutions for real-time feedback control. This is difficult due to the nonlinearity of the power flow equations. In this paper, we propose a solution for balanced radial networks. It exploits recent results that suggest solving for a globally optimal solution of OPF over a radial network through the second-order cone program relaxation. Our distributed algorithm is based on alternating direction method of multiplier (ADMM), but unlike standard ADMM-based distributed OPF algorithms that require solving optimization subproblems using iterative method, our decomposition allows us to derive closed form solutions for these subproblems, greatly speeding up each ADMM iteration. We illustrate the scalability of the proposed algorithm by simulating it on a real-world 2065-bus distribution network.</description><subject>Closed-form solutions</subject><subject>Convergence</subject><subject>Distributed algorithms</subject><subject>Engineering</subject><subject>Indexes</subject><subject>Mathematical model</subject><subject>nonlinear systems</subject><subject>Optimization</subject><subject>Power distribution</subject><subject>power system control</subject><subject>Scalability</subject><issn>1949-3053</issn><issn>1949-3061</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9UMFOAjEQbYwmEuRu4qXx7GK703apN0RBEiJE8OShKd0uVBeWtDXEv7cEwmQyM8m8N3nzELqlpEspkY-L-aibEyq6OWcCCL9ALSqZzIAIenmeOVyjTgjfJAUAiFy20NeLC9G75W-0JZ7uotvoGs-avfV4WDd73K9XjXdxvcFV4_GHLl3av9u4b_xPeMDjJ_ysa701iT1321Vt8Wytg8WDVG7QVaXrYDun3kafw9fF4C2bTEfjQX-SGeAiZoZSoKXUoswP8iuqNRRMghRWMFIZYMbySibBRsiCLYkAIXjBK9CS2xKgje6Pd5sQnQrGRWvWptlurYmKcpZSJhA5goxvQvC2UjufnvV_ihJ1MFElE9XBRHUyMVHujhRnrT3DC8ZIj_fgH53ea2k</recordid><startdate>201801</startdate><enddate>201801</enddate><creator>Qiuyu Peng</creator><creator>Low, Steven H.</creator><general>IEEE</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>OTOTI</scope></search><sort><creationdate>201801</creationdate><title>Distributed Optimal Power Flow Algorithm for Radial Networks, I: Balanced Single Phase Case</title><author>Qiuyu Peng ; Low, Steven H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c356t-c1131d9a6d22546f1aa3749396e640fc34ce5f9336c6974b06366575f3a95ed33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Closed-form solutions</topic><topic>Convergence</topic><topic>Distributed algorithms</topic><topic>Engineering</topic><topic>Indexes</topic><topic>Mathematical model</topic><topic>nonlinear systems</topic><topic>Optimization</topic><topic>Power distribution</topic><topic>power system control</topic><topic>Scalability</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Qiuyu Peng</creatorcontrib><creatorcontrib>Low, Steven H.</creatorcontrib><creatorcontrib>California Inst. of Technology (CalTech), Pasadena, CA (United States)</creatorcontrib><creatorcontrib>Los Alamos National Lab. (LANL), Los Alamos, NM (United States)</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>OSTI.GOV</collection><jtitle>IEEE transactions on smart grid</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Qiuyu Peng</au><au>Low, Steven H.</au><aucorp>California Inst. of Technology (CalTech), Pasadena, CA (United States)</aucorp><aucorp>Los Alamos National Lab. (LANL), Los Alamos, NM (United States)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Distributed Optimal Power Flow Algorithm for Radial Networks, I: Balanced Single Phase Case</atitle><jtitle>IEEE transactions on smart grid</jtitle><stitle>TSG</stitle><date>2018-01</date><risdate>2018</risdate><volume>9</volume><issue>1</issue><spage>111</spage><epage>121</epage><pages>111-121</pages><issn>1949-3053</issn><eissn>1949-3061</eissn><coden>ITSGBQ</coden><abstract>The optimal power flow (OPF) problem determines a network operating point that minimizes a certain objective such as generation cost or power loss. Traditionally, OPF is solved in a centralized manner. With increasing penetration of renewable energy in distribution system, we need faster and distributed solutions for real-time feedback control. This is difficult due to the nonlinearity of the power flow equations. In this paper, we propose a solution for balanced radial networks. It exploits recent results that suggest solving for a globally optimal solution of OPF over a radial network through the second-order cone program relaxation. Our distributed algorithm is based on alternating direction method of multiplier (ADMM), but unlike standard ADMM-based distributed OPF algorithms that require solving optimization subproblems using iterative method, our decomposition allows us to derive closed form solutions for these subproblems, greatly speeding up each ADMM iteration. We illustrate the scalability of the proposed algorithm by simulating it on a real-world 2065-bus distribution network.</abstract><cop>United States</cop><pub>IEEE</pub><doi>10.1109/TSG.2016.2546305</doi><tpages>11</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 1949-3053
ispartof IEEE transactions on smart grid, 2018-01, Vol.9 (1), p.111-121
issn 1949-3053
1949-3061
language eng
recordid cdi_crossref_primary_10_1109_TSG_2016_2546305
source IEEE Electronic Library (IEL)
subjects Closed-form solutions
Convergence
Distributed algorithms
Engineering
Indexes
Mathematical model
nonlinear systems
Optimization
Power distribution
power system control
Scalability
title Distributed Optimal Power Flow Algorithm for Radial Networks, I: Balanced Single Phase Case
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-09T14%3A24%3A52IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-crossref_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Distributed%20Optimal%20Power%20Flow%20Algorithm%20for%20Radial%20Networks,%20I:%20Balanced%20Single%20Phase%20Case&rft.jtitle=IEEE%20transactions%20on%20smart%20grid&rft.au=Qiuyu%20Peng&rft.aucorp=California%20Inst.%20of%20Technology%20(CalTech),%20Pasadena,%20CA%20(United%20States)&rft.date=2018-01&rft.volume=9&rft.issue=1&rft.spage=111&rft.epage=121&rft.pages=111-121&rft.issn=1949-3053&rft.eissn=1949-3061&rft.coden=ITSGBQ&rft_id=info:doi/10.1109/TSG.2016.2546305&rft_dat=%3Ccrossref_RIE%3E10_1109_TSG_2016_2546305%3C/crossref_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=7440858&rfr_iscdi=true