Developing a Robust Expansion Planning Approach for Transmission Networks and Privately-Owned Renewable Sources

Power system restructuring has changed transmission expansion planning (TEP) and caused many complications due to conflicting and contradictory objectives. The transmission capacity expansion would significantly affect the revenue of investor-owned renewable energy sources (RESs). Thus, the investme...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE access 2023, Vol.11, p.76046-76058
Hauptverfasser: Peng, Li, Zabihi, Alireza, Azimian, Mahdi, Shirvani, Hadis, Shahnia, Farhad
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 76058
container_issue
container_start_page 76046
container_title IEEE access
container_volume 11
creator Peng, Li
Zabihi, Alireza
Azimian, Mahdi
Shirvani, Hadis
Shahnia, Farhad
description Power system restructuring has changed transmission expansion planning (TEP) and caused many complications due to conflicting and contradictory objectives. The transmission capacity expansion would significantly affect the revenue of investor-owned renewable energy sources (RESs). Thus, the investment decisions on merchant RESs must be considered in the TEP studies conducted by the transmission system operator (TSO). In this regard, this paper aims to propose a multi-objective co-planning of investment in transmission networks and merchant RESs with three objective functions: minimizing the investment cost of newly deployed transmission lines, minimizing transmission congestion cost, and minimizing load curtailment in N-1 conditions. Moreover, the TSO guarantees a desirable rate of return for private investors to finance renewable energy projects. Further, a robust optimization (RO) technique is employed to cope with the uncertainties associated with demand and renewable energy production. Also, a posteriori multi-objective optimization algorithm, i.e., the non-dominated sorting genetic algorithm (NSGAII), is applied to solve the advanced optimization problem, followed by the fuzzy min-max method to acquire the final optimal solution. Finally, the IEEE RTS 24-bus test system is utilized to demonstrate the effectiveness and applicability of the suggested approach.
doi_str_mv 10.1109/ACCESS.2022.3226695
format Article
fullrecord <record><control><sourceid>proquest_ieee_</sourceid><recordid>TN_cdi_ieee_primary_9970312</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9970312</ieee_id><doaj_id>oai_doaj_org_article_f7e39dda8fbf40c7a4e27505ecace2f6</doaj_id><sourcerecordid>2843142804</sourcerecordid><originalsourceid>FETCH-LOGICAL-c408t-fc283aa55a1b3b2e6068ad729690376280987d0733636202b7f9ed0057c72f553</originalsourceid><addsrcrecordid>eNpNUU1P3DAQjVArFQG_gIulnrN17NiOj6vttiAhQCw9WxNnDNkGO7WzLPx7vASh-jLWzHtvPl5RnFd0UVVU_1iuVuvNZsEoYwvOmJRaHBXHrJK65ILLL__9vxVnKW1pfk1OCXVchJ_4jEMYe_9AgNyFdpcmsn4Zwac-eHI7gPeH2nIcYwD7SFyI5D7m8lOf3iHXOO1D_JsI-I7cxv4ZJhxey5u9x47cocc9tAOSTdhFi-m0-OpgSHj2EU-KP7_W96uL8urm9-VqeVXamjZT6SxrOIAQULW8ZSipbKBTTEtNuZKsobpRHVWcSy7z5q1yGjtKhbKKOSH4SXE563YBtmaM_RPEVxOgN--JEB8MxKm3AxqnkOuug8a1rqZWQY1MCSrQgkXmZNb6PmvlE_zbYZrMNi_j8_iGNTWv6jxOnVF8RtkYUoroPrtW1ByMMrNR5mCU-TAqs85nVo-InwytFeUV428Tho-O</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2843142804</pqid></control><display><type>article</type><title>Developing a Robust Expansion Planning Approach for Transmission Networks and Privately-Owned Renewable Sources</title><source>IEEE Open Access Journals</source><source>DOAJ Directory of Open Access Journals</source><source>EZB-FREE-00999 freely available EZB journals</source><creator>Peng, Li ; Zabihi, Alireza ; Azimian, Mahdi ; Shirvani, Hadis ; Shahnia, Farhad</creator><creatorcontrib>Peng, Li ; Zabihi, Alireza ; Azimian, Mahdi ; Shirvani, Hadis ; Shahnia, Farhad</creatorcontrib><description>Power system restructuring has changed transmission expansion planning (TEP) and caused many complications due to conflicting and contradictory objectives. The transmission capacity expansion would significantly affect the revenue of investor-owned renewable energy sources (RESs). Thus, the investment decisions on merchant RESs must be considered in the TEP studies conducted by the transmission system operator (TSO). In this regard, this paper aims to propose a multi-objective co-planning of investment in transmission networks and merchant RESs with three objective functions: minimizing the investment cost of newly deployed transmission lines, minimizing transmission congestion cost, and minimizing load curtailment in N-1 conditions. Moreover, the TSO guarantees a desirable rate of return for private investors to finance renewable energy projects. Further, a robust optimization (RO) technique is employed to cope with the uncertainties associated with demand and renewable energy production. Also, a posteriori multi-objective optimization algorithm, i.e., the non-dominated sorting genetic algorithm (NSGAII), is applied to solve the advanced optimization problem, followed by the fuzzy min-max method to acquire the final optimal solution. Finally, the IEEE RTS 24-bus test system is utilized to demonstrate the effectiveness and applicability of the suggested approach.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2022.3226695</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Alternative energy sources ; Costs ; Financing ; Genetic algorithms ; Investment ; Load modeling ; multiobjective ; Multiple objective analysis ; Optimization ; Planning ; private investor ; Renewable energy sources ; Renewable resources ; robust optimization ; Robustness ; Sorting algorithms ; Transmission expansion planning ; Transmission lines ; uncertainties ; Uncertainty</subject><ispartof>IEEE access, 2023, Vol.11, p.76046-76058</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c408t-fc283aa55a1b3b2e6068ad729690376280987d0733636202b7f9ed0057c72f553</citedby><cites>FETCH-LOGICAL-c408t-fc283aa55a1b3b2e6068ad729690376280987d0733636202b7f9ed0057c72f553</cites><orcidid>0000-0002-6431-5445 ; 0000-0002-8434-0525</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9970312$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,777,781,861,2096,4010,27614,27904,27905,27906,54914</link.rule.ids></links><search><creatorcontrib>Peng, Li</creatorcontrib><creatorcontrib>Zabihi, Alireza</creatorcontrib><creatorcontrib>Azimian, Mahdi</creatorcontrib><creatorcontrib>Shirvani, Hadis</creatorcontrib><creatorcontrib>Shahnia, Farhad</creatorcontrib><title>Developing a Robust Expansion Planning Approach for Transmission Networks and Privately-Owned Renewable Sources</title><title>IEEE access</title><addtitle>Access</addtitle><description>Power system restructuring has changed transmission expansion planning (TEP) and caused many complications due to conflicting and contradictory objectives. The transmission capacity expansion would significantly affect the revenue of investor-owned renewable energy sources (RESs). Thus, the investment decisions on merchant RESs must be considered in the TEP studies conducted by the transmission system operator (TSO). In this regard, this paper aims to propose a multi-objective co-planning of investment in transmission networks and merchant RESs with three objective functions: minimizing the investment cost of newly deployed transmission lines, minimizing transmission congestion cost, and minimizing load curtailment in N-1 conditions. Moreover, the TSO guarantees a desirable rate of return for private investors to finance renewable energy projects. Further, a robust optimization (RO) technique is employed to cope with the uncertainties associated with demand and renewable energy production. Also, a posteriori multi-objective optimization algorithm, i.e., the non-dominated sorting genetic algorithm (NSGAII), is applied to solve the advanced optimization problem, followed by the fuzzy min-max method to acquire the final optimal solution. Finally, the IEEE RTS 24-bus test system is utilized to demonstrate the effectiveness and applicability of the suggested approach.</description><subject>Alternative energy sources</subject><subject>Costs</subject><subject>Financing</subject><subject>Genetic algorithms</subject><subject>Investment</subject><subject>Load modeling</subject><subject>multiobjective</subject><subject>Multiple objective analysis</subject><subject>Optimization</subject><subject>Planning</subject><subject>private investor</subject><subject>Renewable energy sources</subject><subject>Renewable resources</subject><subject>robust optimization</subject><subject>Robustness</subject><subject>Sorting algorithms</subject><subject>Transmission expansion planning</subject><subject>Transmission lines</subject><subject>uncertainties</subject><subject>Uncertainty</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNpNUU1P3DAQjVArFQG_gIulnrN17NiOj6vttiAhQCw9WxNnDNkGO7WzLPx7vASh-jLWzHtvPl5RnFd0UVVU_1iuVuvNZsEoYwvOmJRaHBXHrJK65ILLL__9vxVnKW1pfk1OCXVchJ_4jEMYe_9AgNyFdpcmsn4Zwac-eHI7gPeH2nIcYwD7SFyI5D7m8lOf3iHXOO1D_JsI-I7cxv4ZJhxey5u9x47cocc9tAOSTdhFi-m0-OpgSHj2EU-KP7_W96uL8urm9-VqeVXamjZT6SxrOIAQULW8ZSipbKBTTEtNuZKsobpRHVWcSy7z5q1yGjtKhbKKOSH4SXE563YBtmaM_RPEVxOgN--JEB8MxKm3AxqnkOuug8a1rqZWQY1MCSrQgkXmZNb6PmvlE_zbYZrMNi_j8_iGNTWv6jxOnVF8RtkYUoroPrtW1ByMMrNR5mCU-TAqs85nVo-InwytFeUV428Tho-O</recordid><startdate>2023</startdate><enddate>2023</enddate><creator>Peng, Li</creator><creator>Zabihi, Alireza</creator><creator>Azimian, Mahdi</creator><creator>Shirvani, Hadis</creator><creator>Shahnia, Farhad</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7SR</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-6431-5445</orcidid><orcidid>https://orcid.org/0000-0002-8434-0525</orcidid></search><sort><creationdate>2023</creationdate><title>Developing a Robust Expansion Planning Approach for Transmission Networks and Privately-Owned Renewable Sources</title><author>Peng, Li ; Zabihi, Alireza ; Azimian, Mahdi ; Shirvani, Hadis ; Shahnia, Farhad</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c408t-fc283aa55a1b3b2e6068ad729690376280987d0733636202b7f9ed0057c72f553</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Alternative energy sources</topic><topic>Costs</topic><topic>Financing</topic><topic>Genetic algorithms</topic><topic>Investment</topic><topic>Load modeling</topic><topic>multiobjective</topic><topic>Multiple objective analysis</topic><topic>Optimization</topic><topic>Planning</topic><topic>private investor</topic><topic>Renewable energy sources</topic><topic>Renewable resources</topic><topic>robust optimization</topic><topic>Robustness</topic><topic>Sorting algorithms</topic><topic>Transmission expansion planning</topic><topic>Transmission lines</topic><topic>uncertainties</topic><topic>Uncertainty</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Peng, Li</creatorcontrib><creatorcontrib>Zabihi, Alireza</creatorcontrib><creatorcontrib>Azimian, Mahdi</creatorcontrib><creatorcontrib>Shirvani, Hadis</creatorcontrib><creatorcontrib>Shahnia, Farhad</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>IEEE access</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Peng, Li</au><au>Zabihi, Alireza</au><au>Azimian, Mahdi</au><au>Shirvani, Hadis</au><au>Shahnia, Farhad</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Developing a Robust Expansion Planning Approach for Transmission Networks and Privately-Owned Renewable Sources</atitle><jtitle>IEEE access</jtitle><stitle>Access</stitle><date>2023</date><risdate>2023</risdate><volume>11</volume><spage>76046</spage><epage>76058</epage><pages>76046-76058</pages><issn>2169-3536</issn><eissn>2169-3536</eissn><coden>IAECCG</coden><abstract>Power system restructuring has changed transmission expansion planning (TEP) and caused many complications due to conflicting and contradictory objectives. The transmission capacity expansion would significantly affect the revenue of investor-owned renewable energy sources (RESs). Thus, the investment decisions on merchant RESs must be considered in the TEP studies conducted by the transmission system operator (TSO). In this regard, this paper aims to propose a multi-objective co-planning of investment in transmission networks and merchant RESs with three objective functions: minimizing the investment cost of newly deployed transmission lines, minimizing transmission congestion cost, and minimizing load curtailment in N-1 conditions. Moreover, the TSO guarantees a desirable rate of return for private investors to finance renewable energy projects. Further, a robust optimization (RO) technique is employed to cope with the uncertainties associated with demand and renewable energy production. Also, a posteriori multi-objective optimization algorithm, i.e., the non-dominated sorting genetic algorithm (NSGAII), is applied to solve the advanced optimization problem, followed by the fuzzy min-max method to acquire the final optimal solution. Finally, the IEEE RTS 24-bus test system is utilized to demonstrate the effectiveness and applicability of the suggested approach.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/ACCESS.2022.3226695</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-6431-5445</orcidid><orcidid>https://orcid.org/0000-0002-8434-0525</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2169-3536
ispartof IEEE access, 2023, Vol.11, p.76046-76058
issn 2169-3536
2169-3536
language eng
recordid cdi_ieee_primary_9970312
source IEEE Open Access Journals; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals
subjects Alternative energy sources
Costs
Financing
Genetic algorithms
Investment
Load modeling
multiobjective
Multiple objective analysis
Optimization
Planning
private investor
Renewable energy sources
Renewable resources
robust optimization
Robustness
Sorting algorithms
Transmission expansion planning
Transmission lines
uncertainties
Uncertainty
title Developing a Robust Expansion Planning Approach for Transmission Networks and Privately-Owned Renewable Sources
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-20T11%3A59%3A48IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_ieee_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Developing%20a%20Robust%20Expansion%20Planning%20Approach%20for%20Transmission%20Networks%20and%20Privately-Owned%20Renewable%20Sources&rft.jtitle=IEEE%20access&rft.au=Peng,%20Li&rft.date=2023&rft.volume=11&rft.spage=76046&rft.epage=76058&rft.pages=76046-76058&rft.issn=2169-3536&rft.eissn=2169-3536&rft.coden=IAECCG&rft_id=info:doi/10.1109/ACCESS.2022.3226695&rft_dat=%3Cproquest_ieee_%3E2843142804%3C/proquest_ieee_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2843142804&rft_id=info:pmid/&rft_ieee_id=9970312&rft_doaj_id=oai_doaj_org_article_f7e39dda8fbf40c7a4e27505ecace2f6&rfr_iscdi=true