Community Resilience Optimization Subject to Power Flow Constraints in Cyber-Physical-Social Systems
This article develops a community resilience optimization method subject to power flow constraints in the cyber-physical-social systems in power engineering, which is solved using a multiagent-based algorithm. The tool that makes the nexus between the electric generation on the physical side and con...
Saved in:
Published in | IEEE systems journal Vol. 17; no. 2; pp. 1 - 12 |
---|---|
Main Authors | , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.06.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | This article develops a community resilience optimization method subject to power flow constraints in the cyber-physical-social systems in power engineering, which is solved using a multiagent-based algorithm. The tool that makes the nexus between the electric generation on the physical side and consumers and prosumers on the social side is the power flow algorithm. Specifically, the levels of emotion, empathy, cooperation, and the physical health of the consumers, prosumers are modeled in the proposed community resilience optimization approach while accounting for the electric power system constraints and their impact on the critical loads, which include hospitals, shelters, and gas stations, to name a few. The optimization accounts for the fact that the level of satisfaction of the society, the living standards, and the social well-being are depended on the supply of energy, including electricity. Evidently, the lack of electric energy resulting from load shedding has an impact on both the mental and the psychical quality of life, which in turn affects the community resilience. The developed constrained community resilience optimization method is applied to two case studies, including a two-area 6-buses system and a modified IEEE RTS 24-bus system. |
---|---|
AbstractList | This article develops a community resilience optimization method subject to power flow constraints in the cyber-physical-social systems in power engineering, which is solved using a multiagent-based algorithm. The tool that makes the nexus between the electric generation on the physical side and consumers and prosumers on the social side is the power flow algorithm. Specifically, the levels of emotion, empathy, cooperation, and the physical health of the consumers, prosumers are modeled in the proposed community resilience optimization approach while accounting for the electric power system constraints and their impact on the critical loads, which include hospitals, shelters, and gas stations, to name a few. The optimization accounts for the fact that the level of satisfaction of the society, the living standards, and the social well-being are depended on the supply of energy, including electricity. Evidently, the lack of electric energy resulting from load shedding has an impact on both the mental and the psychical quality of life, which in turn affects the community resilience. The developed constrained community resilience optimization method is applied to two case studies, including a two-area 6-buses system and a modified IEEE RTS 24-bus system. |
Author | Valinejad, Jaber Mili, Lamine |
Author_xml | – sequence: 1 givenname: Jaber orcidid: 0000-0003-3619-1606 surname: Valinejad fullname: Valinejad, Jaber organization: Data and System Science in Public Health Lab, Harvard University, Cambridge, MA, USA – sequence: 2 givenname: Lamine orcidid: 0000-0001-6134-3945 surname: Mili fullname: Mili, Lamine organization: Bradley Department of Electrical and Computer Engineering, Virginia Tech, Northern Virginia Center, Washington, VA, USA |
BookMark | eNp9kDtPwzAUhS0EEqXwB2CxxJziV9J4RBFPIVGRMjBFjnMjXCV2sV1V4dfTlxgYmO4dzneO9J2hY-ssIHRJyYRSIm-ey49yPmGEsQlnlJBpeoRGVPJpIhkXx7ufJTnNxSk6C2FBSJqnUzlCTeH6fmVNHPAbBNMZsBrw6zKa3nyraJzF5apegI44Ojxza_D4vnNrXDgbolfGxoCNxcVQg09mn0MwWnVJ6bRRHS6HEKEP5-ikVV2Ai8Mdo_f7u3nxmLy8PjwVty-JZjKNiaolUxIoZzWtdUYEQKubhgInWUaAiCbNFCM845CxVui0aUUmiWwlFdO05XyMrve9S---VhBitXArbzeTFcuZoJTznGxSbJ_S3oXgoa2W3vTKDxUl1dZmtbNZbW1WB5sbKP8DaRN3frYSuv_Rqz1qAOB3S0qaZ4LzH8bEhfo |
CODEN | ISJEB2 |
CitedBy_id | crossref_primary_10_1049_enc2_12087 crossref_primary_10_1109_TCSII_2021_3109850 crossref_primary_10_1109_TPWRS_2022_3212688 crossref_primary_10_3390_su151813369 crossref_primary_10_1007_s42001_023_00220_z crossref_primary_10_1111_mice_13445 |
Cites_doi | 10.1109/TNSE.2022.3181130 10.1016/j.riob.2008.04.007 10.1109/TPWRS.2005.857931 10.1109/TSMC.2016.2608658 10.1109/TAFFC.2014.2360418 10.1109/TPWRS.2015.2503426 10.1073/pnas.0913149107 10.1109/ACCESS.2018.2879887 10.1111/risa.13320 10.1109/TCYB.2019.2951207 10.1109/TPWRS.2018.2871182 10.1109/TCYB.2019.2957415 10.1109/TCSII.2021.3109850 10.1080/17517571003763380 10.1037/0022-3514.52.1.81 10.1109/TPWRS.2019.2900513 10.1109/WI-IAT.2010.181 10.1111/1467-9280.00431 10.1002/art.1790070405 10.1109/MWSCAS.2017.8053185 10.1007/978-3-642-11161-7_4 10.1109/TCYB.2014.2306919 10.1201/b13161-12 10.1109/TCYB.2014.2323892 10.1109/TCYB.2017.2708321 10.1109/TPWRS.2019.2914431 10.1002/2050-7038.12704 10.1147/JRD.2019.2952330 10.4324/9780429480355 10.1109/TCYB.2016.2602498 10.1109/TCYB.2016.2634027 10.7717/peerj.231 10.2139/ssrn.2429787 10.1007/978-3-642-15314-3_4 10.7148/2009-0212-0218 10.1109/TNSE.2021.3098194 10.1109/TNSE.2018.2850904 10.1037/xge0000399 10.1186/s12961-016-0103-6 10.1007/s10458-012-9201-1 10.1080/02699939008410799 10.1016/j.apenergy.2017.06.059 10.1057/palgrave.ip.8800113 10.1109/TSG.2018.2890548 10.1038/nphys2160 |
ContentType | Journal Article |
Copyright | Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023 |
Copyright_xml | – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023 |
DBID | 97E RIA RIE AAYXX CITATION |
DOI | 10.1109/JSYST.2022.3210075 |
DatabaseName | IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Xplore CrossRef |
DatabaseTitle | CrossRef |
DatabaseTitleList | |
Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/ sourceTypes: Publisher |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Engineering |
EISSN | 1937-9234 |
EndPage | 12 |
ExternalDocumentID | 10_1109_JSYST_2022_3210075 9918643 |
Genre | orig-research |
GroupedDBID | 0R~ 29I 4.4 5GY 5VS 6IK 97E AAJGR AARMG AASAJ AAWTH ABAZT ABQJQ ABVLG ACIWK AENEX AETIX AGQYO AGSQL AHBIQ AKJIK AKQYR ALMA_UNASSIGNED_HOLDINGS ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ CS3 DU5 EBS EJD HZ~ IFIPE IPLJI JAVBF LAI M43 O9- OCL RIA RIE RNS AAYXX CITATION RIG |
ID | FETCH-LOGICAL-c295t-ab92a9e132b1bc604eefcdd1e30660e04d56a20363e62f4c5df46909f91475f33 |
IEDL.DBID | RIE |
ISSN | 1932-8184 |
IngestDate | Mon Jun 30 09:12:06 EDT 2025 Thu Apr 24 22:54:30 EDT 2025 Tue Jul 01 01:43:40 EDT 2025 Wed Aug 27 02:29:09 EDT 2025 |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 2 |
Language | English |
License | https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html https://doi.org/10.15223/policy-029 https://doi.org/10.15223/policy-037 |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c295t-ab92a9e132b1bc604eefcdd1e30660e04d56a20363e62f4c5df46909f91475f33 |
Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
ORCID | 0000-0003-3619-1606 0000-0001-6134-3945 |
PQID | 2824113380 |
PQPubID | 85494 |
PageCount | 12 |
ParticipantIDs | crossref_primary_10_1109_JSYST_2022_3210075 ieee_primary_9918643 proquest_journals_2824113380 crossref_citationtrail_10_1109_JSYST_2022_3210075 |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | 2023-06-01 |
PublicationDateYYYYMMDD | 2023-06-01 |
PublicationDate_xml | – month: 06 year: 2023 text: 2023-06-01 day: 01 |
PublicationDecade | 2020 |
PublicationPlace | New York |
PublicationPlace_xml | – name: New York |
PublicationTitle | IEEE systems journal |
PublicationTitleAbbrev | JSYST |
PublicationYear | 2023 |
Publisher | IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher_xml | – name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
References | ref13 ref12 ref15 ref14 ref53 ref11 ref10 ref54 ref17 ref16 ref19 ref18 ali (ref52) 2013; 2 ref51 ref50 ref46 ref45 ref47 hämäläinen (ref48) 2016; 14 ref42 ref41 ref44 ref43 mili (ref1) 0 yu (ref2) 2021 ref49 ref8 ref7 ref9 ref4 pederson (ref3) 2006; 25 ref6 ref5 barsade (ref22) 1998 ref40 ref35 ref34 ref37 zuckerman (ref25) 1994 ref31 ref30 ref33 ref39 ref38 ref24 ref23 ref26 ref20 valinejad (ref21) 2022 (ref36) 0 ref28 ref27 (ref32) 0 ref29 |
References_xml | – ident: ref42 doi: 10.1109/TNSE.2022.3181130 – ident: ref27 doi: 10.1016/j.riob.2008.04.007 – ident: ref54 doi: 10.1109/TPWRS.2005.857931 – ident: ref39 doi: 10.1109/TSMC.2016.2608658 – ident: ref40 doi: 10.1109/TAFFC.2014.2360418 – volume: 25 year: 2006 ident: ref3 article-title: Critical infrastructure interdependency modeling: A survey of us and international research publication-title: Idaho National Laboratory – year: 2022 ident: ref21 article-title: Measuring and enhancing the resilience of interdependent power systems, emergency services, and social communities – ident: ref53 doi: 10.1109/TPWRS.2015.2503426 – ident: ref50 doi: 10.1073/pnas.0913149107 – start-page: 81 year: 1998 ident: ref22 article-title: Group emotion: A view from top and bottom publication-title: Composition – ident: ref37 doi: 10.1109/ACCESS.2018.2879887 – ident: ref12 doi: 10.1111/risa.13320 – ident: ref33 doi: 10.1109/TCYB.2019.2951207 – ident: ref10 doi: 10.1109/TPWRS.2018.2871182 – ident: ref34 doi: 10.1109/TCYB.2019.2957415 – ident: ref17 doi: 10.1109/TCSII.2021.3109850 – ident: ref11 doi: 10.1080/17517571003763380 – volume: 2 start-page: 125 year: 2013 ident: ref52 article-title: Media myths and realities in natural disasters publication-title: Eur J Bus Soc Sci – year: 0 ident: ref32 article-title: Empathy revolution – ident: ref24 doi: 10.1037/0022-3514.52.1.81 – ident: ref6 doi: 10.1109/TPWRS.2019.2900513 – year: 0 ident: ref1 article-title: Integrating community resilience in power system planning publication-title: Power Engineering Advances and Challenges Part B Electrical Power – ident: ref43 doi: 10.1109/WI-IAT.2010.181 – ident: ref28 doi: 10.1111/1467-9280.00431 – ident: ref49 doi: 10.1002/art.1790070405 – year: 0 ident: ref36 article-title: Bridging compassion and technology, compassion – ident: ref14 doi: 10.1109/MWSCAS.2017.8053185 – ident: ref30 doi: 10.1007/978-3-642-11161-7_4 – ident: ref20 doi: 10.1109/TCYB.2014.2306919 – ident: ref51 doi: 10.1201/b13161-12 – start-page: 1 year: 2021 ident: ref2 article-title: A semantic model for enterprise application integration in the era of data explosion and globalisation publication-title: Enterprise Inf Syst – ident: ref19 doi: 10.1109/TCYB.2014.2323892 – ident: ref18 doi: 10.1109/TCYB.2017.2708321 – ident: ref7 doi: 10.1109/TPWRS.2019.2914431 – ident: ref15 doi: 10.1002/2050-7038.12704 – ident: ref38 doi: 10.1147/JRD.2019.2952330 – ident: ref16 doi: 10.4324/9780429480355 – ident: ref35 doi: 10.1109/TCYB.2016.2602498 – ident: ref31 doi: 10.1109/TCYB.2016.2634027 – ident: ref47 doi: 10.7717/peerj.231 – ident: ref44 doi: 10.2139/ssrn.2429787 – ident: ref23 doi: 10.1007/978-3-642-15314-3_4 – ident: ref29 doi: 10.7148/2009-0212-0218 – ident: ref5 doi: 10.1109/TNSE.2021.3098194 – ident: ref9 doi: 10.1109/TNSE.2018.2850904 – year: 1994 ident: ref25 publication-title: Behavioral Expressions and Biosocial Bases of Sensation Seeking – ident: ref46 doi: 10.1037/xge0000399 – volume: 14 year: 2016 ident: ref48 article-title: Cross-sector cooperation in health-enhancing physical activity policymaking: More potential than achievements? publication-title: Health Res Policy Syst doi: 10.1186/s12961-016-0103-6 – ident: ref41 doi: 10.1007/s10458-012-9201-1 – ident: ref26 doi: 10.1080/02699939008410799 – ident: ref13 doi: 10.1016/j.apenergy.2017.06.059 – ident: ref45 doi: 10.1057/palgrave.ip.8800113 – ident: ref8 doi: 10.1109/TSG.2018.2890548 – ident: ref4 doi: 10.1038/nphys2160 |
SSID | ssj0058579 |
Score | 2.3627129 |
Snippet | This article develops a community resilience optimization method subject to power flow constraints in the cyber-physical-social systems in power engineering,... |
SourceID | proquest crossref ieee |
SourceType | Aggregation Database Enrichment Source Index Database Publisher |
StartPage | 1 |
SubjectTerms | Algorithms Behavioral sciences Community resilience Computational modeling Constraints Consumers critical loads cyber-physical-social system Electric power systems Electricity distribution Load modeling Load shedding Microgrids Multiagent systems Optimization Power flow Power systems Resilience Service stations smart grids social computing social well-being |
Title | Community Resilience Optimization Subject to Power Flow Constraints in Cyber-Physical-Social Systems |
URI | https://ieeexplore.ieee.org/document/9918643 https://www.proquest.com/docview/2824113380 |
Volume | 17 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1LSwMxEB7Ukx58i9UqOXjTXfeRbJujFIsIVfEBelp2kyyIdSvtFtFf70w2W4qKeMshgcCXzMyXzDcDcBSqiOvIIE3VooMEJYnJDiq8eEJ0i5ij1yCh8OAquXjgl4_icQFOZloYY4xNPjM-De1fvh6pKT2VnWIs00UPugiLSNxqrVZjdTHqtXX1KB7x0AnxRiATyNPLu6e7e6SCUeSTYiWgnMI5J2S7qvwwxda_9Ndg0OysTit58adV7qvPb0Ub_7v1dVh1gSY7q0_GBiyYchNW5soPboF26pDqg92ayfPQ3nJ2jUbk1akzGdoVeqhh1YjdUD811h-O3hl1-bS9JaoJey5Z7yM3Y-_GIe7Vil_maqFvw0P__L534bmuC56KpKi8LJdRJg2y1DzMVRJwYwqldWiQXCSBCbgWSUbfl7FJooIroQui2LKQIe-IIo53YKkclWYXmE5CncU6R2MsedaVWSy0DPKwg0Ek53HSgrCBIVWuJDntfphaahLI1EKXEnSpg64Fx7M1b3VBjj9nbxEWs5kOhha0G7RTd2cnKZJPHhJlD_Z-X7UPy9Rsvk4Ua8NSNZ6aAwxJqvzQnsUvWz_cXg |
linkProvider | IEEE |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1LSwMxEB58HNSDb7E-c_CmW_eRbJujiKU-qqIV9LTsJlkQayt2i-ivdyabLaIi3nJIIPAlM_Ml880A7AUq5Do0SFO1aCBBiSOygwovnhDNPOLoNUgo3LmM23f87F7cT8DBWAtjjLHJZ6ZOQ_uXrwdqRE9lhxjLNNGDTsI0-n0Rlmqtyu5i3Gsr61FE4qEb4pVExpeHZ7cPt10kg2FYJ82KT1mFX9yQ7avywxhbD9NagE61tzKx5Kk-KrK6-vhWtvG_m1-EeRdqsqPybCzBhOkvw9yXAoQroJ0-pHhnN2b42LP3nF2hGXl2-kyGloWealgxYNfUUY21eoM3Rn0-bXeJYsge--z4PTOv3rXD3Cs1v8xVQ1-Fu9ZJ97jtub4LngqlKLw0k2EqDfLULMhU7HNjcqV1YJBexL7xuRZxSh-YkYnDnCuhcyLZMpcBb4g8itZgqj_om3VgOg50GukMzbHkaVOmkdDSz4IGhpGcR3ENggqGRLmi5LT7XmLJiS8TC11C0CUOuhrsj9e8lCU5_py9QliMZzoYarBVoZ24WztMkH7ygEi7v_H7ql2YaXc7F8nF6eX5JsxS6_kybWwLporXkdnGAKXIduy5_AQEat-o |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Community+Resilience+Optimization+Subject+to+Power+Flow+Constraints+in+Cyber-Physical-Social+Systems&rft.jtitle=IEEE+systems+journal&rft.au=Valinejad%2C+Jaber&rft.au=Mili%2C+Lamine&rft.date=2023-06-01&rft.pub=IEEE&rft.issn=1932-8184&rft.spage=1&rft.epage=12&rft_id=info:doi/10.1109%2FJSYST.2022.3210075&rft.externalDocID=9918643 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1932-8184&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1932-8184&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1932-8184&client=summon |