A Novel Solution Technique for the Expansion Planning of Modern Distribution Systems
| Main Author: | |
|---|---|
| Publication Date: | 2023 |
| Other Authors: | , , |
| Format: | Conference object |
| Language: | eng |
| Source: | Repositório Institucional da UNESP |
| Download full: | http://dx.doi.org/10.1109/EEEIC/ICPSEurope57605.2023.10194884 https://hdl.handle.net/11449/309466 |
Summary: | This paper addresses the expansion planning problem of modern distribution systems using a novel solution methodology based on matheuristics. The problem is formulated as a mixed-integer quadratic programming model. The proposed technique constitutes a novel local search algorithm that, using linearized and relaxed versions of the original problem, finds successive solutions, improving at each iteration the feasibility of the original problem until attaining a high-quality near-optimal solution. Planning actions include line reconductoring and installation of distributed generation (DG) units, electrical energy storage (EES) systems, and fixed and switchable capacitor banks (CBs). Operation system variability in demand and energy resources is modeled through representative days in order to preserve EES temporal transition. Furthermore, the model guarantees CO2 reduction in order to be on track to limit global warming. The effective performance of the proposed approach in terms of solution quality and computational time has been illustrated with a case study based on a 33-node distribution system. |
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A Novel Solution Technique for the Expansion Planning of Modern Distribution SystemsCO2emissions reductionLocal search algorithmmodern distribution systemsquadratic programmingThis paper addresses the expansion planning problem of modern distribution systems using a novel solution methodology based on matheuristics. The problem is formulated as a mixed-integer quadratic programming model. The proposed technique constitutes a novel local search algorithm that, using linearized and relaxed versions of the original problem, finds successive solutions, improving at each iteration the feasibility of the original problem until attaining a high-quality near-optimal solution. Planning actions include line reconductoring and installation of distributed generation (DG) units, electrical energy storage (EES) systems, and fixed and switchable capacitor banks (CBs). Operation system variability in demand and energy resources is modeled through representative days in order to preserve EES temporal transition. Furthermore, the model guarantees CO2 reduction in order to be on track to limit global warming. The effective performance of the proposed approach in terms of solution quality and computational time has been illustrated with a case study based on a 33-node distribution system.São Paulo State University Dept. of Electrical EngineeringUniversidad de Castilla-La Mancha E.T.S. de Ingeniería IndustrialSão Paulo State University Dept. of Electrical EngineeringUniversidade Estadual Paulista (UNESP)E.T.S. de Ingeniería IndustrialMarcelo, Jonathan A. [UNESP]Muñoz-Delgado, GregorioContreras, JavierMantovani, José R. S. [UNESP]2025-04-29T20:15:37Z2023-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1109/EEEIC/ICPSEurope57605.2023.10194884Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023.https://hdl.handle.net/11449/30946610.1109/EEEIC/ICPSEurope57605.2023.101948842-s2.0-85168688199Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023info:eu-repo/semantics/openAccess2025-04-30T13:33:10Zoai:repositorio.unesp.br:11449/309466Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestrepositoriounesp@unesp.bropendoar:29462025-04-30T13:33:10Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
| dc.title.none.fl_str_mv |
A Novel Solution Technique for the Expansion Planning of Modern Distribution Systems |
| title |
A Novel Solution Technique for the Expansion Planning of Modern Distribution Systems |
| spellingShingle |
A Novel Solution Technique for the Expansion Planning of Modern Distribution Systems Marcelo, Jonathan A. [UNESP] CO2emissions reduction Local search algorithm modern distribution systems quadratic programming |
| title_short |
A Novel Solution Technique for the Expansion Planning of Modern Distribution Systems |
| title_full |
A Novel Solution Technique for the Expansion Planning of Modern Distribution Systems |
| title_fullStr |
A Novel Solution Technique for the Expansion Planning of Modern Distribution Systems |
| title_full_unstemmed |
A Novel Solution Technique for the Expansion Planning of Modern Distribution Systems |
| title_sort |
A Novel Solution Technique for the Expansion Planning of Modern Distribution Systems |
| author |
Marcelo, Jonathan A. [UNESP] |
| author_facet |
Marcelo, Jonathan A. [UNESP] Muñoz-Delgado, Gregorio Contreras, Javier Mantovani, José R. S. [UNESP] |
| author_role |
author |
| author2 |
Muñoz-Delgado, Gregorio Contreras, Javier Mantovani, José R. S. [UNESP] |
| author2_role |
author author author |
| dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) E.T.S. de Ingeniería Industrial |
| dc.contributor.author.fl_str_mv |
Marcelo, Jonathan A. [UNESP] Muñoz-Delgado, Gregorio Contreras, Javier Mantovani, José R. S. [UNESP] |
| dc.subject.por.fl_str_mv |
CO2emissions reduction Local search algorithm modern distribution systems quadratic programming |
| topic |
CO2emissions reduction Local search algorithm modern distribution systems quadratic programming |
| description |
This paper addresses the expansion planning problem of modern distribution systems using a novel solution methodology based on matheuristics. The problem is formulated as a mixed-integer quadratic programming model. The proposed technique constitutes a novel local search algorithm that, using linearized and relaxed versions of the original problem, finds successive solutions, improving at each iteration the feasibility of the original problem until attaining a high-quality near-optimal solution. Planning actions include line reconductoring and installation of distributed generation (DG) units, electrical energy storage (EES) systems, and fixed and switchable capacitor banks (CBs). Operation system variability in demand and energy resources is modeled through representative days in order to preserve EES temporal transition. Furthermore, the model guarantees CO2 reduction in order to be on track to limit global warming. The effective performance of the proposed approach in terms of solution quality and computational time has been illustrated with a case study based on a 33-node distribution system. |
| publishDate |
2023 |
| dc.date.none.fl_str_mv |
2023-01-01 2025-04-29T20:15:37Z |
| dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
| dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
| format |
conferenceObject |
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publishedVersion |
| dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1109/EEEIC/ICPSEurope57605.2023.10194884 Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023. https://hdl.handle.net/11449/309466 10.1109/EEEIC/ICPSEurope57605.2023.10194884 2-s2.0-85168688199 |
| url |
http://dx.doi.org/10.1109/EEEIC/ICPSEurope57605.2023.10194884 https://hdl.handle.net/11449/309466 |
| identifier_str_mv |
Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023. 10.1109/EEEIC/ICPSEurope57605.2023.10194884 2-s2.0-85168688199 |
| dc.language.iso.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
Proceedings - 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023 |
| dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
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openAccess |
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Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
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Universidade Estadual Paulista (UNESP) |
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UNESP |
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UNESP |
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Repositório Institucional da UNESP |
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Repositório Institucional da UNESP |
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Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
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repositoriounesp@unesp.br |
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1834482801987026944 |