Mostrar el registro sencillo del ítem

dc.contributor.authorCastiblanco-Pérez, Cristian Mateo
dc.contributor.authorToro-Rodríguez, David Esteban
dc.contributor.authorMontoya, Oscar Danilo
dc.contributor.authorGiral-Ramírez, Diego Armando
dc.date.accessioned2021-09-28T14:34:24Z
dc.date.available2021-09-28T14:34:24Z
dc.date.issued2021-06-02
dc.date.submitted2021-09-27
dc.identifier.citationCastiblanco-Pérez CM, Toro-Rodríguez DE, Montoya OD, Giral-Ramírez DA. Optimal Placement and Sizing of D-STATCOM in Radial and Meshed Distribution Networks Using a Discrete-Continuous Version of the Genetic Algorithm. Electronics. 2021; 10(12):1452. ttps://doi.org/10.3390/electronics10121452spa
dc.identifier.urihttps://hdl.handle.net/20.500.12585/10373
dc.description.abstractIn this paper, we propose a new discrete-continuous codification of the Chu–Beasley genetic algorithm to address the optimal placement and sizing problem of the distribution static compensators (D-STATCOM) in electrical distribution grids. The discrete part of the codification determines the nodes where D-STATCOM will be installed. The continuous part of the codification regulates their sizes. The objective function considered in this study is the minimization of the annual operative costs regarding energy losses and installation investments in D-STATCOM. This objective function is subject to the classical power balance constraints and devices’ capabilities. The proposed discrete-continuous version of the genetic algorithm solves the mixed-integer non-linear programming model that the classical power balance generates. Numerical validations in the 33 test feeder with radial and meshed configurations show that the proposed approach effectively minimizes the annual operating costs of the grid. In addition, the GAMS software compares the results of the proposed optimization method, which allows demonstrating its efficiency and robustnessspa
dc.format.extent20 páginas
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceElectronics 2021, 10, 1452spa
dc.titleOptimal Placement and sizing of D-STATCOM in radial and meshed distribution networks using a discrete-continuous version of the genetic algorithmspa
dcterms.bibliographicCitationCavellucci, C.; Lyra, C. Minimization of Energy Losses in Electric Power Distribution Systems by Intelligent Search Strategies. IFAC Proc. Vol. 1995, 28, 589–594spa
dcterms.bibliographicCitationMontoya, O.D.; Gil-González, W.; Hernández, J.C. Efficient Operative Cost Reduction in Distribution Grids Considering the Optimal Placement and Sizing of D-STATCOMs Using a Discrete-Continuous VSA. Appl. Sci. 2021, 11, 2175. [spa
dcterms.bibliographicCitationAlam, M.S.; Arefifar, S.A. Energy Management in Power Distribution Systems: Review, Classification, Limitations and Challenges. IEEE Access 2019, 7, 92979–93001spa
dcterms.bibliographicCitationSadovskaia, K.; Bogdanov, D.; Honkapuro, S.; Breyer, C. Power transmission and distribution losses—A model based on available empirical data and future trends for all countries globally. Int. J. Electr. Power Energy Syst. 2019, 107, 98–109spa
dcterms.bibliographicCitationComisión de Regulación de Energía y Gas. CREG. Resolución CREG 119 de 21 de Diciembre de 2007; CREG: Bogotá, Colombia, 2007spa
dcterms.bibliographicCitationColmenar-Santos, A.; Reino-Rio, C.; Borge-Diez, D.; Collado-Fernández, E. Distributed generation: A review of factors that can contribute most to achieve a scenario of DG units embedded in the new distribution networks. Renew. Sustain. Energy Rev. 2016, 59, 1130–1148.spa
dcterms.bibliographicCitationMuruganantham, B.; Selvam, M.M.; Gnanadass, R.; Padhy, N.P. Energy loss reduction and load balancing through network reconfiguration in practical LV distribution feeder using GAMS. In Proceedings of the 7th International Conference on Power Systems (ICPS), Pune, India, 21–23 December 2017; IEEE: Piscataway, NJ, USA, 2017spa
dcterms.bibliographicCitationElsheikh, A.; Helmy, Y.; Abouelseoud, Y.; Elsherif, A. Optimal capacitor placement and sizing in radial electric power systems. Alex. Eng. J. 2014, 53, 809–816spa
dcterms.bibliographicCitationTamilselvan, V.; Jayabarathi, T.; Raghunathan, T.; Yang, X.S. Optimal capacitor placement in radial distribution systems using flower pollination algorithm. Alex. Eng. J. 2018, 57, 2775–2786spa
dcterms.bibliographicCitationSirjani, R.; Jordehi, A.R. Optimal placement and sizing of distribution static compensator (D-STATCOM) in electric distribution networks: A review. Renew. Sustain. Energy Rev. 2017, 77, 688–694spa
dcterms.bibliographicCitationMontoya, O.D.; Chamorro, H.R.; Alvarado-Barrios, L.; Gil-González, W.; Orozco-Henao, C. Genetic-Convex Model for Dynamic Reactive Power Compensation in Distribution Networks Using D-STATCOMs. Appl. Sci. 2021, 11, 3353spa
dcterms.bibliographicCitationSedighizadeh, M.; Eisapour-Moarref, A. The Imperialist Competitive Algorithm for Optimal Multi-Objective Location and Sizing of DSTATCOM in Distribution Systems Considering Loads Uncertainty. INAE Lett. 2017, 2, 83–95spa
dcterms.bibliographicCitationZhang, Q.; Chen, H.; Luo, J.; Xu, Y.; Wu, C.; Li, C. Chaos Enhanced Bacterial Foraging Optimization for Global Optimization. IEEE Access 2018, 6, 64905–64919spa
dcterms.bibliographicCitationYuvaraj, T.; Devabalaji, K.; Ravi, K. Optimal Placement and Sizing of DSTATCOM Using Harmony Search Algorithm. Energy Procedia 2015, 79, 759–765spa
dcterms.bibliographicCitationTaher, S.A.; Afsari, S.A. Optimal location and sizing of DSTATCOM in distribution systems by immune algorithm. Int. J. Electr. Power Energy Syst. 2014, 60, 34–44.spa
dcterms.bibliographicCitationMarjani, S.R.; Talavat, V.; Galvani, S. Optimal allocation of D-STATCOM and reconfiguration in radial distribution network using MOPSO algorithm in TOPSIS framework. Int. Trans. Electr. Energy Syst. 2018, 29, e2723spa
dcterms.bibliographicCitationTolabi, H.B.; Ali, M.H.; Rizwan, M. Simultaneous Reconfiguration, Optimal Placement of DSTATCOM, and Photovoltaic Array in a Distribution System Based on Fuzzy-ACO Approach. IEEE Trans. Sustain. Energy 2015, 6, 210–218spa
dcterms.bibliographicCitationGupta, A.R.; Kumar, A. Energy Savings Using D-STATCOM Placement in Radial Distribution System; Elsevier: Amsterdam, The Netherlands, 2015; Volume 70, pp. 558–564. [spa
dcterms.bibliographicCitationRukmani, D.K.; Thangaraj, Y.; Subramaniam, U.; Ramachandran, S.; Elavarasan, R.M.; Das, N.; Baringo, L.; Rasheed, M.I.A. A New Approach to Optimal Location and Sizing of DSTATCOM in Radial Distribution Networks Using Bio-Inspired Cuckoo Search Algorithm. Energies 2020, 13, 4615spa
dcterms.bibliographicCitationSamimi, A.; Golkar, M.A. A Novel Method for Optimal Placement of STATCOM in Distribution Networks Using Sensitivity Analysis by DIgSILENT Software. In Proceedings of the 2011 Asia-Pacific Power and Energy Engineering Conference, Wuhan, China, 25–28 March 2011; pp. 1–5spa
dcterms.bibliographicCitationMuthukumar, K.; Jayalalitha, S. Optimal placement and sizing of distributed generators and shunt capacitors for power loss minimization in radial distribution networks using hybrid heuristic search optimization technique. Int. J. Electr. Power Energy Syst. 2016, 78, 299–319.spa
dcterms.bibliographicCitationSannigrahi, S.; Acharjee, P. Implementation of crow search algorithm for optimal allocation of DG and DSTATCOM in practical distribution system. In Proceedings of the 2018 International Conference on Power, Instrumentation, Control and Computing (PICC), Thrissur, India, 18–20 January 2018; IEEE: Piscataway, NJ, USA, 2018spa
dcterms.bibliographicCitationRajan, C.S.G.; Ravi, K. Optimal placement and sizing of DSTATCOM using Ant lion optimization algorithm. In Proceedings of the 2019 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC), Melmaruvathur, Chennai, India, 27–28 March 2019; IEEE: Piscataway, NJ, USA, 2019;spa
dcterms.bibliographicCitationAmin, A.; Kamel, S.; Selim, A.; Nasrat, L. Optimal Placement of Distribution Static Compensators in Radial Distribution Systems Using Hybrid Analytical-Coyote optimization Technique. In Proceedings of the 2019 21st International Middle East Power Systems Conference (MEPCON), Cairo, Egypt, 17–19 December 2019; IEEE: Piscataway, NJ, USA, 2019spa
dcterms.bibliographicCitation. Dash, S.; Mishra, S. Simultaneous Optimal Placement and Sizing of D- STATCOMs Using a Modified Sine Cosine Algorithm. In Advances in Intelligent Computing and Communication; Springer: Singapore, 2020.spa
dcterms.bibliographicCitationMontoya, O.D.; Fuentes, J.E.; Moya, F.D.; Barrios, J.Á.; Chamorro, H.R. Reduction of Annual Operational Costs in Power Systems through the Optimal Siting and Sizing of STATCOMs. Appl. Sci. 2021, 11, 4634.spa
dcterms.bibliographicCitationHuanca, D.; Gallego, L. Chu and Beasley Genetic Algorithm to Solve the Transmission Network Expansion Planning Problem Considering Active Power Losses. IEEE Latin Am. Trans. 2021, 19, 1967–1975.spa
dcterms.bibliographicCitationComisión de Regulación De Energía y Gas. CREG. RESOLUCIÓN No. 024 de 2005; CREG: Bogotá, Colombia, 2005.spa
dcterms.bibliographicCitationMontoya, O.D.; Gil-González, W.; Giral, D.A. On the Matricial Formulation of Iterative Sweep Power Flow for Radial and Meshed Distribution Networks with Guarantee of Convergence. Appl. Sci. 2020, 10, 5802spa
dcterms.bibliographicCitationShen, T.; Li, Y.; Xiang, J. A Graph-Based Power Flow Method for Balanced Distribution Systems. Energies 2018, 11, 511spa
dcterms.bibliographicCitationVasconcellos, D.B.; González, P.P.; González, G.F. Control de demanda eléctrica aplicando algoritmos genéticos. Ingeniare Rev. Chilena de Ingeniería 2017, 25, 389–398spa
dcterms.bibliographicCitationZhao, J.-Q.; Wang, L. Center Based Genetic Algorithm and its application to the stiffness equivalence of the aircraft wing. Expert Syst. Appl. 2011, 38, 6254–6261spa
dcterms.bibliographicCitationDuan, D.L.; Ling, X.D.; Wu, X.Y.; Zhong, B. Reconfiguration of distribution network for loss reduction and reliability improvement based on an enhanced genetic algorithm. Int. J. Electr. Power Energy Syst. 2015, 64, 88–95spa
dcterms.bibliographicCitationSingh, B.; Singh, S. GA-based optimization for integration of DGs, STATCOM and PHEVs in distribution systems. Energy Rep. 2019, 5, 84–103spa
dcterms.bibliographicCitationVenkatesh, B.; Ranjan, R. Optimal radial distribution system reconfiguration using fuzzy adaptation of evolutionary programming. Int. J. Electr. Power Energy Syst. 2003, 25, 775–780spa
datacite.rightshttp://purl.org/coar/access_right/c_abf2spa
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.hasversioninfo:eu-repo/semantics/restrictedAccessspa
dc.identifier.doihttps://doi.org/10.3390/electronics10121452
dc.subject.keywordsDistribution networksspa
dc.subject.keywordsDistribution static compensatorsspa
dc.subject.keywordsDiscrete-continuous genetic algorithmspa
dc.subject.keywordsRadial and meshed configurationsspa
dc.subject.keywordsEvolutive computationspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.ccAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.identifier.instnameUniversidad Tecnológica de Bolívarspa
dc.identifier.reponameRepositorio Universidad Tecnológica de Bolívarspa
dc.publisher.placeCartagena de Indiasspa
dc.subject.armarcLEMB
dc.type.spahttp://purl.org/coar/resource_type/c_2df8fbb1spa
dc.audienceInvestigadoresspa
oaire.resourcetypehttp://purl.org/coar/resource_type/c_2df8fbb1spa


Ficheros en el ítem

Thumbnail
Thumbnail

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem

http://creativecommons.org/licenses/by-nc-nd/4.0/
http://creativecommons.org/licenses/by-nc-nd/4.0/

Universidad Tecnológica de Bolívar - 2017 Institución de Educación Superior sujeta a inspección y vigilancia por el Ministerio de Educación Nacional. Resolución No 961 del 26 de octubre de 1970 a través de la cual la Gobernación de Bolívar otorga la Personería Jurídica a la Universidad Tecnológica de Bolívar.