Mostrar el registro sencillo del ítem

dc.contributor.editorFigueroa-Garcia J.C.
dc.contributor.editorDuarte-Gonzalez M.
dc.contributor.editorJaramillo-Isaza S.
dc.contributor.editorOrjuela-Canon A.D.
dc.contributor.editorDiaz-Gutierrez Y.
dc.creatorManrique M.L.
dc.creatorMontoya O.D.
dc.creatorGarrido Arévalo, Víctor Manuel
dc.creatorGrisales-Noreña L.F.
dc.creatorGil-González W.
dc.date.accessioned2020-03-26T16:33:09Z
dc.date.available2020-03-26T16:33:09Z
dc.date.issued2019
dc.identifier.citationCommunications in Computer and Information Science; Vol. 1052, pp. 28-39
dc.identifier.isbn9783030310189
dc.identifier.issn18650929
dc.identifier.urihttps://hdl.handle.net/20.500.12585/9183
dc.description.abstractThis paper addresses the analysis the optimal power flow (OPF) problem in alternating current (AC) radial distribution networks by using a new metaheuristic optimization technique known as a sine-cosine algorithm (SCA). This combinatorial optimization approach allows for solving the nonlinear non-convex optimization OPF problem by using a master-slave strategy. In the master stage, the soft computing SCA is used to define the power dispatch at each distributed generator (dimensioning problem). In the slave stage, it is used a conventional radial power flow formulated by incidence matrices is used for evaluating the total power losses (objective function evaluation). Two conventional highly used distribution feeders with 33 and 69 nodes are employed for validating the proposed master-slave approach. Simulation results are compared with different literature methods such as genetic algorithm, particle swarm optimization, and krill herd algorithm. All the simulations are performed in MATLAB programming environment, and their results show the effectiveness of the proposed approach in contrast to previously reported methods. © 2019, Springer Nature Switzerland AG.eng
dc.format.mediumRecurso electrónico
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherSpringer
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourcehttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85075672718&doi=10.1007%2f978-3-030-31019-6_3&partnerID=40&md5=7b578464309de0f72fbd68cbf2cc0083
dc.titleSine-Cosine Algorithm for OPF Analysis in Distribution Systems to Size Distributed Generators
dcterms.bibliographicCitationKeane, A., State-of-the-art techniques and challenges ahead for distributed generation planning and optimization (2013) IEEE Trans. Power Syst., 28 (2), pp. 1493-1502
dcterms.bibliographicCitationMontoya, O.D., Garces, A., Castro, C.A., Optimal conductor size selection in radial distribution networks using a mixed-integer non-linear programming formulation (2018) IEEE Lat. Am. Trans., 16 (8), pp. 2213-2220
dcterms.bibliographicCitationZeng, B., Zhang, J., Yang, X., Wang, J., Dong, J., Zhang, Y., Integrated planning for transition to low-carbon distribution system with renewable energy generation and demand response (2014) IEEE Trans. Power Syst., 29 (3), pp. 1153-1165
dcterms.bibliographicCitationLi, R., Wang, W., Xia, M., Cooperative planning of active distribution system with renewable energy sources and energy storage systems (2018) IEEE Access, 6, pp. 5916-5926
dcterms.bibliographicCitationMontoya, O.D., Grajales, A., Garces, A., Castro, C.A., Distribution systems operation considering energy storage devices and distributed generation (2017) IEEE Lat. Am. Trans., 15 (5), pp. 890-900
dcterms.bibliographicCitationBai, X., Qu, L., Qiao, W., Robust AC optimal power flow for power networks with wind power generation (2016) IEEE Trans. Power Syst., 31 (5), pp. 4163-4164
dcterms.bibliographicCitationGabash, A., Li, P., Active-reactive optimal power flow in distribution networks with embedded generation and battery storage (2012) IEEE Trans. Power Syst., 27 (4), pp. 2026-2035
dcterms.bibliographicCitationWang, Y., Zhang, N., Li, H., Yang, J., Kang, C., Linear three-phase power flow for unbalanced active distribution networks with PV nodes (2017) CSEE J. Power Energy Syst., 3 (3), pp. 321-324
dcterms.bibliographicCitationGrisales-Noreña, L.F., Gonzalez-Montoya, D., Ramos-Paja, C.A., Optimal sizing and location of distributed generators based on PBIL and PSO techniques (2018) Energies, 11 (1018), pp. 1-27
dcterms.bibliographicCitationTeng, J.-H., A modified gauss–seidel algorithm of three-phase power flow analysis in distribution networks (2002) Int. J. Electr. Power Energy Syst., 24 (2), pp. 97-102
dcterms.bibliographicCitationZamzam, A.S., Sidiropoulos, N.D., Dall’Anese, E., Beyond relaxation and Newton– Raphson: Solving AC OPF for multi-phase systems with renewables (2018) IEEE Trans. Smart Grid, 9 (5), pp. 3966-3975
dcterms.bibliographicCitationGarces, A., A linear three-phase load flow for power distribution systems (2016) IEEE Trans. Power Syst., 31 (1), pp. 827-828
dcterms.bibliographicCitationLisboa, A., Guedes, L., Vieira, D., Saldanha, R., A fast power flow method for radial networks with linear storage and no matrix inversions (2014) Int. J. Electr. Power Energy Syst., 63, pp. 901-907
dcterms.bibliographicCitationSultana, S., Roy, P.K., Krill herd algorithm for optimal location of distributed generator in radial distribution system (2016) Appl. Soft Comput., 40, pp. 391-404
dcterms.bibliographicCitationAttia, A.-F., Sehiemy, R.A.E., Hasanien, H.M., Optimal power flow solution in power systems using a novel Sine-Cosine algorithm (2018) Int. J. Electr. Power Energy Syst., 99, pp. 331-343
dcterms.bibliographicCitationMoradi, M., Abedini, M., A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems (2012) Int. J. Electr. Power Energy Syst., 34 (1), pp. 66-74
dcterms.bibliographicCitationHuang, S., Wu, Q., Wang, J., Zhao, H., A sufficient condition on convex relaxation of AC optimal power flow in distribution networks (2017) IEEE Trans. Power Syst., 32 (2), pp. 1359-1368
dcterms.bibliographicCitationVenzke, A., Halilbasic, L., Markovic, U., Hug, G., Chatzivasileiadis, S., Convex relaxations of chance constrained AC optimal power flow (2018) IEEE Trans. Power Syst., 33 (3), pp. 2829-2841
dcterms.bibliographicCitationMiao, Z., Fan, L., Aghamolki, H.G., Zeng, B., Least squares estimation based SDP cuts for SOCP relaxation of AC OPF (2018) IEEE Trans. Autom. Control, 63 (1), pp. 241-248
dcterms.bibliographicCitationOliveira, E.J., Oliveira, L.W., Pereira, J., Honório, L.M., Silva, I.C., Marcato, A., An optimal power flow based on safety barrier interior point method (2015) Int. J. Electr. Power Energy Syst., 64, pp. 977-985
dcterms.bibliographicCitationYang, J., He, L., Fu, S., An improved PSO-based charging strategy of electric vehicles in electrical distribution grid (2014) Appl. Energy, 128, pp. 82-92
dcterms.bibliographicCitationTodorovski, M., Rajicic, D., An initialization procedure in solving optimal power flow by genetic algorithm (2006) IEEE Trans. Power Syst., 21 (2), pp. 480-487
dcterms.bibliographicCitationAbido, M.A., Optimal power flow using tabu search algorithm (2002) Electr. Power Compon. Syst., 30 (5), pp. 469-483
dcterms.bibliographicCitationKılıc, U., Ayan, K., Optimizing power flow of AC–DC power systems using artificial bee colony algorithm (2013) Int. J. Electr. Power Energy Syst., 53, pp. 592-602
dcterms.bibliographicCitationBalachennaiah, P., Suryakalavathi, M., Nagendra, P., Firefly algorithm based solution to minimize the real power loss in a power system (2018) Ain Shams Eng. J., 9 (1), pp. 89-100
dcterms.bibliographicCitationMontoya, O.D., Garrido, V.M., Gil-González, W., Grisales-Noreña, L.F., Power flow analysis in DC grids: Two alternative numerical methods (2019) IEEE Trans. Circuits Syst. II, 1
dcterms.bibliographicCitationGarces, A., Uniqueness of the power flow solutions in low voltage direct current grids (2017) Electr. Power Syst. Res., 151, pp. 149-153
dcterms.bibliographicCitationInjeti, S.K., Kumar, N.P., A novel approach to identify optimal access point and capacity of multiple DGs in a small, medium and large scale radial distribution systems (2013) Int. J. Electr. Power Energy Syst., 45 (1), pp. 142-151
datacite.rightshttp://purl.org/coar/access_right/c_16ec
oaire.resourceTypehttp://purl.org/coar/resource_type/c_c94f
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
dc.source.event6th Workshop on Engineering Applications, WEA 2019
dc.type.driverinfo:eu-repo/semantics/conferenceObject
dc.type.hasversioninfo:eu-repo/semantics/publishedVersion
dc.identifier.doi10.1007/978-3-030-31019-6_3
dc.subject.keywordsOptimal power flow
dc.subject.keywordsOptimal sizing of distributed generation
dc.subject.keywordsRadial distribution networks
dc.subject.keywordsSine-cosine algorithm
dc.subject.keywordsSoft computing optimization technique
dc.subject.keywordsAcoustic generators
dc.subject.keywordsCombinatorial optimization
dc.subject.keywordsConvex optimization
dc.subject.keywordsDistributed power generation
dc.subject.keywordsElectric impedance measurement
dc.subject.keywordsElectric load flow
dc.subject.keywordsGenetic algorithms
dc.subject.keywordsMATLAB
dc.subject.keywordsParticle size analysis
dc.subject.keywordsParticle swarm optimization (PSO)
dc.subject.keywordsSilicon compounds
dc.subject.keywordsSoft computing
dc.subject.keywordsOptimal power flows
dc.subject.keywordsOptimal sizing
dc.subject.keywordsOptimization techniques
dc.subject.keywordsRadial distribution networks
dc.subject.keywordsSine-cosine algorithm
dc.subject.keywordsElectric load dispatching
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.rights.ccAtribución-NoComercial 4.0 Internacional
dc.identifier.instnameUniversidad Tecnológica de Bolívar
dc.identifier.reponameRepositorio UTB
dc.relation.conferencedate16 October 2019 through 18 October 2019
dc.type.spaConferencia
dc.identifier.orcid57212008879
dc.identifier.orcid56919564100
dc.identifier.orcid57208126635
dc.identifier.orcid55791991200
dc.identifier.orcid57191493648


Ficheros en el ítem

FicherosTamañoFormatoVer

No hay ficheros asociados a este ítem.

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.