Recursive Convex Model for Optimal Power Flow Solution in Monopolar DC Networks

This paper presents a new optimal power flow (OPF) formulation for monopolar DC networks using a recursive convex representation. The hyperbolic relation between the voltages and power at each constant power terminal (generator or demand) is represented as a linear constraint for the demand nodes an...

Full description

Autores:
Montoya, Oscar Danilo
Zishan, Farhad
Giral-Ramírez, Diego Armando
Tipo de recurso:
Fecha de publicación:
2022
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/12218
Acceso en línea:
https://hdl.handle.net/20.500.12585/12218
Palabra clave:
Convex optimization
Monopolar DC networks
Optimal power flow solution
Power losses minimization
Recursive convex formulation
Rights
openAccess
License
http://creativecommons.org/licenses/by-nc-nd/4.0/
id UTB2_573f2d1b8affc08a3a61a4c49f2d9c4d
oai_identifier_str oai:repositorio.utb.edu.co:20.500.12585/12218
network_acronym_str UTB2
network_name_str Repositorio Institucional UTB
repository_id_str
dc.title.spa.fl_str_mv Recursive Convex Model for Optimal Power Flow Solution in Monopolar DC Networks
title Recursive Convex Model for Optimal Power Flow Solution in Monopolar DC Networks
spellingShingle Recursive Convex Model for Optimal Power Flow Solution in Monopolar DC Networks
Convex optimization
Monopolar DC networks
Optimal power flow solution
Power losses minimization
Recursive convex formulation
title_short Recursive Convex Model for Optimal Power Flow Solution in Monopolar DC Networks
title_full Recursive Convex Model for Optimal Power Flow Solution in Monopolar DC Networks
title_fullStr Recursive Convex Model for Optimal Power Flow Solution in Monopolar DC Networks
title_full_unstemmed Recursive Convex Model for Optimal Power Flow Solution in Monopolar DC Networks
title_sort Recursive Convex Model for Optimal Power Flow Solution in Monopolar DC Networks
dc.creator.fl_str_mv Montoya, Oscar Danilo
Zishan, Farhad
Giral-Ramírez, Diego Armando
dc.contributor.author.none.fl_str_mv Montoya, Oscar Danilo
Zishan, Farhad
Giral-Ramírez, Diego Armando
dc.subject.keywords.spa.fl_str_mv Convex optimization
Monopolar DC networks
Optimal power flow solution
Power losses minimization
Recursive convex formulation
topic Convex optimization
Monopolar DC networks
Optimal power flow solution
Power losses minimization
Recursive convex formulation
description This paper presents a new optimal power flow (OPF) formulation for monopolar DC networks using a recursive convex representation. The hyperbolic relation between the voltages and power at each constant power terminal (generator or demand) is represented as a linear constraint for the demand nodes and generators. To reach the solution for the OPF problem a recursive evaluation of the model that determines the voltage variables at the iteration (Formula presented.) ((Formula presented.)) by using the information of the voltages at the iteration t ((Formula presented.)) is proposed. To finish the recursive solution process of the OPF problem via the convex relaxation, the difference between the voltage magnitudes in two consecutive iterations less than the predefined tolerance is considered as a stopping criterion. The numerical results in the 85-bus grid demonstrate that the proposed recursive convex model can solve the classical power flow problem in monopolar DC networks, and it also solves the OPF problem efficiently with a reduced convergence error when compared with semidefinite programming and combinatorial optimization methods. In addition, the proposed approach can deal with radial and meshed monopolar DC networks without modifications in its formulation. All the numerical implementations were in the MATLAB programming environment and the convex models were solved with the CVX and the Gurobi solver. © 2022 by the authors
publishDate 2022
dc.date.issued.none.fl_str_mv 2022-10-05
dc.date.accessioned.none.fl_str_mv 2023-07-19T21:22:53Z
dc.date.available.none.fl_str_mv 2023-07-19T21:22:53Z
dc.date.submitted.none.fl_str_mv 2023-07
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_b1a7d7d4d402bcce
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/article
dc.type.hasversion.spa.fl_str_mv info:eu-repo/semantics/draft
dc.type.spa.spa.fl_str_mv http://purl.org/coar/resource_type/c_6501
status_str draft
dc.identifier.citation.spa.fl_str_mv Montoya, O.D.; Zishan, F.; Giral-Ramírez, D.A. Recursive Convex Model for Optimal Power Flow Solution in Monopolar DC Networks. Mathematics 2022, 10, 3649. https://doi.org/10.3390/math10193649
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12585/12218
dc.identifier.doi.none.fl_str_mv 10.3390/math10193649
dc.identifier.instname.spa.fl_str_mv Universidad Tecnológica de Bolívar
dc.identifier.reponame.spa.fl_str_mv Repositorio Universidad Tecnológica de Bolívar
identifier_str_mv Montoya, O.D.; Zishan, F.; Giral-Ramírez, D.A. Recursive Convex Model for Optimal Power Flow Solution in Monopolar DC Networks. Mathematics 2022, 10, 3649. https://doi.org/10.3390/math10193649
10.3390/math10193649
Universidad Tecnológica de Bolívar
Repositorio Universidad Tecnológica de Bolívar
url https://hdl.handle.net/20.500.12585/12218
dc.language.iso.spa.fl_str_mv eng
language eng
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.uri.*.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.accessrights.spa.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.cc.*.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.extent.none.fl_str_mv 14 páginas
dc.format.medium.none.fl_str_mv Pdf
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.place.spa.fl_str_mv Cartagena de Indias
dc.source.spa.fl_str_mv Mathematics - Vol. 10 No. 9 (2022)
institution Universidad Tecnológica de Bolívar
bitstream.url.fl_str_mv https://repositorio.utb.edu.co/bitstream/20.500.12585/12218/1/Recursive-Convex-Model-for-Optimal-Power-Flow-Solution-in-Monopolar-DC-NetworksMathematics.pdf
https://repositorio.utb.edu.co/bitstream/20.500.12585/12218/2/license_rdf
https://repositorio.utb.edu.co/bitstream/20.500.12585/12218/3/license.txt
https://repositorio.utb.edu.co/bitstream/20.500.12585/12218/4/Recursive-Convex-Model-for-Optimal-Power-Flow-Solution-in-Monopolar-DC-NetworksMathematics.pdf.txt
https://repositorio.utb.edu.co/bitstream/20.500.12585/12218/5/Recursive-Convex-Model-for-Optimal-Power-Flow-Solution-in-Monopolar-DC-NetworksMathematics.pdf.jpg
bitstream.checksum.fl_str_mv 0d9924d6665225a89ec20d62eb5b2606
4460e5956bc1d1639be9ae6146a50347
e20ad307a1c5f3f25af9304a7a7c86b6
27b3182a12a054c4f2d75949ad9b91db
4998741a337e1ec0a90f279b8b8e08a1
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
MD5
MD5
repository.name.fl_str_mv Repositorio Institucional UTB
repository.mail.fl_str_mv repositorioutb@utb.edu.co
_version_ 1814021562825703424
spelling Montoya, Oscar Danilo9fa8a75a-58fa-436d-a6e2-d80f718a4ea8Zishan, Farhad041e882b-354f-48b5-87bc-d4748b261f08Giral-Ramírez, Diego Armandoa9612d05-bc90-49f9-94c7-20a0766e00f52023-07-19T21:22:53Z2023-07-19T21:22:53Z2022-10-052023-07Montoya, O.D.; Zishan, F.; Giral-Ramírez, D.A. Recursive Convex Model for Optimal Power Flow Solution in Monopolar DC Networks. Mathematics 2022, 10, 3649. https://doi.org/10.3390/math10193649https://hdl.handle.net/20.500.12585/1221810.3390/math10193649Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThis paper presents a new optimal power flow (OPF) formulation for monopolar DC networks using a recursive convex representation. The hyperbolic relation between the voltages and power at each constant power terminal (generator or demand) is represented as a linear constraint for the demand nodes and generators. To reach the solution for the OPF problem a recursive evaluation of the model that determines the voltage variables at the iteration (Formula presented.) ((Formula presented.)) by using the information of the voltages at the iteration t ((Formula presented.)) is proposed. To finish the recursive solution process of the OPF problem via the convex relaxation, the difference between the voltage magnitudes in two consecutive iterations less than the predefined tolerance is considered as a stopping criterion. The numerical results in the 85-bus grid demonstrate that the proposed recursive convex model can solve the classical power flow problem in monopolar DC networks, and it also solves the OPF problem efficiently with a reduced convergence error when compared with semidefinite programming and combinatorial optimization methods. In addition, the proposed approach can deal with radial and meshed monopolar DC networks without modifications in its formulation. All the numerical implementations were in the MATLAB programming environment and the convex models were solved with the CVX and the Gurobi solver. © 2022 by the authors14 páginasPdfapplication/pdfenghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2Mathematics - Vol. 10 No. 9 (2022)Recursive Convex Model for Optimal Power Flow Solution in Monopolar DC Networksinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/drafthttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/version/c_b1a7d7d4d402bccehttp://purl.org/coar/resource_type/c_2df8fbb1Convex optimizationMonopolar DC networksOptimal power flow solutionPower losses minimizationRecursive convex formulationCartagena de IndiasSimiyu, P., Xin, A., Wang, K., Adwek, G., Salman, S. Multiterminal medium voltage DC distribution network hierarchical control (2020) Electronics (Switzerland), 9 (3), art. no. 506. Cited 15 times. https://www.mdpi.com/2079-9292/9/3/506/pdf doi: 10.3390/electronics9030506Gelani, H.E., Dastgeer, F., Nasir, M., Khan, S., Guerrero, J.M. Ac vs. Dc distribution efficiency: Are we on the right path? (2021) Energies, 14 (13), art. no. 4039. Cited 10 times. https://www.mdpi.com/1996-1073/14/13/4039/pdf doi: 10.3390/en14134039Xu, F., Lu, Y., Huang, X., Lu, C., Qiu, P., Ding, C. Research on DC power flow controllable multi-port DC circuit breaker (2022) Energy Reports, 8, pp. 1163-1171. Cited 2 times. http://www.journals.elsevier.com/energy-reports/ doi: 10.1016/j.egyr.2021.11.073Garces, A. Uniqueness of the power flow solutions in low voltage direct current grids (Open Access) (2017) Electric Power Systems Research, 151, pp. 149-153. Cited 92 times. doi: 10.1016/j.epsr.2017.05.031Gan, L., Low, S.H. Optimal power flow in direct current networks (2013) Proceedings of the IEEE Conference on Decision and Control, art. no. 6760774, pp. 5614-5619. Cited 15 times. ISBN: 978-146735717-3 doi: 10.1109/CDC.2013.6760774Rodriguez, P., Rouzbehi, K. Multi-terminal DC grids: challenges and prospects (2017) Journal of Modern Power Systems and Clean Energy, 5 (4), pp. 515-523. Cited 109 times. www.springer.com/40565 doi: 10.1007/s40565-017-0305-0Grisales-Noreña, L.F., Garzon-Rivera, O.D., Ocampo-Toro, J.A., Ramos-Paja, C.A., Rodriguez Cabal, M.A. Metaheuristic optimization methods for optimal power flow analysis in DC distribution networks (Open Access) (2020) Transactions on Energy Systems and Engineering Applications, 1 (1), pp. 13-31. Cited 13 times. revistas.utb.edu.co/tesea/ doi: 10.32397/tesea.vol1.n1.2Fan, Y., Chi, Y., Li, Y., Wang, Z., Liu, H., Liu, W., Li, X. Key technologies for medium and low voltage DC distribution system (2021) Global Energy Interconnection, 4 (1), pp. 91-103. Cited 16 times. www.keaipublishing.com/en/journals/global-energy-interconnection/ doi: 10.1016/j.gloei.2021.03.009Li, J., Liu, F., Wang, Z., Low, S.H., Mei, S. Optimal Power Flow in Stand-Alone DC Microgrids (2018) IEEE Transactions on Power Systems, 33 (5), art. no. 8279503, pp. 5496-5506. Cited 113 times. doi: 10.1109/TPWRS.2018.2801280Garces, A., Montoya, D., Torres, R. Optimal power flow in multiterminal HVDC systems considering DC/DC converters (Open Access) (2016) IEEE International Symposium on Industrial Electronics, 2016-November, art. no. 7745067, pp. 1212-1217. Cited 30 times. ISBN: 978-150900873-5 doi: 10.1109/ISIE.2016.7745067Montoya, O.D., Gil-González, W., Garces, A. Sequential quadratic programming models for solving the OPF problem in DC grids (Open Access) (2019) Electric Power Systems Research, 169, pp. 18-23. Cited 39 times. doi: 10.1016/j.epsr.2018.12.008Turgut, M.S., Turgut, O.E., Afan, H.A., El-Shafie, A. A novel Master–Slave optimization algorithm for generating an optimal release policy in case of reservoir operation (Open Access) (2019) Journal of Hydrology, 577, art. no. 123959. Cited 18 times. www.elsevier.com/inca/publications/store/5/0/3/3/4/3 doi: 10.1016/j.jhydrol.2019.123959Grisales-Noreña, L.F., Montoya, D.G., Ramos-Paja, C.A. Optimal sizing and location of distributed generators based on PBIL and PSO techniques (Open Access) (2018) Energies, 11 (4), art. no. en11041018. Cited 98 times. http://www.mdpi.com/journal/energies/ doi: 10.3390/en11041018Muñoz, A.A.R., Grisales-Noreña, L.F., Montano, J., Montoya, O.D., Giral-Ramírez, D.A. Optimal power dispatch of distributed generators in direct current networks using a master–slave methodology that combines the salp swarm algorithm and the successive approximation method (2021) Electronics (Switzerland), 10 (22), art. no. 2837. Cited 6 times. https://www.mdpi.com/2079-9292/10/22/2837/pdf doi: 10.3390/electronics10222837Montoya, O.D., Gil-Gonzalez, W., Grisales-Norena, L.F. Vortex Search Algorithm for Optimal Power Flow Analysis in DC Resistive Networks with CPLs (2020) IEEE Transactions on Circuits and Systems II: Express Briefs, 67 (8), art. no. 8821394, pp. 1439-1443. Cited 15 times. http://www.ieee-cas.org doi: 10.1109/TCSII.2019.2938530Montoya, O.D., Giral-Ramírez, D.A., Grisales-Noreña, L.F. Optimal economic-environmental dispatch in MT-HVDC systems via sine-cosine algorithm (Open Access) (2022) Results in Engineering, 13, art. no. 100348. Cited 7 times. https://www.journals.elsevier.com/results-in-engineering doi: 10.1016/j.rineng.2022.100348Chen, Y., Xiang, J., Li, Y. Socp relaxations of optimal power flow problem considering current margins in radial networks (Open Access) (2018) Energies, 11 (11), art. no. 3164. Cited 17 times. https://www.mdpi.com/1996-1073/11/11 doi: 10.3390/en11113164Benedito, E., Puerto-Flores, D.D., Dòria-Cerezo, A., Scherpen, J.M.A. Optimal Power Flow for resistive DC Networks: a Port-Hamiltonian approach (2017) IFAC-PapersOnLine, 50 (1), pp. 25-30. Cited 5 times. http://www.journals.elsevier.com/ifac-papersonline/ doi: 10.1016/j.ifacol.2017.08.005Li, L. (2015) Selected Applications of Convex Optimization. Cited 16 times. Springer, Berlin/Heidelberg, GermanyMonteiro, A.C.B., Fran, R.P., Arthur, R., Iano, Y. The fundamentals and potential of heuristics and metaheuristics for multiobjective combinatorial optimization problems and solution methods (Open Access) (2022) Multi-Objective Combinatorial Optimization Problems and Solution Methods, pp. 9-29. Cited 3 times. https://www.sciencedirect.com/book/9780128237991 ISBN: 978-012823799-1; 978-012823800-4 doi: 10.1016/B978-0-12-823799-1.00002-4Zhang, H., Vittal, V., Heydt, G.T., Quintero, J. A relaxed AC optimal power flow model based on a Taylor series (Open Access) (2013) 2013 IEEE Innovative Smart Grid Technologies - Asia, ISGT Asia 2013, art. no. 6698739. Cited 27 times. ISBN: 978-147991347-3 doi: 10.1109/ISGT-Asia.2013.6698739Liu, J., Cui, B., Molzahn, D.K., Chen, C., Lu, X., Qiu, F. Optimal Power Flow in DC Networks With Robust Feasibility and Stability Guarantees (Open Access) (2022) IEEE Transactions on Control of Network Systems, 9 (2), pp. 904-916. Cited 3 times. http://ieeexplore.ieee.org/servlet/opac?punumber=6509490 doi: 10.1109/TCNS.2021.3124932Fantauzzi, M., Lauria, D., Mottola, F., Scalfati, A. Sizing energy storage systems in DC networks: A general methodology based upon power losses minimization (2017) Applied Energy, 187, pp. 862-872. Cited 24 times. http://www.elsevier.com/inca/publications/store/4/0/5/8/9/1/index.htt doi: 10.1016/j.apenergy.2016.11.044Li, H., Wang, X., Lin, J., Wu, L., Liu, T. An improved Newton-Raphson based linear power flow method for DC grids with dispatchable DGs and ZIP loads (Open Access) (2022) COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 41 (5), pp. 1297-1312. http://www.emeraldinsight.com/info/journals/compel/compel.jsp doi: 10.1108/COMPEL-06-2021-0195Garcés, A., Rodriguez-Garcia, L. An Approach for Nodal Admittance Matrix Real-Time Estimation on DC Microgrids (2019) IEEE Green Technologies Conference, 2019-April, art. no. 8767140. Cited 5 times. http://ieeexplore.ieee.org ISBN: 978-172811457-6 doi: 10.1109/GreenTech.2019.8767140Liu, B., Wei, W., Liu, F. Locating all real solutions of power flow equations: A convex optimisation-based method (Open Access) (2018) IET Generation, Transmission and Distribution, 12 (10), pp. 2273-2279. Cited 9 times. www.ietdl.org/IET-GTD doi: 10.1049/iet-gtd.2017.1870Garces, A. A Linear Three-Phase Load Flow for Power Distribution Systems (2016) IEEE Transactions on Power Systems, 31 (1), art. no. 7027253, pp. 827-828. Cited 213 times. doi: 10.1109/TPWRS.2015.2394296Medina-Quesada, Á., Montoya, O.D., Hernández, J.C. Derivative-Free Power Flow Solution for Bipolar DC Networks with Multiple Constant Power Terminals (Open Access) (2022) Sensors, 22 (8), art. no. 2914. Cited 10 times. https://www.mdpi.com/1424-8220/22/8/2914/pdf doi: 10.3390/s22082914Montoya, O.D., Gil-González, W., Garces, A. Numerical methods for power flow analysis in DC networks: State of the art, methods and challenges (Open Access) (2020) International Journal of Electrical Power and Energy Systems, 123, art. no. 106299. Cited 29 times. https://www.journals.elsevier.com/international-journal-of-electrical-power-and-energy-systems doi: 10.1016/j.ijepes.2020.106299Attia, A.-F., El Sehiemy, R.A., Hasanien, H.M. Optimal power flow solution in power systems using a novel Sine-Cosine algorithm (2018) International Journal of Electrical Power and Energy Systems, 99, pp. 331-343. Cited 257 times. doi: 10.1016/j.ijepes.2018.01.024http://purl.org/coar/resource_type/c_2df8fbb1ORIGINALRecursive-Convex-Model-for-Optimal-Power-Flow-Solution-in-Monopolar-DC-NetworksMathematics.pdfRecursive-Convex-Model-for-Optimal-Power-Flow-Solution-in-Monopolar-DC-NetworksMathematics.pdfapplication/pdf326441https://repositorio.utb.edu.co/bitstream/20.500.12585/12218/1/Recursive-Convex-Model-for-Optimal-Power-Flow-Solution-in-Monopolar-DC-NetworksMathematics.pdf0d9924d6665225a89ec20d62eb5b2606MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://repositorio.utb.edu.co/bitstream/20.500.12585/12218/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-83182https://repositorio.utb.edu.co/bitstream/20.500.12585/12218/3/license.txte20ad307a1c5f3f25af9304a7a7c86b6MD53TEXTRecursive-Convex-Model-for-Optimal-Power-Flow-Solution-in-Monopolar-DC-NetworksMathematics.pdf.txtRecursive-Convex-Model-for-Optimal-Power-Flow-Solution-in-Monopolar-DC-NetworksMathematics.pdf.txtExtracted texttext/plain46079https://repositorio.utb.edu.co/bitstream/20.500.12585/12218/4/Recursive-Convex-Model-for-Optimal-Power-Flow-Solution-in-Monopolar-DC-NetworksMathematics.pdf.txt27b3182a12a054c4f2d75949ad9b91dbMD54THUMBNAILRecursive-Convex-Model-for-Optimal-Power-Flow-Solution-in-Monopolar-DC-NetworksMathematics.pdf.jpgRecursive-Convex-Model-for-Optimal-Power-Flow-Solution-in-Monopolar-DC-NetworksMathematics.pdf.jpgGenerated Thumbnailimage/jpeg7852https://repositorio.utb.edu.co/bitstream/20.500.12585/12218/5/Recursive-Convex-Model-for-Optimal-Power-Flow-Solution-in-Monopolar-DC-NetworksMathematics.pdf.jpg4998741a337e1ec0a90f279b8b8e08a1MD5520.500.12585/12218oai:repositorio.utb.edu.co:20.500.12585/122182023-07-20 00:17:59.871Repositorio Institucional UTBrepositorioutb@utb.edu.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