Optimal Reactive Power Compensation via D-STATCOMs in Electrical Distribution Systems by Applying the Generalized Normal Distribution Optimizer
This research deals with the problem regarding the optimal siting and sizing of distribution static compensators (D-STATCOMs) via the application of a master–slave optimization technique. The master stage determines the nodes where the D-STATCOMs must be located and their nominal rates by applying t...
- Autores:
-
García-Pineda, Laura Patricia
Montoya, Oscar Danilo
- Tipo de recurso:
- Fecha de publicación:
- 2023
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/11838
- Palabra clave:
- Generalized normal distribution optimizer
Optimal reactive power flow
Distribution static compensators
Radial and meshed distribution networks
Annual operating cost minimization
LEMB
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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dc.title.spa.fl_str_mv |
Optimal Reactive Power Compensation via D-STATCOMs in Electrical Distribution Systems by Applying the Generalized Normal Distribution Optimizer |
title |
Optimal Reactive Power Compensation via D-STATCOMs in Electrical Distribution Systems by Applying the Generalized Normal Distribution Optimizer |
spellingShingle |
Optimal Reactive Power Compensation via D-STATCOMs in Electrical Distribution Systems by Applying the Generalized Normal Distribution Optimizer Generalized normal distribution optimizer Optimal reactive power flow Distribution static compensators Radial and meshed distribution networks Annual operating cost minimization LEMB |
title_short |
Optimal Reactive Power Compensation via D-STATCOMs in Electrical Distribution Systems by Applying the Generalized Normal Distribution Optimizer |
title_full |
Optimal Reactive Power Compensation via D-STATCOMs in Electrical Distribution Systems by Applying the Generalized Normal Distribution Optimizer |
title_fullStr |
Optimal Reactive Power Compensation via D-STATCOMs in Electrical Distribution Systems by Applying the Generalized Normal Distribution Optimizer |
title_full_unstemmed |
Optimal Reactive Power Compensation via D-STATCOMs in Electrical Distribution Systems by Applying the Generalized Normal Distribution Optimizer |
title_sort |
Optimal Reactive Power Compensation via D-STATCOMs in Electrical Distribution Systems by Applying the Generalized Normal Distribution Optimizer |
dc.creator.fl_str_mv |
García-Pineda, Laura Patricia Montoya, Oscar Danilo |
dc.contributor.author.none.fl_str_mv |
García-Pineda, Laura Patricia Montoya, Oscar Danilo |
dc.subject.keywords.spa.fl_str_mv |
Generalized normal distribution optimizer Optimal reactive power flow Distribution static compensators Radial and meshed distribution networks Annual operating cost minimization |
topic |
Generalized normal distribution optimizer Optimal reactive power flow Distribution static compensators Radial and meshed distribution networks Annual operating cost minimization LEMB |
dc.subject.armarc.none.fl_str_mv |
LEMB |
description |
This research deals with the problem regarding the optimal siting and sizing of distribution static compensators (D-STATCOMs) via the application of a master–slave optimization technique. The master stage determines the nodes where the D-STATCOMs must be located and their nominal rates by applying the generalized normal distribution optimizer (GNDO) with a discrete–continuous codification. In the slave stage, the successive approximations power flow method is implemented in order to establish the technical feasibility of the solution provided by the master stage, i.e., voltage regulation and device capabilities, among other features. The main goal of the proposed master–slave optimizer is to minimize the expected annual operating costs of the distribution grid, which includes the energy loss and investment costs of the D-STATCOMs. With the purpose of improving the effectiveness of reactive power compensation during the daily operation of the distribution grid, an optimal reactive power flow (ORPF) approach is used that considers the nodes where D-STATCOMs are located as inputs in order to obtain their daily expected dynamical behavior with regard to reactive power injection to obtain additional net profits. The GNDO approach and the power flow method are implemented in the MATLAB programming environment, and the ORPF approach is implemented in the GAMS software using a test feeder comprising 33 nodes with both radial and meshed configurations. A complete comparative analysis with the Salp Swarm Algorithm is presented in order to demonstrate the effectiveness of the proposed two-stage optimization approach in the fixed operation scenario regarding the final objective function values. In addition, different tests considering the possibility of hourly power injection using D-STATCOMs through the ORPF solution demonstrate that additional gains can be obtained in the expected annual operative costs of the grid. |
publishDate |
2023 |
dc.date.accessioned.none.fl_str_mv |
2023-05-04T15:43:29Z |
dc.date.available.none.fl_str_mv |
2023-05-04T15:43:29Z |
dc.date.issued.none.fl_str_mv |
2023-01-03 |
dc.date.submitted.none.fl_str_mv |
2023-05-03 |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_b1a7d7d4d402bcce |
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_2df8fbb1 |
status_str |
draft |
dc.identifier.citation.spa.fl_str_mv |
García-Pineda, L.P.; Montoya, O.D. Optimal Reactive Power Compensation via D-STATCOMs in Electrical Distribution Systems by Applying the Generalized Normal Distribution Optimizer. Algorithms 2023, 16, 29.https://doi.org/10.3390/a16010029 |
dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/11838 |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.3390/a16010029 |
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 |
García-Pineda, L.P.; Montoya, O.D. Optimal Reactive Power Compensation via D-STATCOMs in Electrical Distribution Systems by Applying the Generalized Normal Distribution Optimizer. Algorithms 2023, 16, 29.https://doi.org/10.3390/a16010029 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
url |
https://hdl.handle.net/20.500.12585/11838 https://doi.org/10.3390/a16010029 |
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 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 |
18 páginas |
dc.format.mimetype.spa.fl_str_mv |
application/pdf |
dc.publisher.place.spa.fl_str_mv |
Cartagena de Indias |
dc.publisher.sede.spa.fl_str_mv |
Campus Tecnológico |
dc.source.spa.fl_str_mv |
Algorithms Vol. 16 N° 1 |
institution |
Universidad Tecnológica de Bolívar |
bitstream.url.fl_str_mv |
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García-Pineda, Laura Patriciabfa22d64-b19b-4240-952c-d5247a27fd70Montoya, Oscar Danilo8a59ede1-6a4a-4d2e-abdc-d0afb14d44802023-05-04T15:43:29Z2023-05-04T15:43:29Z2023-01-032023-05-03García-Pineda, L.P.; Montoya, O.D. Optimal Reactive Power Compensation via D-STATCOMs in Electrical Distribution Systems by Applying the Generalized Normal Distribution Optimizer. Algorithms 2023, 16, 29.https://doi.org/10.3390/a16010029https://hdl.handle.net/20.500.12585/11838https://doi.org/10.3390/a16010029Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThis research deals with the problem regarding the optimal siting and sizing of distribution static compensators (D-STATCOMs) via the application of a master–slave optimization technique. The master stage determines the nodes where the D-STATCOMs must be located and their nominal rates by applying the generalized normal distribution optimizer (GNDO) with a discrete–continuous codification. In the slave stage, the successive approximations power flow method is implemented in order to establish the technical feasibility of the solution provided by the master stage, i.e., voltage regulation and device capabilities, among other features. The main goal of the proposed master–slave optimizer is to minimize the expected annual operating costs of the distribution grid, which includes the energy loss and investment costs of the D-STATCOMs. With the purpose of improving the effectiveness of reactive power compensation during the daily operation of the distribution grid, an optimal reactive power flow (ORPF) approach is used that considers the nodes where D-STATCOMs are located as inputs in order to obtain their daily expected dynamical behavior with regard to reactive power injection to obtain additional net profits. The GNDO approach and the power flow method are implemented in the MATLAB programming environment, and the ORPF approach is implemented in the GAMS software using a test feeder comprising 33 nodes with both radial and meshed configurations. A complete comparative analysis with the Salp Swarm Algorithm is presented in order to demonstrate the effectiveness of the proposed two-stage optimization approach in the fixed operation scenario regarding the final objective function values. In addition, different tests considering the possibility of hourly power injection using D-STATCOMs through the ORPF solution demonstrate that additional gains can be obtained in the expected annual operative costs of the grid.18 páginasapplication/pdfenghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAttribution-NonCommercial-NoDerivatives 4.0 InternacionalAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2Algorithms Vol. 16 N° 1Optimal Reactive Power Compensation via D-STATCOMs in Electrical Distribution Systems by Applying the Generalized Normal Distribution Optimizerinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/drafthttp://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_b1a7d7d4d402bcceGeneralized normal distribution optimizerOptimal reactive power flowDistribution static compensatorsRadial and meshed distribution networksAnnual operating cost minimizationLEMBCartagena de IndiasCampus TecnológicoPúblico generalSiano, P.; Rigatos, G.; Piccolo, A. Active Distribution Networks and Smart Grids: Optimal Allocation of Wind Turbines by Using Hybrid GA and Multi-Period OPF. In Atlantis Computational Intelligence Systems; Atlantis Press: Amsterdam, The Netherlands, 2012; pp. 579–599. [CrossRef]Krishna, T.M.; Ramana, N.; Kamakshaiah, S. A novel algorithm for the loss estimation and minimization of radial distribution system with distributed generation. In Proceedings of the 2013 International Conference on Energy Efficient Technologies for Sustainability, Nagercoil, India, 10–12 April 2013; pp. 1289–1293.Nasir, M.; Shahrin, N.; Bohari, Z.; Sulaima, M.; Hassan, M. A Distribution Network Reconfiguration based on PSO: Considering DGs sizing and allocation evaluation for voltage profile improvement. In Proceedings of the 2014 IEEE Student Conference on Research and Development, Penang, Malaysia, 16–17 December 2014; pp. 1–6.Vita, V. Development of a Decision-Making Algorithm for the Optimum Size and Placement of Distributed Generation Units in Distribution Networks. Energies 2017, 10, 1433. [CrossRef]Verma, H.K.; Singh, P. Optimal reconfiguration of distribution network using modified culture algorithm. J. Inst. Eng. Ser. B 2018, 99, 613–622. [CrossRef]Vita, V. Development of a Decision-Making Algorithm for the Optimum Size and Placement of Distributed Generation Units in Distribution Networks. Energies 2017, 10, 1433. [CrossRef]Verma, H.K.; Singh, P. Optimal reconfiguration of distribution network using modified culture algorithm. J. Inst. Eng. Ser. B 2018, 99, 613–622. [CrossRef]Sultana, S.; Roy, P.K. Optimal capacitor placement in radial distribution systems using teaching learning based optimization. Int. J. Electr. Power Energy Syst. 2014, 54, 387–398. [CrossRef]Kerrouche, K.D.E.; Lodhi, E.; Kerrouche, M.B.;Wang, L.; Zhu, F.; Xiong, G. Modeling and design of the improved D-STATCOM control for power distribution grid. SN Appl. Sci. 2020, 2, 1519. [CrossRef]Sirjani, 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, 688–694. [CrossRef]Rezaeian Marjani, S.; 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. 2019, 29, e2723.Tolabi, 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 2014, 6, 210–218. [CrossRef]Gupta, A.R.; Kumar, A. Energy savings using D-STATCOM placement in radial distribution system. Procedia Comput. Sci. 2015, 70, 558–564. [CrossRef]Jazebi, S.; Hosseinian, S.H.; Vahidi, B. DSTATCOM allocation in distribution networks considering reconfiguration using differential evolution algorithm. Energy Convers. Manag. 2011, 52, 2777–2783. [CrossRef]Devi, S.; Geethanjali, M. Optimal location and sizing of distribution static synchronous series compensator using particle swarm optimization. Int. J. Electr. Power Energy Syst. 2014, 62, 646–653. [CrossRef]Gupta, A.R.; Kumar, A. Optimal placement of D-STATCOM in distribution network using new sensitivity index with probabilistic load models. In Proceedings of the 2015 2nd International Conference on Recent Advances in Engineering & Computational Sciences (RAECS), Chandigarh, India, 21–22 December 2015; pp. 1–6.Sharma, A.K.; Saxena, A.; Tiwari, R. Optimal Placement of SVC Incorporating Installation Cost. Int. J. Hybrid Inf. Technol. 2016, 9, 289–302. [CrossRef]Bayer, Christophe Pierre, Fionna Klasen, and Hubertus Adam. 2007. “Association of Trauma and PTSD Symptoms with Openness to Reconciliation and Feelings of Revenge Among Former Ugandan and Congolese Child Soldiers.” Journal of the American Medical Association 298 (5): 555-559. https://doi.org/10.1001/jama.298.5.555 8.Tuzikova, V.; Tlusty, J.; Muller, Z. A novel power losses reduction method based on a particle swarm optimization algorithm using STATCOM. Energies 2018, 11, 2851Mora-Burbano, J.A.; Fonseca-Díaz, C.D.; Montoya, O.D. Application of the SSA for Optimal Reactive Power Compensation in Radial and Meshed Distribution Using D-STATCOMs. Algorithms 2022, 15, 345.Garrido, V.M.; Montoya, O.D.; Medina-Quesada, Á.; Hernández, J.C. Optimal Reactive Power Compensation in Distribution Networks with Radial and Meshed Structures Using D-STATCOMs: A Mixed-Integer Convex Approach. Sensors 2022, 22, 8676. [CrossRef]Zhang, Y. An improved generalized normal distribution optimization and its applications in numerical problems and engineering design problems. Artif. Intell. Rev. 2022Abdel-Basset, M.; Mohamed, R.; Abouhawwash, M.; Chang, V.; Askar, S. A Local Search-Based Generalized Normal Distribution Algorithm for Permutation Flow Shop Scheduling. Appl. Sci. 2021, 11, 4837Zhang, Y.; Jin, Z.; Mirjalili, S. Generalized normal distribution optimization and its applications in parameter extraction of photovoltaic models. Energy Convers. Manag. 2020, 224, 113301Lazarou, S.; Vita, V.; Christodoulou, C.; Ekonomou, L. Calculating Operational Patterns for Electric Vehicle Charging on a Real Distribution Network Based on Renewables’ Production. Energies 2018, 11, 2400.Marini, A.; Mortazavi, S.; Piegari, L.; Ghazizadeh, M.S. An efficient graph-based power flow algorithm for electrical distribution systems with a comprehensive modeling of distributed generations. Electr. Power Syst. Res. 2019, 170, 229–243. [Kaur, S.; Kumbhar, G.; Sharma, J. A MINLP technique for optimal placement of multiple DG units in distribution systems. Int. J. Electr. Power Energy Syst. 2014, 63, 609–617.Montoya, O.D.; Gil-González, W. On the numerical analysis based on successive approximations for power flow problems in AC distribution systems. Electr. Power Syst. Res. 2020, 187, 106454.Herrera-Briñez, M.C.; Montoya, O.D.; Alvarado-Barrios, L.; Chamorro, H.R. The Equivalence between Successive Approximations and Matricial Load Flow Formulations. Appl. Sci. 2021, 11,Saravan, M.; Slochanal, S.; Venkatesh, P.; Abraham, P. Application of PSO technique for optimal location of FACTS devices considering system loadability and cost of installation. 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