Optimal Placement and sizing of D-STATCOM in radial and meshed distribution networks using a discrete-continuous version of the genetic algorithm

In 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 w...

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Autores:
Castiblanco-Pérez, Cristian Mateo
Toro-Rodríguez, David Esteban
Montoya, Oscar Danilo
Giral-Ramírez, Diego Armando
Tipo de recurso:
Fecha de publicación:
2021
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/10373
Acceso en línea:
https://hdl.handle.net/20.500.12585/10373
https://doi.org/10.3390/electronics10121452
Palabra clave:
Distribution networks
Distribution static compensators
Discrete-continuous genetic algorithm
Radial and meshed configurations
Evolutive computation
LEMB
Rights
openAccess
License
http://creativecommons.org/licenses/by-nc-nd/4.0/
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dc.title.spa.fl_str_mv Optimal Placement and sizing of D-STATCOM in radial and meshed distribution networks using a discrete-continuous version of the genetic algorithm
title Optimal Placement and sizing of D-STATCOM in radial and meshed distribution networks using a discrete-continuous version of the genetic algorithm
spellingShingle Optimal Placement and sizing of D-STATCOM in radial and meshed distribution networks using a discrete-continuous version of the genetic algorithm
Distribution networks
Distribution static compensators
Discrete-continuous genetic algorithm
Radial and meshed configurations
Evolutive computation
LEMB
title_short Optimal Placement and sizing of D-STATCOM in radial and meshed distribution networks using a discrete-continuous version of the genetic algorithm
title_full Optimal Placement and sizing of D-STATCOM in radial and meshed distribution networks using a discrete-continuous version of the genetic algorithm
title_fullStr Optimal Placement and sizing of D-STATCOM in radial and meshed distribution networks using a discrete-continuous version of the genetic algorithm
title_full_unstemmed Optimal Placement and sizing of D-STATCOM in radial and meshed distribution networks using a discrete-continuous version of the genetic algorithm
title_sort Optimal Placement and sizing of D-STATCOM in radial and meshed distribution networks using a discrete-continuous version of the genetic algorithm
dc.creator.fl_str_mv Castiblanco-Pérez, Cristian Mateo
Toro-Rodríguez, David Esteban
Montoya, Oscar Danilo
Giral-Ramírez, Diego Armando
dc.contributor.author.none.fl_str_mv Castiblanco-Pérez, Cristian Mateo
Toro-Rodríguez, David Esteban
Montoya, Oscar Danilo
Giral-Ramírez, Diego Armando
dc.subject.keywords.spa.fl_str_mv Distribution networks
Distribution static compensators
Discrete-continuous genetic algorithm
Radial and meshed configurations
Evolutive computation
topic Distribution networks
Distribution static compensators
Discrete-continuous genetic algorithm
Radial and meshed configurations
Evolutive computation
LEMB
dc.subject.armarc.none.fl_str_mv LEMB
description In 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 robustness
publishDate 2021
dc.date.accessioned.none.fl_str_mv 2021-09-28T14:34:24Z
dc.date.available.none.fl_str_mv 2021-09-28T14:34:24Z
dc.date.issued.none.fl_str_mv 2021-06-02
dc.date.submitted.none.fl_str_mv 2021-09-27
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.citation.spa.fl_str_mv Castiblanco-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/electronics10121452
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12585/10373
dc.identifier.doi.none.fl_str_mv https://doi.org/10.3390/electronics10121452
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 Castiblanco-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/electronics10121452
Universidad Tecnológica de Bolívar
Repositorio Universidad Tecnológica de Bolívar
url https://hdl.handle.net/20.500.12585/10373
https://doi.org/10.3390/electronics10121452
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 20 páginas
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 Electronics 2021, 10, 1452
institution Universidad Tecnológica de Bolívar
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spelling Castiblanco-Pérez, Cristian Mateo2ec26353-73f4-43f8-a859-ed63820e5b4cToro-Rodríguez, David Esteban9d15205b-4f51-4bab-9275-8b1c41b17cf1Montoya, Oscar Danilo8a59ede1-6a4a-4d2e-abdc-d0afb14d4480Giral-Ramírez, Diego Armandoa9612d05-bc90-49f9-94c7-20a0766e00f52021-09-28T14:34:24Z2021-09-28T14:34:24Z2021-06-022021-09-27Castiblanco-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/electronics10121452https://hdl.handle.net/20.500.12585/10373https://doi.org/10.3390/electronics10121452Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarIn 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 robustness20 páginasapplication/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_abf2Electronics 2021, 10, 1452Optimal Placement and sizing of D-STATCOM in radial and meshed distribution networks using a discrete-continuous version of the genetic algorithminfo:eu-repo/semantics/articleinfo:eu-repo/semantics/restrictedAccesshttp://purl.org/coar/resource_type/c_2df8fbb1Distribution networksDistribution static compensatorsDiscrete-continuous genetic algorithmRadial and meshed configurationsEvolutive computationLEMBCartagena de IndiasInvestigadoresCavellucci, C.; Lyra, C. Minimization of Energy Losses in Electric Power Distribution Systems by Intelligent Search Strategies. IFAC Proc. Vol. 1995, 28, 589–594Montoya, 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. [Alam, M.S.; Arefifar, S.A. Energy Management in Power Distribution Systems: Review, Classification, Limitations and Challenges. IEEE Access 2019, 7, 92979–93001Sadovskaia, 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, 98–109Comisión de Regulación de Energía y Gas. CREG. Resolución CREG 119 de 21 de Diciembre de 2007; CREG: Bogotá, Colombia, 2007Colmenar-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.Muruganantham, 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, 2017Elsheikh, A.; Helmy, Y.; Abouelseoud, Y.; Elsherif, A. Optimal capacitor placement and sizing in radial electric power systems. Alex. Eng. J. 2014, 53, 809–816Tamilselvan, V.; Jayabarathi, T.; Raghunathan, T.; Yang, X.S. Optimal capacitor placement in radial distribution systems using flower pollination algorithm. Alex. Eng. J. 2018, 57, 2775–2786Sirjani, 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, 688–694Montoya, 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, 3353Sedighizadeh, 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, 83–95Zhang, Q.; Chen, H.; Luo, J.; Xu, Y.; Wu, C.; Li, C. Chaos Enhanced Bacterial Foraging Optimization for Global Optimization. IEEE Access 2018, 6, 64905–64919Yuvaraj, T.; Devabalaji, K.; Ravi, K. Optimal Placement and Sizing of DSTATCOM Using Harmony Search Algorithm. Energy Procedia 2015, 79, 759–765Taher, 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.Marjani, 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, e2723Tolabi, 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, 210–218Gupta, A.R.; Kumar, A. Energy Savings Using D-STATCOM Placement in Radial Distribution System; Elsevier: Amsterdam, The Netherlands, 2015; Volume 70, pp. 558–564. [Rukmani, 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, 4615Samimi, 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. 1–5Muthukumar, 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.Sannigrahi, 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, 2018Rajan, 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;Amin, A.; Kamel, S.; Selim, A.; Nasrat, L. 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RESOLUCIÓN No. 024 de 2005; CREG: Bogotá, Colombia, 2005.Montoya, 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, 5802Shen, T.; Li, Y.; Xiang, J. A Graph-Based Power Flow Method for Balanced Distribution Systems. Energies 2018, 11, 511Vasconcellos, D.B.; González, P.P.; González, G.F. Control de demanda eléctrica aplicando algoritmos genéticos. Ingeniare Rev. Chilena de Ingeniería 2017, 25, 389–398Zhao, J.-Q.; Wang, L. Center Based Genetic Algorithm and its application to the stiffness equivalence of the aircraft wing. Expert Syst. Appl. 2011, 38, 6254–6261Duan, 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, 88–95Singh, B.; Singh, S. GA-based optimization for integration of DGs, STATCOM and PHEVs in distribution systems. Energy Rep. 2019, 5, 84–103Venkatesh, B.; Ranjan, R. Optimal radial distribution system reconfiguration using fuzzy adaptation of evolutionary programming. Int. J. Electr. Power Energy Syst. 2003, 25, 775–780http://purl.org/coar/resource_type/c_2df8fbb1ORIGINAL[Art. 29] Optimal Placement and Sizing of D-S_Oscar Danilo Montoya.pdf[Art. 29] Optimal Placement and Sizing of D-S_Oscar Danilo Montoya.pdfapplication/pdf603177https://repositorio.utb.edu.co/bitstream/20.500.12585/10373/1/%5bArt.%2029%5d%20Optimal%20Placement%20and%20Sizing%20of%20D-S_Oscar%20Danilo%20Montoya.pdf6fb100d1b8ea8f7714a88b9b9ee37720MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://repositorio.utb.edu.co/bitstream/20.500.12585/10373/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-83182https://repositorio.utb.edu.co/bitstream/20.500.12585/10373/3/license.txte20ad307a1c5f3f25af9304a7a7c86b6MD53TEXT[Art. 29] Optimal Placement and Sizing of D-S_Oscar Danilo Montoya.pdf.txt[Art. 29] Optimal Placement and Sizing of D-S_Oscar Danilo Montoya.pdf.txtExtracted 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