Optimal Location and Sizing of DGs in DC Networks Using a Hybrid Methodology Based on the PPBIL Algorithm and the VSA
In this paper, we propose a master–slave methodology to address the problem of optimal integration (location and sizing) of Distributed Generators (DGs) in Direct Current (DC) networks. This proposed methodology employs a parallel version of the Population-Based Incremental Learning (PPBIL) optimiza...
- Autores:
-
Grisales-Noreña, Luis Fernando
Montoya, Oscar Danilo
Hincapié-Isaza, Ricardo Alberto
Granada Echeverri, Mauricio
Perea-Moreno, Alberto-Jesus
- 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:20.500.12585/10396
- Palabra clave:
- Direct current grids
Distributed generation
Direct current networks
Metaheuristic optimization
Parallel processing tools
Power loss reduction
LEMB
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Optimal Location and Sizing of DGs in DC Networks Using a Hybrid Methodology Based on the PPBIL Algorithm and the VSA |
| title |
Optimal Location and Sizing of DGs in DC Networks Using a Hybrid Methodology Based on the PPBIL Algorithm and the VSA |
| spellingShingle |
Optimal Location and Sizing of DGs in DC Networks Using a Hybrid Methodology Based on the PPBIL Algorithm and the VSA Direct current grids Distributed generation Direct current networks Metaheuristic optimization Parallel processing tools Power loss reduction LEMB |
| title_short |
Optimal Location and Sizing of DGs in DC Networks Using a Hybrid Methodology Based on the PPBIL Algorithm and the VSA |
| title_full |
Optimal Location and Sizing of DGs in DC Networks Using a Hybrid Methodology Based on the PPBIL Algorithm and the VSA |
| title_fullStr |
Optimal Location and Sizing of DGs in DC Networks Using a Hybrid Methodology Based on the PPBIL Algorithm and the VSA |
| title_full_unstemmed |
Optimal Location and Sizing of DGs in DC Networks Using a Hybrid Methodology Based on the PPBIL Algorithm and the VSA |
| title_sort |
Optimal Location and Sizing of DGs in DC Networks Using a Hybrid Methodology Based on the PPBIL Algorithm and the VSA |
| dc.creator.fl_str_mv |
Grisales-Noreña, Luis Fernando Montoya, Oscar Danilo Hincapié-Isaza, Ricardo Alberto Granada Echeverri, Mauricio Perea-Moreno, Alberto-Jesus |
| dc.contributor.author.none.fl_str_mv |
Grisales-Noreña, Luis Fernando Montoya, Oscar Danilo Hincapié-Isaza, Ricardo Alberto Granada Echeverri, Mauricio Perea-Moreno, Alberto-Jesus |
| dc.subject.keywords.es_CO.fl_str_mv |
Direct current grids Distributed generation Direct current networks Metaheuristic optimization Parallel processing tools Power loss reduction |
| topic |
Direct current grids Distributed generation Direct current networks Metaheuristic optimization Parallel processing tools Power loss reduction LEMB |
| dc.subject.armarc.none.fl_str_mv |
LEMB |
| description |
In this paper, we propose a master–slave methodology to address the problem of optimal integration (location and sizing) of Distributed Generators (DGs) in Direct Current (DC) networks. This proposed methodology employs a parallel version of the Population-Based Incremental Learning (PPBIL) optimization method in the master stage to solve the location problem and the Vortex Search Algorithm (VSA) in the slave stage to solve the sizing problem. In addition, it uses the reduction of power losses as the objective function, considering all the constraints associated with the technical conditions specific to DGs and DC networks. To validate its effectiveness and robustness, we use as comparison methods, different solution methodologies that have been reported in the specialized literature, as well as two test systems (the 21 and 69-bus test systems). All simulations were performed in MATLAB. According to the results, the proposed hybrid (PPBIL–VSA) methodology provides the best trade-off between quality of the solution and processing times and exhibits an adequate repeatability every time it is executed. |
| publishDate |
2021 |
| dc.date.issued.none.fl_str_mv |
2021-08-11 |
| dc.date.accessioned.none.fl_str_mv |
2022-01-24T21:14:18Z |
| dc.date.available.none.fl_str_mv |
2022-01-24T21:14:18Z |
| dc.date.submitted.none.fl_str_mv |
2022-01-24 |
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info:eu-repo/semantics/article |
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info:eu-repo/semantics/restrictedAccess |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
| dc.identifier.citation.es_CO.fl_str_mv |
Grisales-Noreña, L.F.; Montoya, O.D.; Hincapié-Isaza, R.A.; Granada Echeverri, M; Perea-Moreno, A.-J. Optimal Location and Sizing of DGs in DC Networks Using a Hybrid Methodology Based on the PPBIL Algorithm and the VSA. Mathematics 2021, 9, 1913. https://doi.org/0.3390/math9161913 |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/10396 |
| dc.identifier.doi.none.fl_str_mv |
https://doi.org/0.3390/math9161913 |
| dc.identifier.instname.es_CO.fl_str_mv |
Universidad Tecnológica de Bolívar |
| dc.identifier.reponame.es_CO.fl_str_mv |
Repositorio Universidad Tecnológica de Bolívar |
| identifier_str_mv |
Grisales-Noreña, L.F.; Montoya, O.D.; Hincapié-Isaza, R.A.; Granada Echeverri, M; Perea-Moreno, A.-J. Optimal Location and Sizing of DGs in DC Networks Using a Hybrid Methodology Based on the PPBIL Algorithm and the VSA. Mathematics 2021, 9, 1913. https://doi.org/0.3390/math9161913 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
| url |
https://hdl.handle.net/20.500.12585/10396 https://doi.org/0.3390/math9161913 |
| dc.language.iso.es_CO.fl_str_mv |
eng |
| language |
eng |
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http://purl.org/coar/access_right/c_abf2 |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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info:eu-repo/semantics/openAccess |
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Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://purl.org/coar/access_right/c_abf2 |
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openAccess |
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18 páginas |
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application/pdf |
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Cartagena de Indias |
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Mathematics - vol. 9 n° 6 2021 |
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Universidad Tecnológica de Bolívar |
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Grisales-Noreña, Luis Fernando7c27cda4-5fe4-4686-8f72-b0442c58a5d1Montoya, Oscar Danilo8a59ede1-6a4a-4d2e-abdc-d0afb14d4480Hincapié-Isaza, Ricardo Alberto07b72a3b-f4c3-4e14-8adc-c64302a941a7Granada Echeverri, Mauriciodaca4075-7deb-456d-ad03-02a19c19a392Perea-Moreno, Alberto-Jesuse78da438-8ed5-40ab-a12c-74e84e6d691b2022-01-24T21:14:18Z2022-01-24T21:14:18Z2021-08-112022-01-24Grisales-Noreña, L.F.; Montoya, O.D.; Hincapié-Isaza, R.A.; Granada Echeverri, M; Perea-Moreno, A.-J. Optimal Location and Sizing of DGs in DC Networks Using a Hybrid Methodology Based on the PPBIL Algorithm and the VSA. Mathematics 2021, 9, 1913. https://doi.org/0.3390/math9161913https://hdl.handle.net/20.500.12585/10396https://doi.org/0.3390/math9161913Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarIn this paper, we propose a master–slave methodology to address the problem of optimal integration (location and sizing) of Distributed Generators (DGs) in Direct Current (DC) networks. This proposed methodology employs a parallel version of the Population-Based Incremental Learning (PPBIL) optimization method in the master stage to solve the location problem and the Vortex Search Algorithm (VSA) in the slave stage to solve the sizing problem. In addition, it uses the reduction of power losses as the objective function, considering all the constraints associated with the technical conditions specific to DGs and DC networks. To validate its effectiveness and robustness, we use as comparison methods, different solution methodologies that have been reported in the specialized literature, as well as two test systems (the 21 and 69-bus test systems). All simulations were performed in MATLAB. According to the results, the proposed hybrid (PPBIL–VSA) methodology provides the best trade-off between quality of the solution and processing times and exhibits an adequate repeatability every time it is executed.18 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_abf2Mathematics - vol. 9 n° 6 2021Optimal Location and Sizing of DGs in DC Networks Using a Hybrid Methodology Based on the PPBIL Algorithm and the VSAinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/restrictedAccesshttp://purl.org/coar/resource_type/c_2df8fbb1Direct current gridsDistributed generationDirect current networksMetaheuristic optimizationParallel processing toolsPower loss reductionLEMBCartagena de IndiasGrisales-Noreña, L.F.; Gonzalez Montoya, D.; Ramos-Paja, C.A. Optimal sizing and location of distributed generators based on PBIL and PSO techniques. Energies 2018, 11, 1018.Hassan, A.S.; Othman, E.A.; Bendary, F.M.; Ebrahim, M.A. Optimal integration of distributed generation resources in active distribution networks for techno-economic benefits. Energy Rep. 2020, 6, 3462–3471.Mishra, R.K.; Swarup, K.S. Adaptive Weight-Based Self Reconfiguration of Smart Distribution Network With Intelligent Agents. IEEE Trans. Emerg. Top. Comput. Intell. 2018, 2, 464–472.Gil-González, W.; Montoya, O.D.; Rajagopalan, A.; Grisales-Noreña, L.F.; Hernández, J.C. Optimal selection and location of fixed-step capacitor banks in distribution networks using a discrete version of the vortex search algorithm. Energies 2020, 13, 4914.Montoya, 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, 3353.Nunez Forestieri, J.; Farasat, M. Integrative sizing/real-time energy management of a hybrid supercapacitor/undersea energy storage system for grid integration of wave energy conversion systems. IEEE J. Emerg. Sel. Top. Power Electron. 2020, 8, 3798–3810.Hashimoto, J.; Ustun, T.S.; Suzuki, M.; Sugahara, S.; Hasegawa, M.; Otani, K. Advanced Grid Integration Test Platform for Increased Distributed Renewable Energy Penetration in Smart Grids. IEEE Access 2021, 9, 34040–34053.Abdmouleh, Z.; Gastli, A.; Ben-Brahim, L.; Haouari, M.; Al-Emadi, N.A. Review of optimization techniques applied for the integration of distributed generation from renewable energy sources. Renew. Energy 2017, 113, 266–280.Ehsan, A.; Yang, Q. Optimal integration and planning of renewable distributed generation in the power distribution networks: A review of analytical techniques. Appl. Energy 2018, 210, 44–59.Noreña, L.F.G.; Cuestas, B.J.R.; Ramirez, F.E.J. Ubicación y dimensionamiento de generación distribuida: Una revisión. Cienc. E Ing. Neogranadina 2017, 27, 157–176.Bizuayehu, A.W.; de la Nieta, A.A.S.; Contreras, J.; Catalao, J.P. Impacts of stochastic wind power and storage participation on economic dispatch in distribution systems. IEEE Trans. Sustain. Energy 2016, 7, 1336–1345Grisales-Noreña, L.F.; Montoya, O.D.; Ramos-Paja, C.A. An energy management system for optimal operation of BSS in DC distributed generation environments based on a parallel PSO algorithm. J. Energy Storage 2020, 29, 101488.Grisales-Noreña, L.F.; Ramos-Paja, C.A.; Gonzalez-Montoya, D.; Alcalá, G.; Hernandez-Escobedo, Q. Energy management in PV based microgrids designed for the Universidad Nacional de Colombia. Sustainability 2020, 12, 1219.Dragiˇcevi´c, T.; Lu, X.; Vasquez, J.C.; Guerrero, J.M. DC microgrids—Part II: A review of power architectures, applications, and standardization issues. IEEE Trans. Power Electron. 2015, 31, 3528–3549.Montoya, O.D.; Gil-González, W.; Grisales-Noreña, L.F. On the mathematical modeling for optimal selecting of calibers of conductors in DC radial distribution networks: An MINLP approach. Electr. Power Syst. Res. 2021, 194, 107072.Rodriguez, P.; Rouzbehi, K. Multi-terminal DC grids: Challenges and prospects. J. Mod. Power Syst. Clean Energy 2017, 5, 515–523Montoya, O.D.; Gil-González, W. A MIQP model for optimal location and sizing of dispatchable DGs in DC networks. Energy Syst. 2021, 12, 181–202.Ji, H.; Wang, C.; Li, P.; Zhao, J.; Song, G.; Wu, J. Quantified flexibility evaluation of soft open points to improve distributed generator penetration in active distribution networks based on difference-of-convex programming. Appl. Energy 2018, 218, 338–348.Wong, L.A.; Ramachandaramurthy, V.K.; Taylor, P.; Ekanayake, J.; Walker, S.L.; Padmanaban, S. Review on the optimal placement, sizing and control of an energy storage system in the distribution network. J. Energy Storage 2019, 21, 489–504.Grisales-Noreña, L.F.; Montoya, O.D.; Ramos-Paja, C.A.; Hernandez-Escobedo, Q.; Perea-Moreno, A.J. Optimal Location and Sizing of Distributed Generators in DC Networks Using a Hybrid Method Based on Parallel PBIL and PSO. Electronics 2020, 9, 1808Wang, P.; Wang, W.; Xu, D. Optimal sizing of distributed generations in dc microgrids with comprehensive consideration of system operation modes and operation targets. IEEE Access 2018, 6, 31129–31140.Montoya, O.; Gil-González, W.; Grisales-Noreña, L. Optimal Power Dispatch of Dgs in Dc Power Grids: A Hybrid Gauss-SeidelGenetic-Algorithm Methodology for Solving the OPF Problem; World Scientific and Engineering Academy and Society: Athens, Greece, 2018.Garzon-Rivera, O.; Ocampo, J.; Grisales-Norena, L.; Montoya, O.; Rojas-Montano, J. Optimal Power Flow in Direct Current Networks Using the Antlion Optimizer. Stat. Optim. Inf. Comput. 2020, 8, 846–857.Grisales-Noreña, L.F.; Garzon-Rivera, O.D.; Montoya, O.D.; Ramos-Paja, C.A. Hybrid metaheuristic optimization methods for optimal location and sizing DGs in DC networks. In Workshop on Engineering Applications; Springer: Cham, Switzerland, 2019; pp. 214–225.Montoya, O.D.; Gil-González, W.; Grisales-Noreña, L. Vortex search algorithm for optimal power flow analysis in DC resistive networks with CPLs. IEEE Trans. Circuits Syst. II Express Briefs 2019, 67, 1439–1443.Montoya, O.D.; Garrido, V.M.; Gil-González, W.; Grisales-Noreña, L.F. Power flow analysis in DC grids: Two alternative numerical methods. IEEE Trans. Circuits Syst. II Express Briefs 2019, 66, 1865–1869.Grisales-Noreña, L.F.; Montoya, O.D.; Gil-González, W.J.; Perea-Moreno, A.J.; Perea-Moreno, M.A. A Comparative Study on Power Flow Methods for Direct-Current Networks Considering Processing Time and Numerical Convergence Errors. Electronics 2020, 9, 2062.Montoya, O.D.; Grisales-Noreña, L.F.; Gil-González, W. Triangular matrix formulation for power flow analysis in radial DC resistive grids with CPLs. IEEE Trans. Circuits Syst. II Express Briefs 2019, 67, 1094–1098.Molina-Martin, F.; Montoya, O.D.; Grisales-Noreña, L.F.; Hernández, J.C. A Mixed-Integer Conic Formulation for Optimal Placement and Dimensioning of DGs in DC Distribution Networks. 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