Optimal integration of photovoltaic sources in distribution networks for daily energy losses minimization using the vortex search algorithm
This paper deals with the optimal siting and sizing problem of photovoltaic (PV) generators in electrical distribution networks considering daily load and generation profiles. It proposes the discrete-continuous version of the vortex search algorithm (DCVSA) to locate and size the PV sources where t...
- Autores:
-
Paz-Rodríguez, Alejandra
Castro-Ordoñez, Juan Felipe
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:20.500.12585/10370
- Palabra clave:
- Discrete-continuous vortex search algorithm
Energy renewable
Photovoltaic generation
Optimal power flow
Mathematic model
Minimization losses
LEMB
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Optimal integration of photovoltaic sources in distribution networks for daily energy losses minimization using the vortex search algorithm |
| title |
Optimal integration of photovoltaic sources in distribution networks for daily energy losses minimization using the vortex search algorithm |
| spellingShingle |
Optimal integration of photovoltaic sources in distribution networks for daily energy losses minimization using the vortex search algorithm Discrete-continuous vortex search algorithm Energy renewable Photovoltaic generation Optimal power flow Mathematic model Minimization losses LEMB |
| title_short |
Optimal integration of photovoltaic sources in distribution networks for daily energy losses minimization using the vortex search algorithm |
| title_full |
Optimal integration of photovoltaic sources in distribution networks for daily energy losses minimization using the vortex search algorithm |
| title_fullStr |
Optimal integration of photovoltaic sources in distribution networks for daily energy losses minimization using the vortex search algorithm |
| title_full_unstemmed |
Optimal integration of photovoltaic sources in distribution networks for daily energy losses minimization using the vortex search algorithm |
| title_sort |
Optimal integration of photovoltaic sources in distribution networks for daily energy losses minimization using the vortex search algorithm |
| dc.creator.fl_str_mv |
Paz-Rodríguez, Alejandra Castro-Ordoñez, Juan Felipe Montoya, Oscar Danilo Giral-Ramírez, Diego Armando |
| dc.contributor.author.none.fl_str_mv |
Paz-Rodríguez, Alejandra Castro-Ordoñez, Juan Felipe Montoya, Oscar Danilo Giral-Ramírez, Diego Armando |
| dc.subject.keywords.spa.fl_str_mv |
Discrete-continuous vortex search algorithm Energy renewable Photovoltaic generation Optimal power flow Mathematic model Minimization losses |
| topic |
Discrete-continuous vortex search algorithm Energy renewable Photovoltaic generation Optimal power flow Mathematic model Minimization losses LEMB |
| dc.subject.armarc.none.fl_str_mv |
LEMB |
| description |
This paper deals with the optimal siting and sizing problem of photovoltaic (PV) generators in electrical distribution networks considering daily load and generation profiles. It proposes the discrete-continuous version of the vortex search algorithm (DCVSA) to locate and size the PV sources where the discrete part of the codification defines the nodes. Renewable generators are installed in these nodes, and the continuous section determines their optimal sizes. In addition, through the successive approximation power flow method, the objective function of the optimization model is obtained. This objective function is related to the minimization of the daily energy losses. This method allows determining the power losses in each period for each renewable generation input provided by the DCVSA (i.e., location and sizing of the PV sources). Numerical validations in the IEEE 33- and IEEE 69-bus systems demonstrate that: (i) the proposed DCVSA finds the optimal global solution for both test feeders when the location and size of the PV generators are explored, considering the peak load scenario. (ii) In the case of the daily operative scenario, the total reduction of energy losses for both test feeders are 23.3643% and 24.3863%, respectively; and (iii) the DCVSA presents a better numerical performance regarding the objective function value when compared with the BONMIN solver in the GAMS software, which demonstrates the effectiveness and robustness of the proposed master-slave optimization algorithm. |
| publishDate |
2021 |
| dc.date.accessioned.none.fl_str_mv |
2021-09-28T14:28:49Z |
| dc.date.available.none.fl_str_mv |
2021-09-28T14:28:49Z |
| dc.date.issued.none.fl_str_mv |
2021-04-20 |
| dc.date.submitted.none.fl_str_mv |
2021-09-27 |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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info:eu-repo/semantics/article |
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info:eu-repo/semantics/restrictedAccess |
| dc.type.spa.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
| dc.identifier.citation.spa.fl_str_mv |
Paz-Rodríguez, A.; Castro-Ordoñez, J.F.; Montoya, O.D.; Giral-Ramírez, D.A. Optimal Integration of Photovoltaic Sources in Distribution Networks for Daily Energy Losses Minimization Using the Vortex Search Algorithm. Appl. Sci. 2021, 11, 4418. https://doi.org/10.3390/app11104418 |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/10370 |
| dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.3390/app11104418 |
| 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 |
Paz-Rodríguez, A.; Castro-Ordoñez, J.F.; Montoya, O.D.; Giral-Ramírez, D.A. Optimal Integration of Photovoltaic Sources in Distribution Networks for Daily Energy Losses Minimization Using the Vortex Search Algorithm. Appl. Sci. 2021, 11, 4418. https://doi.org/10.3390/app11104418 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
| url |
https://hdl.handle.net/20.500.12585/10370 https://doi.org/10.3390/app11104418 |
| dc.language.iso.spa.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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Appl. Sci. 2021, 11, 4418 |
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Universidad Tecnológica de Bolívar |
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Paz-Rodríguez, Alejandra625ebfd4-924f-4a3a-9229-f56b1b0f7289Castro-Ordoñez, Juan Felipe304e84fc-18ce-4cf0-8735-cba5e884a5feMontoya, Oscar Danilo8a59ede1-6a4a-4d2e-abdc-d0afb14d4480Giral-Ramírez, Diego Armandoa9612d05-bc90-49f9-94c7-20a0766e00f52021-09-28T14:28:49Z2021-09-28T14:28:49Z2021-04-202021-09-27Paz-Rodríguez, A.; Castro-Ordoñez, J.F.; Montoya, O.D.; Giral-Ramírez, D.A. Optimal Integration of Photovoltaic Sources in Distribution Networks for Daily Energy Losses Minimization Using the Vortex Search Algorithm. Appl. Sci. 2021, 11, 4418. https://doi.org/10.3390/app11104418https://hdl.handle.net/20.500.12585/10370https://doi.org/10.3390/app11104418Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThis paper deals with the optimal siting and sizing problem of photovoltaic (PV) generators in electrical distribution networks considering daily load and generation profiles. It proposes the discrete-continuous version of the vortex search algorithm (DCVSA) to locate and size the PV sources where the discrete part of the codification defines the nodes. Renewable generators are installed in these nodes, and the continuous section determines their optimal sizes. In addition, through the successive approximation power flow method, the objective function of the optimization model is obtained. This objective function is related to the minimization of the daily energy losses. This method allows determining the power losses in each period for each renewable generation input provided by the DCVSA (i.e., location and sizing of the PV sources). Numerical validations in the IEEE 33- and IEEE 69-bus systems demonstrate that: (i) the proposed DCVSA finds the optimal global solution for both test feeders when the location and size of the PV generators are explored, considering the peak load scenario. (ii) In the case of the daily operative scenario, the total reduction of energy losses for both test feeders are 23.3643% and 24.3863%, respectively; and (iii) the DCVSA presents a better numerical performance regarding the objective function value when compared with the BONMIN solver in the GAMS software, which demonstrates the effectiveness and robustness of the proposed master-slave optimization algorithm.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_abf2Appl. Sci. 2021, 11, 4418Optimal integration of photovoltaic sources in distribution networks for daily energy losses minimization using the vortex search algorithminfo:eu-repo/semantics/articleinfo:eu-repo/semantics/restrictedAccesshttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Discrete-continuous vortex search algorithmEnergy renewablePhotovoltaic generationOptimal power flowMathematic modelMinimization lossesLEMBCartagena de IndiasPúblico generalUPME. Reference Expansion Planning Generacion Transmision 2004–2018; Resreport, Unidad de Planeación Minero Energética: Bogotá, Colombia, 2004Castro-Galeano, J.C.; Cabra-Sarmiento, W.J.; Ortiz-Portilla, J.F. Fault and load flows analysis of electricity transmission and distribution system in Casanare (Colombia). Rev. Fac. Ing. 2017, 26, 7.Montoya, O.D.; Serra, F.M.; Angelo, C.H.D. On the Efficiency in Electrical Networks with AC and DC Operation Technologies: A Comparative Study at the Distribution Stage. Electronics 2020, 9, 1352Grisales-Noreña, L.; Montoya, D.G.; Ramos-Paja, C.Optimal Sizing and Location of Distributed Generators Based on PBIL and PSO Techniques. Energies 2018, 11, 1018.Montoya, O.D.; Gil-González, W.; Orozco-Henao, C. Vortex search and Chu-Beasley genetic algorithms for optimal location and sizing of distributed generators in distribution networks: A novel hybrid approach. Eng. Sci. Technol. Int. J. 2020, 23, 1351–1363Montoya, O.D.; Molina-Cabrera, A.; Chamorro, H.R.; Alvarado-Barrios, L.; Rivas-Trujillo, E. A Hybrid Approach Based on SOCP and the Discrete Version of the SCA for Optimal Placement and Sizing DGs in AC Distribution Networks. Electronics 2020, 10, 26.Montoya, 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, 2175Esmaeilian, H.; Fadaeinedjad, R.; Attari, S. Distribution network reconfiguration to reduce losses and enhance reliability using binary gravitational search algorithm. In Proceedings of the 22nd International Conference and Exhibition on Electricity Distribution (CIRED 2013), Stockholm, Sweden, 10–13 June 2013Krstic, N. Reduction of Energy and Power Losses in Distribution Network Using Energy Storage Systems. In Proceedings of the 2020 55th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST), Nis, Serbia, 10–12 September 2020.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, 609–617Reyes-Belmonte, M.A. Quo Vadis Solar Energy Research? Appl. Sci. 2021, 11, 3015.Catalbas, M.C.; Gulten, A. Circular structures of puffer fish: A new metaheuristic optimization algorithm. In Proceedings of the 2018 Third International Conference on Electrical and Biomedical Engineering, Clean Energy and Green Computing (EBECEGC), Beirut, Lebanon, 24–26 April 2018.Samala, R.K.; Kotapuri, M.R. Hybridization of Metaheuristic Algorithms for Optimal Location and Capacity in Radial Distribution System. In Proceedings of the 2019 2nd International Conference on Power and Embedded Drive Control (ICPEDC), Chennai, India, 21–23 August 2019.Montoya, O.D.; Gil-González, W.; Grisales-Noreña, L. An exact MINLP model for optimal location and sizing of DGs in distribution networks: A general algebraic modeling system approach. Ain Shams Eng. J. 2020, 11, 409–418Montoya, 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, 106454Moradi, M.; Abedini, M. A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems. Int. J. Electr. Power Energy Syst. 2012, 34, 66–74Injeti, 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. Int. J. Electr. Power Energy Syst. 2013, 45, 142–151Mohanty, B.; Tripathy, S. A teaching learning based optimization technique for optimal location and size of DG in distribution network. J. Electr. Syst. Inf. Technol. 2016, 3, 33–44Kollu, R.; Rayapudi, S.R.; Sadhu, V.L.N. A novel method for optimal placement of distributed generation in distribution systems using HSDO. Int. Trans. Electr. Energy Syst. 2012, 24, 547–561Sultana, S.; Roy, P.K. Multi-objective quasi-oppositional teaching learning based optimization for optimal location of distributed generator in radial distribution systems. Int. J. Electr. Power Energy Syst. 2014, 63, 534–545Muthukumar, 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, 299–319Jamian, J.; Mustafa, M.; Mokhlis, H. Optimal multiple distributed generation output through rank evolutionary particle swarm optimization. Neurocomputing 2015, 152, 190–198Gupta, S.; Saxena, A.; Soni, B.P. Optimal Placement Strategy of Distributed Generators based on Radial Basis Function Neural Network in Distribution Networks. Procedia Comput. Sci. 2015, 57, 249–257Bayat, A.; Bagheri, A. Optimal active and reactive power allocation in distribution networks using a novel heuristic approach. Appl. Energy 2019, 233–234, 71–85Moradi, M.; Abedini, M. A novel method for optimal DG units capacity and location in Microgrids. Int. J. Electr. Power Energy Syst. 2016, 75, 236–244Sultana, S.; Roy, P.K. Krill herd algorithm for optimal location of distributed generator in radial distribution system. Appl. Soft Comput. 2016, 40, 391–404Nguyen, T.P.; Dieu, V.N.; Vasant, P. Symbiotic Organism Search Algorithm for Optimal Size and Siting of Distributed Generators in Distribution Systems. Int. J. Energy Optim. Eng. 2017, 6, 1–28Deshmukh, R.; Kalage, A. Optimal Placement and Sizing of Distributed Generator in Distribution System Using Artificial Bee Colony Algorithm. In Proceedings of the 2018 IEEE Global Conference on Wireless Computing and Networking (GCWCN), Lonavala, India, 23–24 November 2018.Nowdeh, S.A.; Davoudkhani, I.F.; Moghaddam, M.H.; Najmi, E.S.; Abdelaziz, A.; Ahmadi, A.; Razavi, S.; Gandoman, F. Fuzzy multi-objective placement of renewable energy sources in distribution system with objective of loss reduction and reliability improvement using a novel hybrid method. Appl. Soft Comput. 2019, 77, 761–779Gholami, K.; Parvaneh, M.H. A mutated salp swarm algorithm for optimum allocation of active and reactive power sources in radial distribution systems. Appl. Soft Comput. 2019, 85, 105833.Bocanegra, S.Y.; Montoya, O.D. Heuristic approach for optimal location and sizing of distributed generators in AC distribution networks. WSEAS Trans. Power Syst. 2019, 14, 113–121HassanzadehFard, H.; Jalilian, A. A novel objective function for optimal DG allocation in distribution systems using meta-heuristic algorithms. Int. J. Green Energy 2016, 13, 1615–1625. [Do ˘gan, B.; Ölmez, T. A new metaheuristic for numerical function optimization: Vortex Search algorithm. Inf. Sci. 2015, 293, 125–145. [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, 4914Do ˘gan, B.; Ölmez, T. Vortex search algorithm for the analog active filter component selection problem. AEU Int. J. Electron. Commun. 2015, 69, 1243–1253Saka, M.; Tezcan, S.S.; Eke, I.; Taplamacioglu, M.C. Economic load dispatch using vortex search algorithm. In Proceedings of the 2017 4th International Conference on Electrical and Electronic Engineering (ICEEE), Ankara, Turkey, 8–10 April 2017Soroudi, A. Power System Optimization Modeling in GAMS; Springer International Publishing: New York, NY, USA, 2017http://purl.org/coar/resource_type/c_6501ORIGINAL[Art. 23] Optimal Integration of Photovoltaic_Oscar Danilo Montoya.pdf[Art. 23] Optimal Integration of Photovoltaic_Oscar Danilo Montoya.pdfapplication/pdf331110https://repositorio.utb.edu.co/bitstream/20.500.12585/10370/1/%5bArt.%2023%5d%20Optimal%20Integration%20of%20Photovoltaic_Oscar%20Danilo%20Montoya.pdf81eb53837454c44236e3110ad720c99cMD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://repositorio.utb.edu.co/bitstream/20.500.12585/10370/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-83182https://repositorio.utb.edu.co/bitstream/20.500.12585/10370/3/license.txte20ad307a1c5f3f25af9304a7a7c86b6MD53TEXT[Art. 23] Optimal Integration of Photovoltaic_Oscar Danilo Montoya.pdf.txt[Art. 23] Optimal Integration of Photovoltaic_Oscar Danilo 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