Integration of PV Distributed Generators into Electrical Networks for Investment and Energy Purchase Costs Reduction by Using a Discrete–Continuous Parallel PSO

The problem of optimally integrating PV DGs into electrical networks to reduce annual costs (which include energy purchase and investment costs) was addressed in this research by presenting a new solution methodology. For such purpose, we used a Discrete–Continuous Parallel Particle Swarm Optimizati...

Full description

Autores:
Grisales-Noreña, Luis Fernando
Montoya, Oscar Danilo
Marín-García, Edward-J.
Ramos-Paja, v
Perea-Moreno, Alberto-Jesus
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:20.500.12585/12202
Acceso en línea:
https://hdl.handle.net/20.500.12585/12202
Palabra clave:
Placement;
Active Distribution Network;
Voltage Stability
LEMB
Rights
openAccess
License
http://purl.org/coar/access_right/c_abf2
id UTB2_de681d8a4a0860aa20609716e6249c87
oai_identifier_str oai:repositorio.utb.edu.co:20.500.12585/12202
network_acronym_str UTB2
network_name_str Repositorio Institucional UTB
repository_id_str
dc.title.spa.fl_str_mv Integration of PV Distributed Generators into Electrical Networks for Investment and Energy Purchase Costs Reduction by Using a Discrete–Continuous Parallel PSO
title Integration of PV Distributed Generators into Electrical Networks for Investment and Energy Purchase Costs Reduction by Using a Discrete–Continuous Parallel PSO
spellingShingle Integration of PV Distributed Generators into Electrical Networks for Investment and Energy Purchase Costs Reduction by Using a Discrete–Continuous Parallel PSO
Placement;
Active Distribution Network;
Voltage Stability
LEMB
title_short Integration of PV Distributed Generators into Electrical Networks for Investment and Energy Purchase Costs Reduction by Using a Discrete–Continuous Parallel PSO
title_full Integration of PV Distributed Generators into Electrical Networks for Investment and Energy Purchase Costs Reduction by Using a Discrete–Continuous Parallel PSO
title_fullStr Integration of PV Distributed Generators into Electrical Networks for Investment and Energy Purchase Costs Reduction by Using a Discrete–Continuous Parallel PSO
title_full_unstemmed Integration of PV Distributed Generators into Electrical Networks for Investment and Energy Purchase Costs Reduction by Using a Discrete–Continuous Parallel PSO
title_sort Integration of PV Distributed Generators into Electrical Networks for Investment and Energy Purchase Costs Reduction by Using a Discrete–Continuous Parallel PSO
dc.creator.fl_str_mv Grisales-Noreña, Luis Fernando
Montoya, Oscar Danilo
Marín-García, Edward-J.
Ramos-Paja, v
Perea-Moreno, Alberto-Jesus
dc.contributor.author.none.fl_str_mv Grisales-Noreña, Luis Fernando
Montoya, Oscar Danilo
Marín-García, Edward-J.
Ramos-Paja, v
Perea-Moreno, Alberto-Jesus
dc.subject.keywords.spa.fl_str_mv Placement;
Active Distribution Network;
Voltage Stability
topic Placement;
Active Distribution Network;
Voltage Stability
LEMB
dc.subject.armarc.none.fl_str_mv LEMB
description The problem of optimally integrating PV DGs into electrical networks to reduce annual costs (which include energy purchase and investment costs) was addressed in this research by presenting a new solution methodology. For such purpose, we used a Discrete–Continuous Parallel Particle Swarm Optimization method (DCPPSO), which considers both the discrete and continuous variables associated with the location and sizing of DGs in an electrical network and employs a parallel processing tool to reduce processing times. The optimization parameters of the proposed solution methodology were tuned using an external optimization algorithm. To validate the performance of DCPPSO, we employed the 33- and 69-bus test systems and compared it with five other solution methods: the BONMIN solver of the General Algebraic Modeling System (GAMS) and other four discrete–continuous methodologies that have been recently proposed. According to the findings, the DCPPSO produced the best results in terms of quality of the solution, processing time, and repeatability in electrical networks of any size, since it showed a better performance as the size of the electrical system increased. © 2022 by the authors.
publishDate 2022
dc.date.issued.none.fl_str_mv 2022
dc.date.accessioned.none.fl_str_mv 2023-07-19T21:20:06Z
dc.date.available.none.fl_str_mv 2023-07-19T21:20:06Z
dc.date.submitted.none.fl_str_mv 2023
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 Grisales-Noreña, L. F., Montoya, O. D., Marín-García, E. J., Ramos-Paja, C. A., & Perea-Moreno, A. J. (2022). Integration of PV Distributed Generators into Electrical Networks for Investment and Energy Purchase Costs Reduction by Using a Discrete–Continuous Parallel PSO. Energies, 15(20), 7465.
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12585/12202
dc.identifier.doi.none.fl_str_mv 10.3390/en15207465
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 Grisales-Noreña, L. F., Montoya, O. D., Marín-García, E. J., Ramos-Paja, C. A., & Perea-Moreno, A. J. (2022). Integration of PV Distributed Generators into Electrical Networks for Investment and Energy Purchase Costs Reduction by Using a Discrete–Continuous Parallel PSO. Energies, 15(20), 7465.
10.3390/en15207465
Universidad Tecnológica de Bolívar
Repositorio Universidad Tecnológica de Bolívar
url https://hdl.handle.net/20.500.12585/12202
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.accessrights.spa.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
rights_invalid_str_mv http://purl.org/coar/access_right/c_abf2
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 Energies
institution Universidad Tecnológica de Bolívar
bitstream.url.fl_str_mv https://repositorio.utb.edu.co/bitstream/20.500.12585/12202/1/energies-15-07465%20%281%29.pdf
https://repositorio.utb.edu.co/bitstream/20.500.12585/12202/2/license.txt
https://repositorio.utb.edu.co/bitstream/20.500.12585/12202/3/energies-15-07465%20%281%29.pdf.txt
https://repositorio.utb.edu.co/bitstream/20.500.12585/12202/4/energies-15-07465%20%281%29.pdf.jpg
bitstream.checksum.fl_str_mv 5c1a46aa670248c2cd0d2f3b3bae10b4
e20ad307a1c5f3f25af9304a7a7c86b6
b3e6feb38a6346aa5320bd50d7f27b53
d2eae53df19db6c17bd3c1499181d866
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
MD5
repository.name.fl_str_mv Repositorio Institucional UTB
repository.mail.fl_str_mv repositorioutb@utb.edu.co
_version_ 1814021768332967936
spelling Grisales-Noreña, Luis Fernando7c27cda4-5fe4-4686-8f72-b0442c58a5d1Montoya, Oscar Danilo9fa8a75a-58fa-436d-a6e2-d80f718a4ea8Marín-García, Edward-J.fb4b794e-e765-42ae-892b-c85229c0d368Ramos-Paja, v92d9f940-248c-43d8-b811-96d8e4c25d0cPerea-Moreno, Alberto-Jesuse78da438-8ed5-40ab-a12c-74e84e6d691b2023-07-19T21:20:06Z2023-07-19T21:20:06Z20222023Grisales-Noreña, L. F., Montoya, O. D., Marín-García, E. J., Ramos-Paja, C. A., & Perea-Moreno, A. J. (2022). Integration of PV Distributed Generators into Electrical Networks for Investment and Energy Purchase Costs Reduction by Using a Discrete–Continuous Parallel PSO. Energies, 15(20), 7465.https://hdl.handle.net/20.500.12585/1220210.3390/en15207465Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThe problem of optimally integrating PV DGs into electrical networks to reduce annual costs (which include energy purchase and investment costs) was addressed in this research by presenting a new solution methodology. For such purpose, we used a Discrete–Continuous Parallel Particle Swarm Optimization method (DCPPSO), which considers both the discrete and continuous variables associated with the location and sizing of DGs in an electrical network and employs a parallel processing tool to reduce processing times. The optimization parameters of the proposed solution methodology were tuned using an external optimization algorithm. To validate the performance of DCPPSO, we employed the 33- and 69-bus test systems and compared it with five other solution methods: the BONMIN solver of the General Algebraic Modeling System (GAMS) and other four discrete–continuous methodologies that have been recently proposed. According to the findings, the DCPPSO produced the best results in terms of quality of the solution, processing time, and repeatability in electrical networks of any size, since it showed a better performance as the size of the electrical system increased. © 2022 by the authors.20 páginasapplication/pdfengEnergiesIntegration of PV Distributed Generators into Electrical Networks for Investment and Energy Purchase Costs Reduction by Using a Discrete–Continuous Parallel PSOinfo: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_2df8fbb1Placement;Active Distribution Network;Voltage StabilityLEMBinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Cartagena de IndiasLópez González, D.M., Garcia Rendon, J. Opportunities and challenges of mainstreaming distributed energy resources towards the transition to more efficient and resilient energy markets (2022) Renewable and Sustainable Energy Reviews, 157, art. no. 112018. Cited 18 times. https://www.journals.elsevier.com/renewable-and-sustainable-energy-reviews doi: 10.1016/j.rser.2021.112018Al-Shahri, O.A., Ismail, F.B., Hannan, M.A., Lipu, M.S.H., Al-Shetwi, A.Q., Begum, R.A., Al-Muhsen, N.F.O., (...), Soujeri, E. Solar photovoltaic energy optimization methods, challenges and issues: A comprehensive review (2021) Journal of Cleaner Production, 284, art. no. 125465. Cited 133 times. https://www.journals.elsevier.com/journal-of-cleaner-production doi: 10.1016/j.jclepro.2020.125465Cortés-Caicedo, B., Molina-Martin, F., Grisales-Noreña, L.F., Montoya, O.D., Hernández, J.C. Optimal Design of PV Systems in Electrical Distribution Networks by Minimizing the Annual Equivalent Operative Costs through the Discrete-Continuous Vortex Search Algorithm (2022) Sensors, 22 (3), art. no. 851. Cited 18 times. https://www.mdpi.com/1424-8220/22/3/851/pdf doi: 10.3390/s22030851Kandemir, E., Cetin, N.S., Borekci, S. A comprehensive overview of maximum power extraction methods for PV systems (2017) Renewable and Sustainable Energy Reviews, 78, pp. 93-112. Cited 106 times. https://www.journals.elsevier.com/renewable-and-sustainable-energy-reviews doi: 10.1016/j.rser.2017.04.090Montoya, O.D., Grisales-Noreña, L.F., Ramos-Paja, C.A. Optimal Allocation and Sizing of PV Generation Units in Distribution Networks via the Generalized Normal Distribution Optimization Approach (Open Access) (2022) Computers, 11 (4), art. no. 53. Cited 6 times. https://www.mdpi.com/2073-431X/11/4/53/pdf doi: 10.3390/computers11040053Grisales-Noreña, L.F., Montoya, D.G., Ramos-Paja, C.A. Optimal sizing and location of distributed generators based on PBIL and PSO techniques (2018) Energies, 11 (4), art. no. en11041018. Cited 98 times. http://www.mdpi.com/journal/energies/ doi: 10.3390/en11041018Gong, X., Dong, F., Mohamed, M.A., Awwad, E.M., Abdullah, H.M., Ali, Z.M. Towards distributed based energy transaction in a clean smart island (2020) Journal of Cleaner Production, 273, art. no. 122768. Cited 54 times. https://www.journals.elsevier.com/journal-of-cleaner-production doi: 10.1016/j.jclepro.2020.122768Chen, J., Alnowibet, K., Annuk, A., Mohamed, M.A. An effective distributed approach based machine learning for energy negotiation in networked microgrids (Open Access) (2021) Energy Strategy Reviews, 38, art. no. 100760. Cited 22 times. http://www.journals.elsevier.com/energy-strategy-reviews/ doi: 10.1016/j.esr.2021.100760Junedi, M.M., Ludin, N.A., Hamid, N.H., Kathleen, P.R., Hasila, J., Ahmad Affandi, N.A. Environmental and economic performance assessment of integrated conventional solar photovoltaic and agrophotovoltaic systems (2022) Renewable and Sustainable Energy Reviews, 168, art. no. 112799. Cited 5 times. https://www.journals.elsevier.com/renewable-and-sustainable-energy-reviews doi: 10.1016/j.rser.2022.112799Moradi, M.H., Abedini, M. A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems (2012) International Journal of Electrical Power and Energy Systems, 34 (1), pp. 66-74. Cited 865 times. doi: 10.1016/j.ijepes.2011.08.023Montoya, O.D., Gil-González, W., Grisales-Noreña, L.F. An exact MINLP model for optimal location and sizing of DGs in distribution networks: A general algebraic modeling system approach (Open Access) (2020) Ain Shams Engineering Journal, 11 (2), pp. 409-418. Cited 51 times. http://www.elsevier.com/wps/find/journaldescription.cws_home/724208/description#description doi: 10.1016/j.asej.2019.08.011Kollu, R., Rayapudi, S.R., Sadhu, V.L.N. A novel method for optimal placement of distributed generation in distribution systems using HSDO (Open Access) (2014) International Transactions on Electrical Energy Systems, 24 (4), pp. 547-561. Cited 57 times. http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2050-7038;jsessionid=37A99007CF662738769613522C4B81FF.d04t01 doi: 10.1002/etep.1710Injeti, S.K., Prema Kumar, N. A novel approach to identify optimal access point and capacity of multiple DGs in a small, medium and large scale radial distribution systems (2013) International Journal of Electrical Power and Energy Systems, 45 (1), pp. 142-151. Cited 262 times. doi: 10.1016/j.ijepes.2012.08.043Ramadan, A., Ebeed, M., Kamel, S., Agwa, A.M., Tostado‐véliz, M. The Probabilistic Optimal Integration of Renewable Distributed Generators Considering the Time‐Varying Load Based on an Artificial Gorilla Troops Optimizer (Open Access) (2022) Energies, 15 (4), art. no. 1302. Cited 12 times. https://www.mdpi.com/1996-1073/15/4/1302/pdf doi: 10.3390/en15041302Nagadurga, T., Narasimham, P.V.R.L., Vakula, V.S., Devarapalli, R. Gray wolf optimization-based optimal grid connected solar photovoltaic system with enhanced power quality features (2022) Concurrency and Computation: Practice and Experience, 34 (5), art. no. e6696. Cited 5 times. http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1532-0634 doi: 10.1002/cpe.6696Montoya, O.D., Grisales-Noreña, L.F., Perea-Moreno, A.-J. Optimal investments in PV sources for grid-connected distribution networks: An application of the discrete–continuous genetic algorithm (2021) Sustainability (Switzerland), 13 (24), art. no. 13633. Cited 16 times. https://www.mdpi.com/2071-1050/13/24/13633/pdf doi: 10.3390/su132413633Montoya, O.D., Giral-Ramírez, D.A., Hernández, J.C. Efficient Integration of PV Sources in Distribution Networks to Reduce Annual Investment and Operating Costs Using the Modified Arithmetic Optimization Algorithm (Open Access) (2022) Electronics (Switzerland), 11 (11), art. no. 1680. Cited 4 times. https://www.mdpi.com/2079-9292/11/11/1680/pdf?version=1653469820 doi: 10.3390/electronics11111680Montoya, O.D., Grisales-Noreña, L.F., Alvarado-Barrios, L., Arias-Londoño, A., Álvarez-Arroyo, C. Efficient reduction in the annual investment costs in ac distribution networks via optimal integration of solar pv sources using the newton metaheuristic algorithm (Open Access) (2021) Applied Sciences (Switzerland), 11 (23), art. no. 11525. Cited 12 times. https://www.mdpi.com/2076-3417/11/23/11525/pdf doi: 10.3390/app112311525Abualigah, L., Diabat, A., Mirjalili, S., Abd Elaziz, M., Gandomi, A.H. The Arithmetic Optimization Algorithm (Open Access) (2021) Computer Methods in Applied Mechanics and Engineering, 376, art. no. 113609. Cited 1114 times. http://www.journals.elsevier.com/computer-methods-in-applied-mechanics-and-engineering/http://www.journals.elsevier.com/computer-methods-in-applied-mechanics-and-engineering/ doi: 10.1016/j.cma.2020.113609Grisales-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 (Open Access) (2020) Journal of Energy Storage, 29, art. no. 101488. Cited 58 times. http://www.journals.elsevier.com/journal-of-energy-storage/ doi: 10.1016/j.est.2020.101488Muñoz, A.A.R., Grisales-Noreña, L.F., Montano, J., Montoya, O.D., Perea-Moreno, A.-J. Application of the Multiverse Optimization Method to Solve the Optimal Power Flow Problem in Alternating Current Networks (Open Access) (2022) Electronics (Switzerland), 11 (8), art. no. 1287. Cited 3 times. https://www.mdpi.com/2079-9292/11/8/1287/pdf doi: 10.3390/electronics11081287Kim, J.-Y., Mun, K.-J., Kim, H.-S., Park, J.H. Optimal power system operation using parallel processing system and PSO algorithm (Open Access) (2011) International Journal of Electrical Power and Energy Systems, 33 (8), pp. 1457-1461. Cited 37 times. doi: 10.1016/j.ijepes.2011.06.026Pereira da Silva, P., Dantas, G., Pereira, G.I., Câmara, L., De Castro, N.J. Photovoltaic distributed generation – An international review on diffusion, support policies, and electricity sector regulatory adaptation (2019) Renewable and Sustainable Energy Reviews, 103, pp. 30-39. Cited 38 times. https://www.journals.elsevier.com/renewable-and-sustainable-energy-reviews doi: 10.1016/j.rser.2018.12.028Zhang, F., Deng, H., Margolis, R., Su, J. Analysis of distributed-generation photovoltaic deployment, installation time and cost, market barriers, and policies in China (Open Access) (2015) Energy Policy, 81, pp. 43-55. Cited 92 times. http://www.journals.elsevier.com/energy-policy/ doi: 10.1016/j.enpol.2015.02.010Montoya, O.D., Garrido, V.M., Gil-Gonzalez, W., Grisales-Norena, L.F. Power Flow Analysis in DC Grids: Two Alternative Numerical Methods (Open Access) (2019) IEEE Transactions on Circuits and Systems II: Express Briefs, 66 (11), art. no. 8606244, pp. 1865-1869. Cited 60 times. http://www.ieee-cas.org doi: 10.1109/TCSII.2019.2891640Grisales-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 (Open Access) (2021) Mathematics, 9 (16), art. no. 1913. Cited 9 times. https://www.mdpi.com/2227-7390/9/16/1913/pdf doi: 10.3390/math9161913Muñoz, 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/electronics10222837http://purl.org/coar/resource_type/c_6501ORIGINALenergies-15-07465 (1).pdfenergies-15-07465 (1).pdfapplication/pdf501012https://repositorio.utb.edu.co/bitstream/20.500.12585/12202/1/energies-15-07465%20%281%29.pdf5c1a46aa670248c2cd0d2f3b3bae10b4MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-83182https://repositorio.utb.edu.co/bitstream/20.500.12585/12202/2/license.txte20ad307a1c5f3f25af9304a7a7c86b6MD52TEXTenergies-15-07465 (1).pdf.txtenergies-15-07465 (1).pdf.txtExtracted texttext/plain70774https://repositorio.utb.edu.co/bitstream/20.500.12585/12202/3/energies-15-07465%20%281%29.pdf.txtb3e6feb38a6346aa5320bd50d7f27b53MD53THUMBNAILenergies-15-07465 (1).pdf.jpgenergies-15-07465 (1).pdf.jpgGenerated Thumbnailimage/jpeg8145https://repositorio.utb.edu.co/bitstream/20.500.12585/12202/4/energies-15-07465%20%281%29.pdf.jpgd2eae53df19db6c17bd3c1499181d866MD5420.500.12585/12202oai:repositorio.utb.edu.co:20.500.12585/122022023-07-20 00:18:12.008Repositorio Institucional UTBrepositorioutb@utb.edu.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