Optimal Location and Sizing of PV Generation Units in Electrical Networks to Reduce the Total Annual Operating Costs: An Application of the Crow Search Algorithm
This study presents a master–slave methodology to solve the problem of optimally locating and sizing photovoltaic (PV) generation units in electrical networks. This problem is represented by means of a Mixed-Integer Nonlinear Programming (MINLP) model, whose objective function is to reduce the total...
- Autores:
-
Cortés-Caicedo, Brandon
Grisales-Noreña, Luis Fernando
Danilo Montoya, Oscar
Perea-Moreno, Miguel-Angel
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:20.500.12585/12411
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/12411
- Palabra clave:
- Placement;
Active Distribution Network;
Voltage Stability
LEMB
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Optimal Location and Sizing of PV Generation Units in Electrical Networks to Reduce the Total Annual Operating Costs: An Application of the Crow Search Algorithm |
| title |
Optimal Location and Sizing of PV Generation Units in Electrical Networks to Reduce the Total Annual Operating Costs: An Application of the Crow Search Algorithm |
| spellingShingle |
Optimal Location and Sizing of PV Generation Units in Electrical Networks to Reduce the Total Annual Operating Costs: An Application of the Crow Search Algorithm Placement; Active Distribution Network; Voltage Stability LEMB |
| title_short |
Optimal Location and Sizing of PV Generation Units in Electrical Networks to Reduce the Total Annual Operating Costs: An Application of the Crow Search Algorithm |
| title_full |
Optimal Location and Sizing of PV Generation Units in Electrical Networks to Reduce the Total Annual Operating Costs: An Application of the Crow Search Algorithm |
| title_fullStr |
Optimal Location and Sizing of PV Generation Units in Electrical Networks to Reduce the Total Annual Operating Costs: An Application of the Crow Search Algorithm |
| title_full_unstemmed |
Optimal Location and Sizing of PV Generation Units in Electrical Networks to Reduce the Total Annual Operating Costs: An Application of the Crow Search Algorithm |
| title_sort |
Optimal Location and Sizing of PV Generation Units in Electrical Networks to Reduce the Total Annual Operating Costs: An Application of the Crow Search Algorithm |
| dc.creator.fl_str_mv |
Cortés-Caicedo, Brandon Grisales-Noreña, Luis Fernando Danilo Montoya, Oscar Perea-Moreno, Miguel-Angel Perea-Moreno, Alberto-Jesus |
| dc.contributor.author.none.fl_str_mv |
Cortés-Caicedo, Brandon Grisales-Noreña, Luis Fernando Danilo Montoya, Oscar Perea-Moreno, Miguel-Angel 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 |
This study presents a master–slave methodology to solve the problem of optimally locating and sizing photovoltaic (PV) generation units in electrical networks. This problem is represented by means of a Mixed-Integer Nonlinear Programming (MINLP) model, whose objective function is to reduce the total annual operating costs of a network for a 20-year planning period. Such costs include (i) the costs of purchasing energy at the conventional generators (the main supply node in this particular case), (ii) the investment in the PV generation units, and (iii) their corresponding operation and maintenance costs. In the proposed master–slave method, the master stage uses the Discrete–Continuous version of the Crow Search Algorithm (DCCSA) to define the set of nodes where the PV generation units will be installed (location), as well as their nominal power (sizing), and the slave stage employs the successive approximation power flow technique to find the value of the objective function of each individual provided by the master stage. The numerical results obtained in the 33- and 69-node test systems demonstrated its applicability, efficiency, and robustness when compared to other methods reported in the specialized literature, such as the vortex search algorithm, the generalized normal distribution optimizer, and the particle swarm optimization algorithm. All simulations were performed in MATLAB using our own scripts. © 2022 by the authors. |
| publishDate |
2022 |
| dc.date.issued.none.fl_str_mv |
2022 |
| dc.date.accessioned.none.fl_str_mv |
2023-07-24T18:54:03Z |
| dc.date.available.none.fl_str_mv |
2023-07-24T18:54:03Z |
| dc.date.submitted.none.fl_str_mv |
2023 |
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http://purl.org/coar/version/c_b1a7d7d4d402bcce |
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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/draft |
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http://purl.org/coar/resource_type/c_6501 |
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draft |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/12411 |
| dc.identifier.doi.none.fl_str_mv |
Alberto-Jesus |
| dc.identifier.instname.spa.fl_str_mv |
Universidad Tecnológica de Bolívar |
| dc.identifier.reponame.spa.fl_str_mv |
Repositorio Universidad Tecnológica de Bolívar |
| url |
https://hdl.handle.net/20.500.12585/12411 |
| identifier_str_mv |
Alberto-Jesus Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
| 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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22 páginas |
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application/pdf |
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Cartagena de Indias |
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Cortés-Caicedo, Brandon0b676225-338d-48dc-8f2a-694085d9bb42Grisales-Noreña, Luis Fernando7c27cda4-5fe4-4686-8f72-b0442c58a5d1Danilo Montoya, Oscar96c898c1-3272-4ab3-864c-43e5bff72ec4Perea-Moreno, Miguel-Angeld9531a58-ba07-42c6-9379-79326fc50422Perea-Moreno, Alberto-Jesuse78da438-8ed5-40ab-a12c-74e84e6d691b2023-07-24T18:54:03Z2023-07-24T18:54:03Z20222023https://hdl.handle.net/20.500.12585/12411Alberto-JesusUniversidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThis study presents a master–slave methodology to solve the problem of optimally locating and sizing photovoltaic (PV) generation units in electrical networks. This problem is represented by means of a Mixed-Integer Nonlinear Programming (MINLP) model, whose objective function is to reduce the total annual operating costs of a network for a 20-year planning period. Such costs include (i) the costs of purchasing energy at the conventional generators (the main supply node in this particular case), (ii) the investment in the PV generation units, and (iii) their corresponding operation and maintenance costs. In the proposed master–slave method, the master stage uses the Discrete–Continuous version of the Crow Search Algorithm (DCCSA) to define the set of nodes where the PV generation units will be installed (location), as well as their nominal power (sizing), and the slave stage employs the successive approximation power flow technique to find the value of the objective function of each individual provided by the master stage. The numerical results obtained in the 33- and 69-node test systems demonstrated its applicability, efficiency, and robustness when compared to other methods reported in the specialized literature, such as the vortex search algorithm, the generalized normal distribution optimizer, and the particle swarm optimization algorithm. All simulations were performed in MATLAB using our own scripts. © 2022 by the authors.22 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_abf2MathematicsOptimal Location and Sizing of PV Generation Units in Electrical Networks to Reduce the Total Annual Operating Costs: An Application of the Crow Search Algorithminfo: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 StabilityLEMBCartagena de IndiasSaeed, M.H., Fangzong, W., Kalwar, B.A., Iqbal, S. A Review on Microgrids' Challenges Perspectives (2021) IEEE Access, 9, pp. 166502-166517. Cited 84 times. http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639 doi: 10.1109/ACCESS.2021.3135083Pimm, A.J., Palczewski, J., Barbour, E.R., Cockerill, T.T. Using electricity storage to reduce greenhouse gas emissions (2021) Applied Energy, Part A 282, art. no. 116199. Cited 22 times. https://www.journals.elsevier.com/applied-energy doi: 10.1016/j.apenergy.2020.116199López 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.2021.112018Valencia, A., Hincapie, R.A., Gallego, R.A. Optimal location, selection, and operation of battery energy storage systems and renewable distributed generation in medium–low voltage distribution networks (2021) Journal of Energy Storage, 34, art. no. 102158. Cited 61 times. http://www.journals.elsevier.com/journal-of-energy-storage/ doi: 10.1016/j.est.2020.102158López, A.R., Krumm, A., Schattenhofer, L., Burandt, T., Montoya, F.C., Oberländer, N., Oei, P.-Y. Solar PV generation in Colombia - A qualitative and quantitative approach to analyze the potential of solar energy market (2020) Renewable Energy, 148, pp. 1266-1279. Cited 46 times. http://www.journals.elsevier.com/renewable-and-sustainable-energy-reviews/ doi: 10.1016/j.renene.2019.10.066Eltawil, M.A., Zhao, Z. Grid-connected photovoltaic power systems: Technical and potential problems-A review (2010) Renewable and Sustainable Energy Reviews, 14 (1), pp. 112-129. Cited 801 times. doi: 10.1016/j.rser.2009.07.015Almadhor, A., Rauf, H.T., Khan, M.A., Kadry, S., Nam, Y. A hybrid algorithm (BAPSO) for capacity configuration optimization in a distributed solar PV based microgrid (Open Access) (2021) Energy Reports, 7, pp. 7906-7912. Cited 23 times. http://www.journals.elsevier.com/energy-reports/ doi: 10.1016/j.egyr.2021.01.034Ngamprasert, P., Rugthaicharoencheep, N., Woothipatanapan, S. Application Improvement of Voltage Profile by Photovoltaic Farm on Distribution System (2019) Proceedings of the 2019 International Conference on Power, Energy and Innovations, ICPEI 2019, art. no. 8944997, pp. 98-101. Cited 4 times. http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8938598 ISBN: 978-172815266-0 doi: 10.1109/ICPEI47862.2019.8944997Al Abri, R.S., El-Saadany, E.F., Atwa, Y.M. Optimal placement and sizing method to improve the voltage stability margin in a distribution system using distributed generation (2013) IEEE Transactions on Power Systems, 28 (1), art. no. 6218226, pp. 326-334. Cited 420 times. doi: 10.1109/TPWRS.2012.2200049Cortés-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/s22030851Montoya, 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 (Open Access) (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., 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 (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/app112311525Montoya, 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 (2022) Computers, 11 (4), art. no. 53. Cited 6 times. https://www.mdpi.com/2073-431X/11/4/53/pdf doi: 10.3390/computers11040053Duong, M.Q., Pham, T.D., Nguyen, T.T., Doan, A.T., Van Tran, H. Determination of optimal location and sizing of solar photovoltaic distribution generation units in radial distribution systems (2019) Energies, 12 (1), art. no. en12010174. Cited 100 times. https://www.mdpi.com/1996-1073/12/1 doi: 10.3390/en12010174Devikanniga, D., Vetrivel, K., Badrinath, N. 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