Optimal Location of DGs in DC Power Grids Using a MINLP Model Implemented in GAMS
This paper addresses the problem of optimal location and sizing of distributed generators (DGs) in direct-current (dc) power grids by using a mixed-integer nonlinear programming (MINLP) formulation. The reduction of the power losses in all branches of the network are considered as the objective func...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2018
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/8860
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/8860
- Palabra clave:
- Direct-current power grids
Distributed generators location and sizing
General algebraic modeling system
Mixed-integer nonlinear programming
Power losses minimization
Algebra
Distributed computer systems
Distributed power generation
Integer programming
Location
Nonlinear programming
Voltage regulators
Algebraic modeling
Direct current power
Location and sizings
Mixed-integer nonlinear programming
Power-losses
Electric power transmission networks
- Rights
- restrictedAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Optimal Location of DGs in DC Power Grids Using a MINLP Model Implemented in GAMS |
| title |
Optimal Location of DGs in DC Power Grids Using a MINLP Model Implemented in GAMS |
| spellingShingle |
Optimal Location of DGs in DC Power Grids Using a MINLP Model Implemented in GAMS Direct-current power grids Distributed generators location and sizing General algebraic modeling system Mixed-integer nonlinear programming Power losses minimization Algebra Distributed computer systems Distributed power generation Integer programming Location Nonlinear programming Voltage regulators Algebraic modeling Direct current power Location and sizings Mixed-integer nonlinear programming Power-losses Electric power transmission networks |
| title_short |
Optimal Location of DGs in DC Power Grids Using a MINLP Model Implemented in GAMS |
| title_full |
Optimal Location of DGs in DC Power Grids Using a MINLP Model Implemented in GAMS |
| title_fullStr |
Optimal Location of DGs in DC Power Grids Using a MINLP Model Implemented in GAMS |
| title_full_unstemmed |
Optimal Location of DGs in DC Power Grids Using a MINLP Model Implemented in GAMS |
| title_sort |
Optimal Location of DGs in DC Power Grids Using a MINLP Model Implemented in GAMS |
| dc.subject.keywords.none.fl_str_mv |
Direct-current power grids Distributed generators location and sizing General algebraic modeling system Mixed-integer nonlinear programming Power losses minimization Algebra Distributed computer systems Distributed power generation Integer programming Location Nonlinear programming Voltage regulators Algebraic modeling Direct current power Location and sizings Mixed-integer nonlinear programming Power-losses Electric power transmission networks |
| topic |
Direct-current power grids Distributed generators location and sizing General algebraic modeling system Mixed-integer nonlinear programming Power losses minimization Algebra Distributed computer systems Distributed power generation Integer programming Location Nonlinear programming Voltage regulators Algebraic modeling Direct current power Location and sizings Mixed-integer nonlinear programming Power-losses Electric power transmission networks |
| description |
This paper addresses the problem of optimal location and sizing of distributed generators (DGs) in direct-current (dc) power grids by using a mixed-integer nonlinear programming (MINLP) formulation. The reduction of the power losses in all branches of the network are considered as the objective function; while the restrictions are the power balance, voltage regulation, maximum penetration and maximum distributed generation units available. The general algebraic modeling system (GAMS) is selected as nonlinear optimizing package to solve this problem; besides, a small numerical example of energy production is introduced to illustrate the usability of using GAMS. Finally, a 21-node dc grid with two ideal generators, and multiple constant power loads, is used as test system. © 2018 IEEE. |
| publishDate |
2018 |
| dc.date.issued.none.fl_str_mv |
2018 |
| dc.date.accessioned.none.fl_str_mv |
2020-03-26T16:32:31Z |
| dc.date.available.none.fl_str_mv |
2020-03-26T16:32:31Z |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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http://purl.org/coar/resource_type/c_c94f |
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info:eu-repo/semantics/conferenceObject |
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info:eu-repo/semantics/publishedVersion |
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Conferencia |
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publishedVersion |
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2018 IEEE 9th Power, Instrumentation and Measurement Meeting, EPIM 2018 |
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9781538678428 |
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https://hdl.handle.net/20.500.12585/8860 |
| dc.identifier.doi.none.fl_str_mv |
10.1109/EPIM.2018.8756492 |
| dc.identifier.instname.none.fl_str_mv |
Universidad Tecnológica de Bolívar |
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Repositorio UTB |
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56919564100 57210170020 55791991200 57191493648 36449223500 22836502400 |
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2018 IEEE 9th Power, Instrumentation and Measurement Meeting, EPIM 2018 9781538678428 10.1109/EPIM.2018.8756492 Universidad Tecnológica de Bolívar Repositorio UTB 56919564100 57210170020 55791991200 57191493648 36449223500 22836502400 |
| url |
https://hdl.handle.net/20.500.12585/8860 |
| dc.language.iso.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.conferencedate.none.fl_str_mv |
14 November 2018 through 16 November 2018 |
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http://purl.org/coar/access_right/c_16ec |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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info:eu-repo/semantics/restrictedAccess |
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Atribución-NoComercial 4.0 Internacional |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ Atribución-NoComercial 4.0 Internacional http://purl.org/coar/access_right/c_16ec |
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restrictedAccess |
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Recurso electrónico |
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application/pdf |
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Institute of Electrical and Electronics Engineers Inc. |
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Institute of Electrical and Electronics Engineers Inc. |
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9th IEEE Power, Instrumentation and Measurement Meeting, EPIM 2018 |
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2020-03-26T16:32:31Z2020-03-26T16:32:31Z20182018 IEEE 9th Power, Instrumentation and Measurement Meeting, EPIM 20189781538678428https://hdl.handle.net/20.500.12585/886010.1109/EPIM.2018.8756492Universidad Tecnológica de BolívarRepositorio UTB569195641005721017002055791991200571914936483644922350022836502400This paper addresses the problem of optimal location and sizing of distributed generators (DGs) in direct-current (dc) power grids by using a mixed-integer nonlinear programming (MINLP) formulation. The reduction of the power losses in all branches of the network are considered as the objective function; while the restrictions are the power balance, voltage regulation, maximum penetration and maximum distributed generation units available. The general algebraic modeling system (GAMS) is selected as nonlinear optimizing package to solve this problem; besides, a small numerical example of energy production is introduced to illustrate the usability of using GAMS. Finally, a 21-node dc grid with two ideal generators, and multiple constant power loads, is used as test system. © 2018 IEEE.Universidad Nacional de Colombia, UN Departamento Administrativo de Ciencia, Tecnología e Innovación, COLCIENCIAS Department of Science, Information Technology and Innovation, Queensland Government, DSITI Universidad Tecnológica de Pereira, UTP UNAL-ITM-39823/P17211FINANCIAL SUPPORT This work was supported by the Administrative Department of Science, Technology and Innovation of Colombia (COLCIENCIAS) through the National Scholarship Program, calling contest 727-2015, the PhD program in Engineering of la Universidad Tecnológica de Pereira, and the Univer-sidad Nacional de Colombia and the Instituto Tecnológico Metropolitano under the project UNAL-ITM-39823/P17211.Recurso electrónicoapplication/pdfengInstitute of Electrical and Electronics Engineers Inc.http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/restrictedAccessAtribución-NoComercial 4.0 Internacionalhttp://purl.org/coar/access_right/c_16echttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85069796375&doi=10.1109%2fEPIM.2018.8756492&partnerID=40&md5=9fa265a155cdfb8e650b5ac623b9caae9th IEEE Power, Instrumentation and Measurement Meeting, EPIM 2018Optimal Location of DGs in DC Power Grids Using a MINLP Model Implemented in GAMSinfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionConferenciahttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_c94fDirect-current power gridsDistributed generators location and sizingGeneral algebraic modeling systemMixed-integer nonlinear programmingPower losses minimizationAlgebraDistributed computer systemsDistributed power generationInteger programmingLocationNonlinear programmingVoltage regulatorsAlgebraic modelingDirect current powerLocation and sizingsMixed-integer nonlinear programmingPower-lossesElectric power transmission networks14 November 2018 through 16 November 2018Montoya O.D.Garrido Arévalo, Víctor ManuelGrisales-Noreña L.F.Gil-González W.Garces A.Ramos-Paja C.A.Montoya, O.D., Grisales-Noreña, L.F., González-Montoya, D., Ramos-Paja, C., Garces, A., Linear power flow formulation for lowvoltage DC power grids (2018) Electr. Power Syst. Res., 163, pp. 375-381Planas, E., Andreu, J., Gárate, J.I., De Alegría, I.M., Ibarra, E., AC and DC technology in microgrids: A review (2015) Renewable Sustainable Energy Rev., 43, pp. 726-749Justo, J.J., Mwasilu, F., Lee, J., Jung, J.W., AC-microgrids versus DC-microgrids with distributed energy resources: A review (2013) Renewable Sustainable Energy Rev., 24, pp. 387-405Nasirian, V., Moayedi, S., Davoudi, A., Lewis, F., Distributed cooperative control of DC microgrids (2014) IEEE Trans. Power Electron., 8993 (C), p. 1Papadimitriou, C.N., Zountouridou, E.I., Hatziargyriou, N.D., Review of hierarchical control in DC microgrids (2015) Electr. Power Syst. Res., 122, pp. 159-167Garces, A., On convergence of newtons method in power flow study for DC microgrids (2018) IEEE Trans. Power Syst., p. 1Garces, A., Uniqueness of the power flow solutions in low voltage direct current grids (2017) Electr. Power Syst. Res., 151, pp. 149-153Salomonsson, D., Söder, L., Sannino, A., Protection of low-voltage DC microgrids (2009) IEEE Trans. Power Del., 24 (3), pp. 1045-1053Li, J., Liu, F., Wang, Z., Low, S., Mei, S., Optimal power flow in stand-alone dc microgrids (2018) IEEE Trans. Power Syst., p. 1Montoya, O.D., Gil-González, W., Garces, A., Optimal power flow on DC microgrids: A quadratic convex approximation (2018) IEEE Trans. Circuits Syst. II Express Briefs, p. 1Montoya, O.D., Numerical Approximation of the Maximum Power Consumption in DC-MGs with CPLs via an SDP Model (2018) IEEE Trans. Circuits Syst. II Express Briefs, p. 1GAMS Free Demo Version, , https://www.gams.com/download/, GAMS Development Corp. [Online]Montoya, O.D., Grajales, A., Garces, A., Castro, C.A., Distribution systems operation considering energy storage devices and distributed generation (2017) IEEE Lat. Am. Trans., 15 (5), pp. 890-900. , MayMontoya, O.D., Solving a Classical Optimization Problem Using GAMS Optimizer Package: Economic Dispatch Problem Implementation (2017) Ingeniería y Ciencia, 13 (26), pp. 39-63. , NovNiazi, G., Lalwani, M., PSO based optimal distributed generation placement and sizing in power distribution networks: A comprehensive review (2017) 2017 International Conference on Computer, Communications and Electronics (Comptelix), pp. 305-311. , JulyRajalakshmi, J., Durairaj, S., Review on optimal distributed generation placement using particle swarm optimization algorithms (2016) 2016 International Conference on Emerging Trends in Engineering, Technology and Science (ICETETS), pp. 1-6. , FebGrisales-Noreña, L.F., González-Montoya, D., Ramos-Paja, C.A., Optimal sizing and location of distributed generators based on PBIL and PSO techniques (2018) Energies, 11 (4), pp. 1-27. , aprVatani, M., Alkaran, D.S., Sanjari, M.J., Gharehpetian, G.B., Multiple distributed generation units allocation in distribution network for loss reduction based on a combination of analytical and genetic algorithm methods (2016) IET Gener. Transm. Distrib., 10 (1), pp. 66-72Yuan, H., Li, F., Wei, Y., Zhu, J., Novel linearized power flow and linearized opf models for active distribution networks with application in distribution LMP (2018) IEEE Trans. Smart Grid, 9 (1), pp. 438-448. , JanKaur, S., Kumbhar, G., Sharma, J., A MINLP technique for optimal placement of multiple DG units in distribution systems (2014) Int. J. Electr. Power Energy Syst., 63, pp. 609-617López Lezama, J.M., Optimal location of distributed generation in distribution systems using a model of nonlineal whole mixed programming (2011) Tecnura, 15 (30), pp. 101-110Chen, C., Simulated annealing-based optimal wind-thermal coordination scheduling (2007) IET Gener. Transm. Distrib., 1 (3), pp. 447-455. , MayOgunjuyigbe, A., Ayodele, T., Akinola, O., Impact of distributed generators on the power loss and voltage profile of sub-transmission network (2016) J. Electr. Syst. Inf. Technol., 3 (1), pp. 94-107http://purl.org/coar/resource_type/c_c94fTHUMBNAILMiniProdInv.pngMiniProdInv.pngimage/png23941https://repositorio.utb.edu.co/bitstream/20.500.12585/8860/1/MiniProdInv.png0cb0f101a8d16897fb46fc914d3d7043MD5120.500.12585/8860oai:repositorio.utb.edu.co:20.500.12585/88602023-05-26 10:05:21.766Repositorio Institucional UTBrepositorioutb@utb.edu.co |