Relaxed convex model for optimal location and sizing of DGs in DC grids using sequential quadratic programming and random hyperplane approaches
This report addresses the problem of optimal location and sizing of constant power sources (distributed generators (DGs)) in direct current (DC) networks for improving network performance in terms of voltage profiles and energy efficiency. An exact mixed-integer nonlinear programming (MINLP) method...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2020
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/9141
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/9141
- Palabra clave:
- Convex optimization
Direct current networks
Distributed generation
Random hyperplane method
Relaxed mathematical model
Taylor series expansion
Convex optimization
Distributed power generation
Energy efficiency
Geometry
Integer programming
MATLAB
Quadratic programming
Relaxation processes
Taylor series
Voltage regulators
Direct current
Distributed generator (DGs)
Meta-heuristic optimizations
Mixed-integer nonlinear programming
Random hyperplane method
Sequential quadratic programming
Taylor series expansions
Taylor series methods
Heuristic methods
- Rights
- restrictedAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Relaxed convex model for optimal location and sizing of DGs in DC grids using sequential quadratic programming and random hyperplane approaches |
| title |
Relaxed convex model for optimal location and sizing of DGs in DC grids using sequential quadratic programming and random hyperplane approaches |
| spellingShingle |
Relaxed convex model for optimal location and sizing of DGs in DC grids using sequential quadratic programming and random hyperplane approaches Convex optimization Direct current networks Distributed generation Random hyperplane method Relaxed mathematical model Taylor series expansion Convex optimization Distributed power generation Energy efficiency Geometry Integer programming MATLAB Quadratic programming Relaxation processes Taylor series Voltage regulators Direct current Distributed generator (DGs) Meta-heuristic optimizations Mixed-integer nonlinear programming Random hyperplane method Sequential quadratic programming Taylor series expansions Taylor series methods Heuristic methods |
| title_short |
Relaxed convex model for optimal location and sizing of DGs in DC grids using sequential quadratic programming and random hyperplane approaches |
| title_full |
Relaxed convex model for optimal location and sizing of DGs in DC grids using sequential quadratic programming and random hyperplane approaches |
| title_fullStr |
Relaxed convex model for optimal location and sizing of DGs in DC grids using sequential quadratic programming and random hyperplane approaches |
| title_full_unstemmed |
Relaxed convex model for optimal location and sizing of DGs in DC grids using sequential quadratic programming and random hyperplane approaches |
| title_sort |
Relaxed convex model for optimal location and sizing of DGs in DC grids using sequential quadratic programming and random hyperplane approaches |
| dc.subject.keywords.none.fl_str_mv |
Convex optimization Direct current networks Distributed generation Random hyperplane method Relaxed mathematical model Taylor series expansion Convex optimization Distributed power generation Energy efficiency Geometry Integer programming MATLAB Quadratic programming Relaxation processes Taylor series Voltage regulators Direct current Distributed generator (DGs) Meta-heuristic optimizations Mixed-integer nonlinear programming Random hyperplane method Sequential quadratic programming Taylor series expansions Taylor series methods Heuristic methods |
| topic |
Convex optimization Direct current networks Distributed generation Random hyperplane method Relaxed mathematical model Taylor series expansion Convex optimization Distributed power generation Energy efficiency Geometry Integer programming MATLAB Quadratic programming Relaxation processes Taylor series Voltage regulators Direct current Distributed generator (DGs) Meta-heuristic optimizations Mixed-integer nonlinear programming Random hyperplane method Sequential quadratic programming Taylor series expansions Taylor series methods Heuristic methods |
| description |
This report addresses the problem of optimal location and sizing of constant power sources (distributed generators (DGs)) in direct current (DC) networks for improving network performance in terms of voltage profiles and energy efficiency. An exact mixed-integer nonlinear programming (MINLP) method is proposed to represent this problem, considering the minimization of total power losses as the objective function. Furthermore, the power balance per node, voltage regulation limits, DG capabilities, and maximum penetration of the DG are considered as constraints. To solve the MINLP model, a convex relaxation is proposed using a Taylor series expansion, in conjunction with the transformation of the binary variables into continuous variables. The solution of the relaxed convex model is constructed using a sequential quadratic programming approach to minimize the linearization error using the Taylor series method. The solution of the relaxed convex model is used as the input for a heuristic random hyperplane method that facilitates the recovery of binary variables that solve the original MINLP model. Two DC distribution feeders, one having 21 and the other having 69 nodes, were used as test systems. Simulation results were obtained using the MATLAB/quadprog package and contrasted with the large-scale nonlinear solvers available for General algebraic modeling system (GAMS) software metaheuristic optimization approaches to demonstrate the robustness and effectiveness of our proposed methodology. © 2019 Elsevier Ltd |
| publishDate |
2020 |
| dc.date.accessioned.none.fl_str_mv |
2020-03-26T16:33:02Z |
| dc.date.available.none.fl_str_mv |
2020-03-26T16:33:02Z |
| dc.date.issued.none.fl_str_mv |
2020 |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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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/publishedVersion |
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Artículo |
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publishedVersion |
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International Journal of Electrical Power and Energy Systems; Vol. 115 |
| dc.identifier.issn.none.fl_str_mv |
01420615 |
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https://hdl.handle.net/20.500.12585/9141 |
| dc.identifier.doi.none.fl_str_mv |
10.1016/j.ijepes.2019.105442 |
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Universidad Tecnológica de Bolívar |
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Repositorio UTB |
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56919564100 57191493648 55791991200 |
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International Journal of Electrical Power and Energy Systems; Vol. 115 01420615 10.1016/j.ijepes.2019.105442 Universidad Tecnológica de Bolívar Repositorio UTB 56919564100 57191493648 55791991200 |
| url |
https://hdl.handle.net/20.500.12585/9141 |
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eng |
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eng |
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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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application/pdf |
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Elsevier Ltd |
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Elsevier Ltd |
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2020-03-26T16:33:02Z2020-03-26T16:33:02Z2020International Journal of Electrical Power and Energy Systems; Vol. 11501420615https://hdl.handle.net/20.500.12585/914110.1016/j.ijepes.2019.105442Universidad Tecnológica de BolívarRepositorio UTB569195641005719149364855791991200This report addresses the problem of optimal location and sizing of constant power sources (distributed generators (DGs)) in direct current (DC) networks for improving network performance in terms of voltage profiles and energy efficiency. An exact mixed-integer nonlinear programming (MINLP) method is proposed to represent this problem, considering the minimization of total power losses as the objective function. Furthermore, the power balance per node, voltage regulation limits, DG capabilities, and maximum penetration of the DG are considered as constraints. To solve the MINLP model, a convex relaxation is proposed using a Taylor series expansion, in conjunction with the transformation of the binary variables into continuous variables. The solution of the relaxed convex model is constructed using a sequential quadratic programming approach to minimize the linearization error using the Taylor series method. The solution of the relaxed convex model is used as the input for a heuristic random hyperplane method that facilitates the recovery of binary variables that solve the original MINLP model. Two DC distribution feeders, one having 21 and the other having 69 nodes, were used as test systems. Simulation results were obtained using the MATLAB/quadprog package and contrasted with the large-scale nonlinear solvers available for General algebraic modeling system (GAMS) software metaheuristic optimization approaches to demonstrate the robustness and effectiveness of our proposed methodology. © 2019 Elsevier LtdUniversidad Tecnológica de Pereira, UTP: C2018P020 Departamento Administrativo de Ciencia, Tecnología e Innovación, COLCIENCIAS: 727-2015This study was funded in part by the Administrative Department of Science, Technology, and Innovation of Colombia ( COLCIENCIAS ) through its National Scholarship Program, under Grant 727-2015 , and in part by Universidad Tecnológica de Bolívar , under Project C2018P020 .Recurso electrónicoapplication/pdfengElsevier Ltdhttp://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-s2.0-85072686799&doi=10.1016%2fj.ijepes.2019.105442&partnerID=40&md5=1afc2e3394c01af635e748ed905ecff0Relaxed convex model for optimal location and sizing of DGs in DC grids using sequential quadratic programming and random hyperplane approachesinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_2df8fbb1Convex optimizationDirect current networksDistributed generationRandom hyperplane methodRelaxed mathematical modelTaylor series expansionConvex optimizationDistributed power generationEnergy efficiencyGeometryInteger programmingMATLABQuadratic programmingRelaxation processesTaylor seriesVoltage regulatorsDirect currentDistributed generator (DGs)Meta-heuristic optimizationsMixed-integer nonlinear programmingRandom hyperplane methodSequential quadratic programmingTaylor series expansionsTaylor series methodsHeuristic methodsMontoya O.D.Gil-González W.Grisales-Noreña L.F.Parhizi, S., Lotfi, H., Khodaei, A., Bahramirad, S., State of the art in research on microgrids: a review (2015) IEEE Access, 3, pp. 890-925Lu, S., Wang, L., Lo, T., Prokhorov, A.V., Integration of wind power and wave power generation systems using a DC microgrid (2015) IEEE Trans Ind Appl, 51 (4), pp. 2753-2761Kwon, M., Choi, S., Control scheme for autonomous and smooth mode switching of bidirectional DCDC converters in a DC microgrid (2018) IEEE Trans Power Electron, 33 (8), pp. 7094-7104Garces, A., Uniqueness of the power flow solutions in low voltage direct current grids (2017) Electr Power Syst Res, 151, pp. 149-153Wang, L., Wang, K., Lee, W., Chen, Z., Power-flow control and stability enhancement of four parallel-operated offshore wind farms using a line-commutated HVDC link (2010) IEEE Trans Power Del, 25 (2), pp. 1190-1202Wang, L., Thi, M.S.N., Comparative stability analysis of 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2018 21st International Conference on Electrical Machines and Systems (ICEMS), pp. 2045-2049http://purl.org/coar/resource_type/c_6501THUMBNAILMiniProdInv.pngMiniProdInv.pngimage/png23941https://repositorio.utb.edu.co/bitstream/20.500.12585/9141/1/MiniProdInv.png0cb0f101a8d16897fb46fc914d3d7043MD5120.500.12585/9141oai:repositorio.utb.edu.co:20.500.12585/91412021-02-02 14:54:10.908Repositorio Institucional UTBrepositorioutb@utb.edu.co |