An approximate mixed-Integer convex model to reduce annual operating costs in radial distribution networks using STATCOMs
: The problem of optimal siting and sizing of distribution static compensators (STATCOMs) is addressed in this research from the point of view of exact mathematical optimization. The exact mixed-integer nonlinear programming model (MINLP) is decoupled into two convex optimization sub-problems, named...
- Autores:
-
Montoya, Oscar Danilo
Alvarado-Barrios, Lázaro
Hernández, Jesus C.
- 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:20.500.12585/10624
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/10624
https://doi.org/10.3390/electronics10243102
- Palabra clave:
- Mixed-integer quadratic relaxation
Second-order cone programming reformulation
Decoupled solution methodology
Location problem
Sizing problem
Distribution static compensators
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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dc.title.spa.fl_str_mv |
An approximate mixed-Integer convex model to reduce annual operating costs in radial distribution networks using STATCOMs |
title |
An approximate mixed-Integer convex model to reduce annual operating costs in radial distribution networks using STATCOMs |
spellingShingle |
An approximate mixed-Integer convex model to reduce annual operating costs in radial distribution networks using STATCOMs Mixed-integer quadratic relaxation Second-order cone programming reformulation Decoupled solution methodology Location problem Sizing problem Distribution static compensators |
title_short |
An approximate mixed-Integer convex model to reduce annual operating costs in radial distribution networks using STATCOMs |
title_full |
An approximate mixed-Integer convex model to reduce annual operating costs in radial distribution networks using STATCOMs |
title_fullStr |
An approximate mixed-Integer convex model to reduce annual operating costs in radial distribution networks using STATCOMs |
title_full_unstemmed |
An approximate mixed-Integer convex model to reduce annual operating costs in radial distribution networks using STATCOMs |
title_sort |
An approximate mixed-Integer convex model to reduce annual operating costs in radial distribution networks using STATCOMs |
dc.creator.fl_str_mv |
Montoya, Oscar Danilo Alvarado-Barrios, Lázaro Hernández, Jesus C. |
dc.contributor.author.none.fl_str_mv |
Montoya, Oscar Danilo Alvarado-Barrios, Lázaro Hernández, Jesus C. |
dc.subject.keywords.spa.fl_str_mv |
Mixed-integer quadratic relaxation Second-order cone programming reformulation Decoupled solution methodology Location problem Sizing problem Distribution static compensators |
topic |
Mixed-integer quadratic relaxation Second-order cone programming reformulation Decoupled solution methodology Location problem Sizing problem Distribution static compensators |
description |
: The problem of optimal siting and sizing of distribution static compensators (STATCOMs) is addressed in this research from the point of view of exact mathematical optimization. The exact mixed-integer nonlinear programming model (MINLP) is decoupled into two convex optimization sub-problems, named the location problem and the sizing problem. The location problem is addressed by relaxing the exact MINLP model, assuming that all the voltages are equal to 1∠0 ◦ , which allows obtaining a mixed-integer quadratic programming model as a function of the active and reactive power flows. The solution of this model provides the best set of nodes to locate all the STATCOMs. When all the nodes are selected, it solves the optimal reactive power problem through a second-order cone programming relaxation of the exact optimal power flow problem; the solution of the SOCP model provides the optimal sizes of the STATCOMs. Finally, it refines the exact objective function value due to the intrinsic non-convexities associated with the costs of the STATCOMs that were relaxed through the application of Taylor’s series expansion in the location and sizing stages. The numerical results in the IEEE 33- and 69-bus systems demonstrate the effectiveness and robustness of the proposed optimization problem when compared with large-scale MINLP solvers in GAMS and the discrete-continuous version of the vortex search algorithm (DCVSA) recently reported in the current literature. With respect to the benchmark cases of the test feeders, the proposed approach reaches the best reductions with 14.17% and 15.79% in the annual operative costs, which improves the solutions of the DCVSA, which are 13.71% and 15.30%, respectively |
publishDate |
2021 |
dc.date.issued.none.fl_str_mv |
2021-12-13 |
dc.date.accessioned.none.fl_str_mv |
2022-03-18T18:32:38Z |
dc.date.available.none.fl_str_mv |
2022-03-18T18:32:38Z |
dc.date.submitted.none.fl_str_mv |
2022-03-18 |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.hasVersion.spa.fl_str_mv |
info:eu-repo/semantics/restrictedAccess |
dc.type.spa.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.identifier.citation.spa.fl_str_mv |
Montoya, O.D.; Alvarado-Barrios, L.; Hernández, J.C. An Approximate Mixed-Integer Convex Model to Reduce Annual Operating Costs in Radial Distribution Networks Using STATCOMs. Electronics 2021, 10, 3102. https://doi.org/10.3390/electronics10243102 |
dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/10624 |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.3390/electronics10243102 |
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 |
Montoya, O.D.; Alvarado-Barrios, L.; Hernández, J.C. An Approximate Mixed-Integer Convex Model to Reduce Annual Operating Costs in Radial Distribution Networks Using STATCOMs. Electronics 2021, 10, 3102. https://doi.org/10.3390/electronics10243102 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
url |
https://hdl.handle.net/20.500.12585/10624 https://doi.org/10.3390/electronics10243102 |
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.uri.*.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
dc.rights.accessRights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
dc.rights.cc.*.fl_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://purl.org/coar/access_right/c_abf2 |
eu_rights_str_mv |
openAccess |
dc.format.extent.none.fl_str_mv |
15 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 |
Electronics 2021, 10, 3102 |
institution |
Universidad Tecnológica de Bolívar |
bitstream.url.fl_str_mv |
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Montoya, Oscar Danilo8a59ede1-6a4a-4d2e-abdc-d0afb14d4480Alvarado-Barrios, Lázaro32360024-18b0-46cd-8b05-2744e95b85f6Hernández, Jesus C.349b3120-388b-42be-8bea-32156f0dc09d2022-03-18T18:32:38Z2022-03-18T18:32:38Z2021-12-132022-03-18Montoya, O.D.; Alvarado-Barrios, L.; Hernández, J.C. An Approximate Mixed-Integer Convex Model to Reduce Annual Operating Costs in Radial Distribution Networks Using STATCOMs. Electronics 2021, 10, 3102. https://doi.org/10.3390/electronics10243102https://hdl.handle.net/20.500.12585/10624https://doi.org/10.3390/electronics10243102Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de Bolívar: The problem of optimal siting and sizing of distribution static compensators (STATCOMs) is addressed in this research from the point of view of exact mathematical optimization. The exact mixed-integer nonlinear programming model (MINLP) is decoupled into two convex optimization sub-problems, named the location problem and the sizing problem. The location problem is addressed by relaxing the exact MINLP model, assuming that all the voltages are equal to 1∠0 ◦ , which allows obtaining a mixed-integer quadratic programming model as a function of the active and reactive power flows. The solution of this model provides the best set of nodes to locate all the STATCOMs. When all the nodes are selected, it solves the optimal reactive power problem through a second-order cone programming relaxation of the exact optimal power flow problem; the solution of the SOCP model provides the optimal sizes of the STATCOMs. Finally, it refines the exact objective function value due to the intrinsic non-convexities associated with the costs of the STATCOMs that were relaxed through the application of Taylor’s series expansion in the location and sizing stages. The numerical results in the IEEE 33- and 69-bus systems demonstrate the effectiveness and robustness of the proposed optimization problem when compared with large-scale MINLP solvers in GAMS and the discrete-continuous version of the vortex search algorithm (DCVSA) recently reported in the current literature. With respect to the benchmark cases of the test feeders, the proposed approach reaches the best reductions with 14.17% and 15.79% in the annual operative costs, which improves the solutions of the DCVSA, which are 13.71% and 15.30%, respectively15 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_abf2Electronics 2021, 10, 3102An approximate mixed-Integer convex model to reduce annual operating costs in radial distribution networks using STATCOMsinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/restrictedAccesshttp://purl.org/coar/resource_type/c_2df8fbb1Mixed-integer quadratic relaxationSecond-order cone programming reformulationDecoupled solution methodologyLocation problemSizing problemDistribution static compensatorsCartagena de IndiasInvestigadoresTemiz, A.; Almalki, A.M.; Kahraman, Ö.; Alshahrani, S.S.; Sönmez, E.B.; Almutairi, S.S.; Nadar, A.; Smiai, M.S.; Alabduljabbar, A.A. Investigation of MV Distribution Networks with High-Penetration Distributed PVs: Study for an Urban Area. Energy Procedia 2017, 141, 517–524Táczi, I.; Sinkovics, B.; Vokony, I.; Hartmann, B. The Challenges of Low Voltage Distribution System State Estimation—An Application Oriented Review. Energies 2021, 14, 5363Arulraj, R.; Kumarappan, N. Optimal economic-driven planning of multiple DG and capacitor in distribution network considering different compensation coefficients in feeder’s failure rate evaluation. Eng. Sci. Technol. Int. J. 2019, 22, 67–77Castiblanco-Pérez, C.M.; Toro-Rodríguez, D.E.; Montoya, O.D.; Giral-Ramírez, D.A. Optimal Placement and Sizing of DSTATCOM in Radial and Meshed Distribution Networks Using a Discrete-Continuous Version of the Genetic Algorithm. Electronics 2021, 10, 1452.Abagiu, S.; Lepadat, I.; Helerea, E. Solutions for energy losses reduction in power networks with renewable energy sources. In Proceedings of the 2016 International Conference on Applied and Theoretical Electricity (ICATE), Craiova, Romania, 6–8 October 2016Soma, G.G. Optimal Sizing and Placement of Capacitor Banks in Distribution Networks Using a Genetic Algorithm. Electricity 2021, 2, 187–204.Gnanasekaran, N.; Chandramohan, S.; Kumar, P.S.; Imran, A.M. Optimal placement of capacitors in radial distribution system using shark smell optimization algorithm. Ain Shams Eng. J. 2016, 7, 907–916Tamilselvan, V.; Jayabarathi, T.; Raghunathan, T.; Yang, X.S. Optimal capacitor placement in radial distribution systems using flower pollination algorithm. Alex. Eng. J. 2018, 57, 2775–2786Sedighizadeh, M.; Dakhem, M.; Sarvi, M.; Kordkheili, H.H. Optimal reconfiguration and capacitor placement for power loss reduction of distribution system using improved binary particle swarm optimization. Int. J. Energy Environ. Eng. 2014, 5, 3.Salau, A.O.; Gebru, Y.W.; Bitew, D. Optimal network reconfiguration for power loss minimization and voltage profile enhancement in distribution systems. Heliyon 2020, 6, e04233Pruitt, K.A.; Leyffer, S.; Newman, A.M.; Braun, R.J. A mixed-integer nonlinear program for the optimal design and dispatch of distributed generation systems. Optim. Eng. 2013, 15, 167–197Kaur, 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, 609–617Valencia, 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. J. Energy Storage 2021, 34, 102158Home-Ortiz, J.M.; Pourakbari-Kasmaei, M.; Lehtonen, M.; Mantovani, J.R.S. Optimal location-allocation of storage devices and renewable-based DG in distribution systems. Electr. Power Syst. Res. 2019, 172, 11–21.Hassan, A.S.; Othman, E.A.; Bendary, F.M.; Ebrahim, M.A. Optimal integration of distributed generation resources in active distribution networks for techno-economic benefits. Energy Rep. 2020, 6, 3462–3471Montoya, 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, 2175Sirjani, R.; Jordehi, A.R. Optimal placement and sizing of distribution static compensator (D-STATCOM) in electric distribution networks: A review. Renew. Sustain. Energy Rev. 2017, 77, 688–694.. Ayodele, T.; Ogunjuyigbe, A.; Akpeji, K.; Akinola, O. Prioritized rule based load management technique for residential building powered by PV/battery system. Eng. Sci. Technol. Int. J. 2017, 20, 859–873Kerrouche, K.D.E.; Lodhi, E.; Kerrouche, M.B.; Wang, L.; Zhu, F.; Xiong, G. Modeling and design of the improved D-STATCOM control for power distribution grid. SN Appl. Sci. 2020, 2, 1519Montoya, O.D.; Chamorro, H.R.; Alvarado-Barrios, L.; Gil-González, W.; Orozco-Henao, C. Genetic-Convex Model for Dynamic Reactive Power Compensation in Distribution Networks Using D-STATCOMs. Appl. Sci. 2021, 11, 3353Farivar, M.; Low, S.H. Branch Flow Model: Relaxations and Convexification—Part I. IEEE Trans. Power Syst. 2013, 28, 2554–2564Taylor, J.A.; Hover, F.S. Convex Models of Distribution System Reconfiguration. IEEE Trans. Power Syst. 2012, 27, 1407–1413Zhao, Y.; Liu, S. Global optimization algorithm for mixed integer quadratically constrained quadratic program. J. Comput. Appl. Math. 2017, 319, 159–169. [Benson, H.Y.; Ümit Sa ˘glam. Mixed-Integer Second-Order Cone Programming: A Survey. In Theory Driven by Influential Applications; INFORMS: Catonsville, MD, USA, 2013; pp. 13–36Sharma, A.K.; Saxena, A.; Tiwari, R. Optimal Placement of SVC Incorporating Installation Cost. Int. J. Hybrid Inf. Technol. 2016, 9, 289–302.Montoya, O.D.; Fuentes, J.E.; Moya, F.D.; Barrios, J.Á.; Chamorro, H.R. Reduction of Annual Operational Costs in Power Systems through the Optimal Siting and Sizing of STATCOMs. Appl. 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