Heuristic Methodology for Planning AC Rural Medium-Voltage Distribution Grids
The optimal expansion of AC medium-voltage distribution grids for rural applications is addressed in this study from a heuristic perspective. The optimal routes of a distribution feeder are selected by applying the concept of a minimum spanning tree by limiting the number of branches that are connec...
- Autores:
-
Montoya, Oscar Danilo
Serra, Federico Martin
De Angelo, Cristian Hernan
Chamorro, Harold R.
Alvarado-Barrios, Lázaro
- 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:20.500.12585/10395
- Palabra clave:
- Distribution system planning
Tabu search algorithm
Minimum spanning tree
Heuristic optimization methodology
Rural distribution networks
LEMB
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
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Heuristic Methodology for Planning AC Rural Medium-Voltage Distribution Grids |
| title |
Heuristic Methodology for Planning AC Rural Medium-Voltage Distribution Grids |
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Heuristic Methodology for Planning AC Rural Medium-Voltage Distribution Grids Distribution system planning Tabu search algorithm Minimum spanning tree Heuristic optimization methodology Rural distribution networks LEMB |
| title_short |
Heuristic Methodology for Planning AC Rural Medium-Voltage Distribution Grids |
| title_full |
Heuristic Methodology for Planning AC Rural Medium-Voltage Distribution Grids |
| title_fullStr |
Heuristic Methodology for Planning AC Rural Medium-Voltage Distribution Grids |
| title_full_unstemmed |
Heuristic Methodology for Planning AC Rural Medium-Voltage Distribution Grids |
| title_sort |
Heuristic Methodology for Planning AC Rural Medium-Voltage Distribution Grids |
| dc.creator.fl_str_mv |
Montoya, Oscar Danilo Serra, Federico Martin De Angelo, Cristian Hernan Chamorro, Harold R. Alvarado-Barrios, Lázaro |
| dc.contributor.author.none.fl_str_mv |
Montoya, Oscar Danilo Serra, Federico Martin De Angelo, Cristian Hernan Chamorro, Harold R. Alvarado-Barrios, Lázaro |
| dc.subject.keywords.spa.fl_str_mv |
Distribution system planning Tabu search algorithm Minimum spanning tree Heuristic optimization methodology Rural distribution networks |
| topic |
Distribution system planning Tabu search algorithm Minimum spanning tree Heuristic optimization methodology Rural distribution networks LEMB |
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LEMB |
| description |
The optimal expansion of AC medium-voltage distribution grids for rural applications is addressed in this study from a heuristic perspective. The optimal routes of a distribution feeder are selected by applying the concept of a minimum spanning tree by limiting the number of branches that are connected to a substation (mixed-integer linear programming formulation). In order to choose the caliber of the conductors for the selected feeder routes, the maximum expected current that is absorbed by the loads is calculated, thereby defining the minimum thermal bound of the conductor caliber. With the topology and the initial selection of the conductors, a tabu search algorithm (TSA) is implemented to refine the solution with the help of a three-phase power flow simulation in MATLAB for three different load conditions, i.e., maximum, medium, and minimum consumption with values of 100%, 60%, and 30%, respectively. This helps in calculating the annual costs of the energy losses that will be summed with the investment cost in conductors for determining the final costs of the planning project. Numerical simulations in two test feeders comprising 9 and 25 nodes with one substation show the effectiveness of the proposed methodology regarding the final grid planning cost; in addition, the heuristic selection of the calibers using the minimum expected current absorbed by the loads provides at least 70% of the calibers that are contained in the final solution of the problem. This demonstrates the importance of using adequate starting points to potentiate metaheuristic optimizers such as the TSA. |
| publishDate |
2021 |
| dc.date.issued.none.fl_str_mv |
2021-08-20 |
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2022-01-24T21:13:20Z |
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2022-01-24T21:13:20Z |
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2022-01-24 |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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info:eu-repo/semantics/restrictedAccess |
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http://purl.org/coar/resource_type/c_6501 |
| dc.identifier.citation.spa.fl_str_mv |
Montoya, O.D.; Serra, F.M.; De Angelo, C.H.; Chamorro, H.R.; Alvarado-Barrios, L. Heuristic Methodology for Planning AC Rural Medium-Voltage Distribution Grids. Energies 2021, 14, 5141. https://doi.org/10.3390/en14165141 |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/10395 |
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https://doi.org/10.3390/en14165141 |
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Universidad Tecnológica de Bolívar |
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Repositorio Universidad Tecnológica de Bolívar |
| identifier_str_mv |
Montoya, O.D.; Serra, F.M.; De Angelo, C.H.; Chamorro, H.R.; Alvarado-Barrios, L. Heuristic Methodology for Planning AC Rural Medium-Voltage Distribution Grids. Energies 2021, 14, 5141. https://doi.org/10.3390/en14165141 Universidad Tecnológica de Bolívar Repositorio Universidad Tecnológica de Bolívar |
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https://hdl.handle.net/20.500.12585/10395 https://doi.org/10.3390/en14165141 |
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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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Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
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openAccess |
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20 páginas |
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application/pdf |
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Cartagena de Indias |
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Energies vol. 14 n° 16 2021 |
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Universidad Tecnológica de Bolívar |
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Montoya, Oscar Danilo8a59ede1-6a4a-4d2e-abdc-d0afb14d4480Serra, Federico Martin563870d4-de87-4b6e-8a41-9a7861d64fecDe Angelo, Cristian Hernan1476b6d7-1a89-4201-bb96-5c45c0ac8635Chamorro, Harold R.59e2dcd8-f603-4e1f-8459-da694d5a324dAlvarado-Barrios, Lázaro57fdbc12-9b16-4b46-abf4-0ba206be47002022-01-24T21:13:20Z2022-01-24T21:13:20Z2021-08-202022-01-24Montoya, O.D.; Serra, F.M.; De Angelo, C.H.; Chamorro, H.R.; Alvarado-Barrios, L. Heuristic Methodology for Planning AC Rural Medium-Voltage Distribution Grids. Energies 2021, 14, 5141. https://doi.org/10.3390/en14165141https://hdl.handle.net/20.500.12585/10395https://doi.org/10.3390/en14165141Universidad Tecnológica de BolívarRepositorio Universidad Tecnológica de BolívarThe optimal expansion of AC medium-voltage distribution grids for rural applications is addressed in this study from a heuristic perspective. The optimal routes of a distribution feeder are selected by applying the concept of a minimum spanning tree by limiting the number of branches that are connected to a substation (mixed-integer linear programming formulation). In order to choose the caliber of the conductors for the selected feeder routes, the maximum expected current that is absorbed by the loads is calculated, thereby defining the minimum thermal bound of the conductor caliber. With the topology and the initial selection of the conductors, a tabu search algorithm (TSA) is implemented to refine the solution with the help of a three-phase power flow simulation in MATLAB for three different load conditions, i.e., maximum, medium, and minimum consumption with values of 100%, 60%, and 30%, respectively. This helps in calculating the annual costs of the energy losses that will be summed with the investment cost in conductors for determining the final costs of the planning project. Numerical simulations in two test feeders comprising 9 and 25 nodes with one substation show the effectiveness of the proposed methodology regarding the final grid planning cost; in addition, the heuristic selection of the calibers using the minimum expected current absorbed by the loads provides at least 70% of the calibers that are contained in the final solution of the problem. This demonstrates the importance of using adequate starting points to potentiate metaheuristic optimizers such as the TSA.20 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_abf2Energies vol. 14 n° 16 2021Heuristic Methodology for Planning AC Rural Medium-Voltage Distribution Gridsinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/restrictedAccesshttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Distribution system planningTabu search algorithmMinimum spanning treeHeuristic optimization methodologyRural distribution networksLEMBCartagena de IndiasPicard, J.L.; Aguado, I.; Cobos, N.G.; Fuster-Roig, V.; Quijano-López, A. Electric Distribution System Planning Methodology Considering Distributed Energy Resources: A Contribution towards Real Smart Grid Deployment. Energies 2021, 14, 1924.Riaño, F.E.; Cruz, J.F.; Montoya, O.D.; Chamorro, H.R.; Alvarado-Barrios, L. Reduction of Losses and Operating Costs in Distribution Networks Using a Genetic Algorithm and Mathematical Optimization. Electronics 2021, 10, 419Li, R.; Wang, W.; Chen, Z.; Jiang, J.; Zhang, W. A Review of Optimal Planning Active Distribution System: Models, Methods, and Future Researches. Energies 2017, 10, 1715.Lavorato, M.; Franco, J.F.; Rider, M.J.; Romero, R. Imposing Radiality Constraints in Distribution System Optimization Problems. IEEE Trans. Power Syst. 2012, 27, 172–180Farrag, M. A new model for distribution system planning. Int. J. Electr. Power Energy Syst. 1999, 21, 523–531.Mejía-Solanilla, A.M.; Hincapié-Isaza, R.A.; Gallego-Rendón, R.A. Optimal planning of distribution systems considering multiple objectives: Investment cost, reliability and technical losses. Rev. Tecnura 2015, 19, 106Dong, Y.F.; Gu, J.H.; Li, N.N.; Hou, X.D.; Yan, W.L. Combination of Genetic Algorithm and Ant Colony Algorithm for Distribution Network Planning. In Proceedings of the 2007 IEEE International Conference on Machine Learning and Cybernetics, Hong Kong, China, 19–22 August 2007Kilyeni, S.; Barbulescu, C.; Simo, A.; Teslovan, R.; Oros, C. Genetic algorithm based distribution network expansion planning. In Proceedings of the 2014 IEEE 49th International Universities Power Engineering Conference (UPEC), Cluj-Napoca, Romania, 2–5 September 2014;Montoya, O.D.; Grajales, A.; Hincapié, R.A.; Granada, M. A new approach to solve the distribution system planning problem considering automatic reclosers. Ing. Rev. Chil. Ing. 2017, 25, 415–429Montoya, O.D.; Giraldo, J.S.; Grisales-Noreña, L.F.; Chamorro, H.R.; Alvarado-Barrios, L. Accurate and Efficient Derivative-Free Three-Phase Power Flow Method for Unbalanced Distribution Networks. Computation 2021, 9, 61Mohamad, H.; Zalnidzham, W.I.F.W.; Salim, N.A.; Shahbudin, S.; Yasin, Z.M. Power system restoration in distribution network using minimum spanning tree—Kruskal’s algorithm. Indones. J. Electr. Eng. Comput. Sci. 2019, 16, 1–8.Lavorato, M.; Rider, M.J.; Garcia, A.V.; Romero, R. Distribution network planning using a constructive heuristic algorithm. In Proceedings of the 2009 IEEE Power & Energy Society General Meeting, Calgary, AB, Canada, 26–30 July 2009Montoya, O.; Grajales, A.; Hincapié, R. Optimal selection of conductors in distribution systems using tabu search algorithm. Ing. Rev. Chil. Ing. 2018, 26, 283–295. [Granada, M.; Gallego-Rendón, R.A.; López-Lezama, J.M. Optimal Phase Balancing Planning for Loss Reduction in Distribution Systems using a Specialized Genetic Algorithm. Ing. Cienc. 2012, 8, 121–140.Rao, B.; Kupzog, F.; Kozek, M. Three-Phase Unbalanced Optimal Power Flow Using Holomorphic Embedding Load Flow Method. Sustainability 2019, 11, 1774.Cortés-Caicedo, B.; Avellaneda-Gómez, L.S.; Montoya, O.D.; Alvarado-Barrios, L.; Chamorro, H.R. Application of the Vortex Search Algorithm to the Phase-Balancing Problem in Distribution Systems. Energies 2021, 14, 1282.Lavorato, M.; Rider, M.J.; Garcia, A.V.; Romero, R. A Constructive Heuristic Algorithm for Distribution System Planning. IEEE Trans. Power Syst. 2010, 25, 1734–1742.Fan, N.; Golari, M. Integer Programming Formulations for Minimum Spanning Forests and Connected Components in Sparse Graphs. In Combinatorial Optimization and Applications; Springer International Publishing: New York, NY, USA, 2014; pp. 613–622Haouari, M.; Chaouachi, J.; Dror, M. Solving the generalized minimum spanning tree problem by a branch-and-bound algorithm. J. Oper. Res. Soc. 2005, 56, 382–389Malamaki, K.N.D.; Konstantinidis, I.; Demoulias, C.S. Analytical evaluation of the annual load duration curve of domestic prosumers. In Proceedings of the 2017 IEEE Manchester PowerTech, Manchester, UK, 18–22 June 2017Caserta, M. Tabu Search-Based Metaheuristic Algorithm for Large-scale Set Covering Problems. In Metaheuristics; Springer: New York, NY, USA, 2007; pp. 43–63Xing, L.; Liu, Y.; Li, H.; Wu, C.C.; Lin, W.C.; Chen, X. A Novel Tabu Search Algorithm for Multi-AGV Routing Problem. Mathematics 2020, 8, 279Tang, F.; Zhou, H.; Wu, Q.; Qin, H.; Jia, J.; Guo, K. A Tabu Search Algorithm for the Power System Islanding Problem. Energies 2015, 8, 11315–11341.Lucay, F.; Gálvez, E.; Cisternas, L. Design of Flotation Circuits Using Tabu-Search Algorithms: Multispecies, Equipment Design, and Profitability Parameters. Minerals 2019, 9, 181.Ismael, S.M.; Aleem, S.H.E.A.; Abdelaziz, A.Y. Optimal selection of conductors in Egyptian radial distribution systems using sine-cosine optimization algorithm. In Proceedings of the IEEE 2017 Nineteenth International Middle East Power Systems Conference (MEPCON), Cairo, Egypt, 19–21 December 2017;Martínez-Gil, J.F.; Moyano-García, N.A.; Montoya, O.D.; Alarcon-Villamil, J.A. Optimal Selection of Conductors in Three-Phase Distribution Networks Using a Discrete Version of the Vortex Search Algorithm. 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