Reconfiguración de redes eléctricas de distribución mediante el algoritmo de recocido simulado
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https://doi.org/10.21754/tecnia.v34i1.1724Palabras clave:
Redes de distribución; Reconfiguración; Recocido Simulado; Optimización; Malla de espacio selectivoResumen
Este artículo presenta un nuevo algoritmo para resolver el problema de la reconfiguración de redes de distribución utilizando Optimización de Recocido Simulado. El método propuesto proporciona una mejora en relación al método clásico, así como la tasa de convergencia entre sus simulaciones, utilizando los recursos del software Open Distribución System Simulator (OpenDSS). Además de utilizar el concepto de búsqueda por malla del espacio selectivo, que reduce considerablemente el espacio de búsqueda de soluciones. El algoritmo propuesto tiene como objetivo reducir las pérdidas de energía en las redes de
distribución, su funcionamiento se aplicó al sistema sencillo de 5 barras. Finalmente, el algoritmo propuesto se aplicó al sistema de prueba de distribución de 33 barras, comúnmente encontrado en la literatura. Los resultados de la simulación muestran que el método propuesto es muy eficiente y garantiza la obtención del óptimo global.
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B. Avelar Rodrigues de Andrade y N. Roberto Ferreira. “Simulated annealing and tabu search applied on network reconfiguration in distribution systems”. En: 2018 Simposio Brasileiro de Sistemas Eletricos (SBSE), 2018, pp. 1–6, doi: 10.1109/SBSE.2018.8395757.
M. Antončič, M. Mikec y B. Blažič. “Development of distribution network model in OpenDSS using Matlab and GIS data”. En: 2019 7th International Youth Conference on Energy (IYCE), 2019, pp. 1–6, doi: 10.1109/IYCE45807.2019.8991604.
A. Augugliaro, L. Dusonchet y E. Riva Sanseverino. “Genetic, simulated annealing and tabu search algorithms: Three heuristic methods for optimal reconfiguration and compensation of distribution networks”, European Transactions on Electrical Power, vol. 9, 1999, pp. 35–41, doi: 10.1002/etep.4450090104.
M.E. Baran y F.F. Wu. “Network reconfiguration in distribution systems for loss reduction and load balancing”, IEEE Transactions on Power Delivery, vol 4, no. 2, 1989, pp. 1401–1407. doi: 10.1109/61.25627.
D. Pinheiro Bernardon. “Novos Métodos para Reconfiguração das Redes de Distribuição a partir de Algoritmos de Tomadas de Decisão Multicritérios”. Tesis de Doctorado, Universidad Federal de Santa Maria, Río Grande del Sur, Brasil, 2007. [En línea]. Disponible: http://repositorio.ufsm.br/handle/1/3651
R.E. Brown. “Distribution reliability assessment and reconfiguration optimization”. En: 2001 IEEE/PES Transmission and Distribution Conference and Exposition. Developing New Perspectives (Cat.No.01CH37294), Vol. 2. 2001, 994–999 vol.2. doi: 10.1109/TDC.2001.971382.
J. Brownlee. Clever algorithms: nature-inspired programming recipes. Jason Brownlee, 2011.
J. Chen, F. Zhang y Y. Zhang. “Distribution Network Reconfiguration Based on Simulated Annealing Immune Algorithm”, Energy Procedia, vol. 12, 2011, pp. 271–277. doi: 10.1016/j.egypro.2011.10.037.
E. Chen, S. Zhang y T. Wang. “Research on distribution network reconstruction based on improved simulated annealing — Ant colony algorithm”. En: 2017 Chinese Automation Congress (CAC), 2017, pp. 3575–3579. doi: 10.1109/CAC.2017.8243401.
H. D. Chiang y R. Jean-Jumeau. “Optimal network reconfigurations in distribution systems. I. A new formulation and a solution methodology”, IEEE Transactions on Power Delivery, vol. 5, no. 4, pp. 1902–1909, 1990. doi: 10.1109/61.103687.
R. Chibante. Simulated annealing: theory with applications. BoD–Books on Demand, 2010.
S. Civanlar et al. “Distribution feeder reconfiguration for loss reduction”, IEEE Transactions on Power Delivery, vol. 3, no. 3, pp. 1217–1223, 1988. doi: 10.1109/61.193906.
R. C. Dugan y D. Montenegro. “Reference Guide: The Open Distribution System Simulator (OpenDSS)”. Electric Power Research Institute, Inc, vol. 9.0, 2020, pp. 1–218. [En línea]. Disponible: https://sourceforge.net/p/electricdss/code/HEAD/tree/trunk/Distrib/Doc/OpenDSS Manual.pdf
E. Goldbarg, M. Goldbarg y H. Luna. Otimização combinatória e metaheurıésticas: algoritmos e apliacações. Elsevier Brasil, 2017.
Y. J. Jeon y J. C. Kim. “Network reconfiguration in radial distribution system using simulated annealing and Tabu search”, 2000 IEEE Power Engineering Society Winter Meeting. Conference Proceedings, Vol. 4, pp. 2329–2333, 2000. doi: 10.1109/PESW. 2000.847169.
S. Koziel, A. Landeros y S. Moskwa. “Power loss reduction through distribution network reconfiguration using feasibility-preserving simulated annealing”, 2018 19th International Scientific Conference on Electric Power Engineering (EPE), pp. 1–5, 2018. doi: 10.1109/EPE.2018.8396016.
M. Lavorato et al. “Imposing radiality constraints in distribution system optimization problems”, IEEE Transactions on Power Systems, vol. 27, no. 1, pp. 172–180, 2011. doi: 10.1109/TPWRS.2011.2161349
R. C. Marques, H. S. Eichkoff y A. P. C. de Mello. “Analysis of the distribution network reconfiguration using the OpenDSS®software”. En: 2018 Simposio Brasileiro de Sistemas Eletricos (SBSE), 2018, pp. 1–6. doi: 10.1109/SBSE.2018.8395703.
A. P. Carboni de Mello. “Reconfiguração de redes de distribuição considerando multivariáveis e geração distribuída”. 2014 Universidade Federal de Santa Maria. Tesis de Maestría, Universidad Federal de Santa Maria, Río Grande del Sur, Brasil, 2014. [En línea]. Disponible: http://repositorio.ufsm.br/handle/1/8537
A. Merlin y H. Back. “Search for a Minimal-Loss Operating Spanning Tree Configuration in an Urban Power Distribution System”. En: Fifth Power Systems Computer Conference (PSCC), 1975.
D. Montenegro. “Introduction to the Next Generation of Distribution Analysis Tools – Summer course D1”. En: Electric Power Research Institute, 2019, pp. 1–105. [En línea]. Disponible: https://sourceforge.net/p/electricdss/code/2705/tree/trunk/Training/Uniandes-2019/NGDAT_Day_1.pdf
S. Nie et al. “Analysis of the impact of DG on distribution network reconfiguration using OpenDSS”. En: IEEE PES Innovative Smart Grid Technologies, 2012, pp. 1–5. doi: 10.1109/ISGT-Asia.2012.6303390.
T. Niknam, E. Azadfarsani y M. Jabbari. “A new hybrid evolutionary algorithm based on new fuzzy adaptive PSO and NM algorithms for distribution feeder reconfiguration”. En: Energy Conversion and Management, vol. 54, no. 1, pp. 7–16, 2012. doi: 10.1016/j.enconman.2011.09.014
R. Pegado et al. “Radial distribution network reconfiguration for power losses reduction based on improved selective BPSO”. En: Electric Power Systems Research, vol. 169, pp. 206–213, 2019. doi: 10.1016/j.epsr.2018.12.030.
R. de Araújo Pegado. Reconfiguração de redes de distribuição de energia elétrica usando otimização por enxame de partículas aprimorado. Tesis de Maestría. Universidade Federal da Paraíba, Paraíba, Brasil, 2019. [En línea]. Disponible: https://repositorio.ufpb.br/jspui/handle/123456789/17174
G.J. Peponis, M.P. Papadopoulos y N.D. Hatziargyriou. “Distribution network reconfiguration to minimize resistive line losses”, IEEE Transactions on Power Delivery, vol. 10, no. 3, pp. 1338–1342, 1995. doi: 10.1109/61.400914.
F. S. Pereira, K. Vittori y G. R. M. da Costa. “Ant colony based method for reconfiguration of power distribution system to reduce losses”. En: 2008 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, 2008, pp. 1–5. doi: 10.1109/TDC-LA.2008.4641831.
J. Sexauver. “New User Primer: The Open Distribution System Simulator (OpenDSS)”, Electric Power Research Institute, Inc, vol. 7, no. 6, 2012, pp. 1–35.
D. Shirmohammadi y H.W. Hong. “Reconfiguration of electric distribution networks for resistive line losses reduction”, IEEE Transactions on Power Delivery, vol 4, no.2, pp. 1492–1498, 1989. doi: 10.1109/61.25637.
A. Skoonpong y S. Sirisumrannukul. “Network Reconfiguration for Reliability Worth Enhancement in Distribution Systems by multi-objective evolutionary algorithm based on decomposition integrating with thought of simulated annealing”, 2008 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, 2008. doi: 10.1109/ECTICON.2008.4600585
El-Ghazali Talbi. Metaheuristics: from design to implementation. John Wiley & Sons, 2009.
M. Zulqarnain Zeb et al. “Optimal Placement of Electric Vehicle Charging Stations in the Active Distribution Network”, IEEE Access, vol. 8, pp. 68124–68134, 2020. doi: 10.1109/ACCESS.2020.2984127.
J. Zhang, Z. Li y B. Wang. “Within-day rolling optimal scheduling problem for active distribution networks by Simulated Annealing”, Energy, Vol. 223, pp. 937–940, 2021. doi: 10.1016/j.energy.2021.120027.
M. Zhigang. “Study on distribution network reconfiguration based on genetic simulated annealing algorithm”. En: 2008 China International Conference on Electricity Distribution, 2008, pp. 1–7. doi: 10.1109/CICED.2008.5211684.
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