Óptima planeación de redes celulares para la infraestructura de medición inteligente en zonas rurales y remotas
La medición inteligente se emplea para controlar, monitorear y conocer el estado del sistema en tiempo real; por ese motivo, la incorporación de redes inteligentes beneficia primordialmente al sistema eléctrico. Así mismo, con la reutilización de la infraestructura y del espectro celular, ayuda a mi...
- Autores:
-
Masache, Andrés
Inga, Esteban
Hincapié, Roberto
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2015
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/12121
- Palabra clave:
- Red Eléctrica Inteligente
Medición Inteligente
AMI
Red Celular
Óptima Planeación
Tráfico
Enrutamiento Óptimo
Smart Grid
Smart Metering
AMI
Cellular Network
Optimal Planning
Traffic
Optimal Routing
- Rights
- openAccess
- License
- INGE CUC - 2015
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Óptima planeación de redes celulares para la infraestructura de medición inteligente en zonas rurales y remotas |
| dc.title.translated.eng.fl_str_mv |
Optimal planning for cellular networks for smart metering infrastructure in rural and remote areas |
| title |
Óptima planeación de redes celulares para la infraestructura de medición inteligente en zonas rurales y remotas |
| spellingShingle |
Óptima planeación de redes celulares para la infraestructura de medición inteligente en zonas rurales y remotas Red Eléctrica Inteligente Medición Inteligente AMI Red Celular Óptima Planeación Tráfico Enrutamiento Óptimo Smart Grid Smart Metering AMI Cellular Network Optimal Planning Traffic Optimal Routing |
| title_short |
Óptima planeación de redes celulares para la infraestructura de medición inteligente en zonas rurales y remotas |
| title_full |
Óptima planeación de redes celulares para la infraestructura de medición inteligente en zonas rurales y remotas |
| title_fullStr |
Óptima planeación de redes celulares para la infraestructura de medición inteligente en zonas rurales y remotas |
| title_full_unstemmed |
Óptima planeación de redes celulares para la infraestructura de medición inteligente en zonas rurales y remotas |
| title_sort |
Óptima planeación de redes celulares para la infraestructura de medición inteligente en zonas rurales y remotas |
| dc.creator.fl_str_mv |
Masache, Andrés Inga, Esteban Hincapié, Roberto |
| dc.contributor.author.spa.fl_str_mv |
Masache, Andrés Inga, Esteban Hincapié, Roberto |
| dc.subject.spa.fl_str_mv |
Red Eléctrica Inteligente Medición Inteligente AMI Red Celular Óptima Planeación Tráfico Enrutamiento Óptimo |
| topic |
Red Eléctrica Inteligente Medición Inteligente AMI Red Celular Óptima Planeación Tráfico Enrutamiento Óptimo Smart Grid Smart Metering AMI Cellular Network Optimal Planning Traffic Optimal Routing |
| dc.subject.eng.fl_str_mv |
Smart Grid Smart Metering AMI Cellular Network Optimal Planning Traffic Optimal Routing |
| description |
La medición inteligente se emplea para controlar, monitorear y conocer el estado del sistema en tiempo real; por ese motivo, la incorporación de redes inteligentes beneficia primordialmente al sistema eléctrico. Así mismo, con la reutilización de la infraestructura y del espectro celular, ayuda a mitigar el tiempo y el costo de su implementación. Con la finalidad de reducir el tráfico y la saturación de las redes celulares, se propone determinar la ruta óptima para el envío de la información, para ello se analiza un ruteo óptimo por medio de distancias y un ruteo óptimo por medio de flujo de tráfico. Gracias a este análisis, se determina cuál es la ruta óptima cuando no existe tráfico en la red celular o cuando existe un tráfico prolongado, y cuáles son las tendencias de tráfico que se pueden producir por el envío excesivo de la información de los medidores inteligentes hacia las empresas eléctricas de distribución. |
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2015-06-01 00:00:00 2024-04-09T20:13:45Z |
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2015-06-01 |
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Artículo de revista |
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R. F. Arritt and R. C. Dugan, “Distribution System Analysis and the Future Smart Grid,” IEEE Trans. Ind. Appl., vol. 47, no. 6, pp. 2343–2350, Nov. 2011. DOI: 10.1109/REPCON.2011.5756725 J. Kim, S. Cho, and H. Shin, “Advanced Power Distribution System Con fi guration for Smart Grid,” IEEE Trans. Smart Grid, vol. 4, no. 1, pp. 353–358, 2013. DOI: 10.1109/TSG.2012.2233771 C. Selva, K. Srinivas, G. Ayyappan, and M. Venkatachala, “Advanced Metering Infrastructure for Smart Grid Applications,” Recent Trends Inf. Technol. (ICRTIT), 2012 Int. Conf. IEEE, pp. 145–150, 2012. DOI: 10.1109/ICRTIT.2012.6206777 S. SAydjari and V. Varadharajan, “The Smarter Grid,” Secur. Privacy, IEEE, vol. 8, no. 1, pp. 60 – 63, 2010. DOI: 10.1109/MSP.2010.52 L. Chun-hao and N. Ansari, “CONSUMER : A Novel Hybrid Intrusion Detection System for Distribution Networks in Smart Grid,” IEEE Trans. Emerg. Top. Comput., vol. 1, no. 1, pp. 33 – 44, 2013. DOI: 10.1109/TETC.2013.2274043 E. Inga and J. Inga, “Wireless Communications and Virtual Operator for Residential Electric Metering,” 12th Lat. Am. Caribb. Conf. Eng. Technol., pp. 1–9, 2014. B. Karimi and V. Namboodiri, “On the Capacity of a Wireless Backhaul for the Distribution Level of the Smart Grid,” Syst. Journal, IEEE, vol. 8, no. 2, pp. 521–532, 2014. DOI: 10.1109/JSYST.2013.2260701 E. Inga, R. Hincapie, C. Suarez, and G. Arevalo, “Shortest path for optimal routing on Advanced Metering Infrastructure using cellular networks,” in Communications and Computing (COLCOM), 2015 IEEE Colombian Conference on, 2015, pp. 1 – 6. Z. Jia, J. Chen, and Y. Liao, “State estimation in distribution system considering effects of AMI data,” 2013 Proc. IEEE Southeastcon, pp. 1–6, Apr. 2013. DOI: 10.1109/SECON.2013.6567406 R. R. Mohassel, A. Fung, F. Mohammadi, and K. Raahemifar, “Application of Advanced Metering Infrastructure in Smart Grids,” Control Autom. (MED), 2014 22nd Mediterr. Conf. IEEE, pp. 822 – 828, 2014. DOI: 10.1109/MED.2014.696147 C. Lo and N. Ansari, “The Progressive Smart Grid System from Both Power and Communications Aspects,” Commun. Surv. Tutorials, IEEE, vol. 14, no. 3, pp. 799–821, 2012. DOI: 10.1109/SURV.2011.072811.00089 P. Kulkarni, S. Gormus, Z. Fan, and F. Ramos, “AMI Mesh Networks—A Practical Solution and Its Performance Evaluation,” IEEE Trans. Smart Grid, vol. 3, no. 3, pp. 1469–1481, Sep. 2012. DOI: 10.1109/TSG.2012.2205023 E. Hossain, Z. Han, and H. V. Poor, Smart Grid communication and networking, First edit. United Stated of America: Cambridge University Press, 2012, p. 481. H. Sui and W.-J. Lee, “An AMI based measurement and control system in smart distribution grid,” 2011 IEEE Ind. Commer. Power Syst. Tech. Conf., pp. 1–5, May 2011. DOI: 10.1109/ICPS.2011.5890876 C. Andres and C. John, The Advanced Smart Grid Edge Power Driving Sustainability, First Edit. 2011, p. 268. M. R. Souryal and N. Golmie, “Analysis of advanced metering over a Wide Area Cellular Network,” 2011 IEEE Int. Conf. Smart Grid Commun., pp. 102–107, Oct. 2011. DOI: 10.1109/SmartGridComm.2011.6102299 B. Saint, “Rural Distribution System Planning using Smart Grid Technologies,” Rural Electr. Power Conf. 2009. REPC ’09. IEEE, no. 09, pp. 0–8, 2009. DOI: 10.1109/REPCON.2009.4919421 S. Li, J. Huang, and S. Member, “Dynamic Profit Maximization of Cognitive Mobile Virtual Network Operator,” IEEE Trans. Mob. Comput., vol. 13, no. 3, pp. 526–540, 2014. DOI: 10.1109/TMC.2013.10 M. Gupta, S. Gupta, and T. Thakur, “Design and impact of wireless AMI for distribution utilities,” 2013 Annu. IEEE India Conf., pp. 1–6, Dec. 2013. DOI: 10.1109/INDCON.2013.6726103 H. Li, S. Gong, L. Lai, Z. Han, S. Member, R. C. Qiu, and D. Yang, “Efficient and Secure Wireless Communications for Advanced Metering Infrastructure in Smart Grids,” IEEE Trans. Smart Grid, vol. 3, no. 3, pp. 1540–1551, 2012. DOI: 10.1109/TSG.2012.2203156 A. Peralta-Sevilla, E. Inga, R. Cumbal, and R. Hincapie, “Optimum deployment of FiWi Networks using wireless sensors based on Universal Data Aggregation Points,” in Communications and Computing (COLCOM), 2015 IEEE Colombian Conference on, 2015, pp. 1 – 6. DOI: 10.1109/ColComCon.2015.7152079 I. E. Reid and H. A. Stevens, Smart Meters and the Smart Grid: Privacy and Cybersecurity Considerations, First edit. Nova Science Publishers, Incorporated, 2012, p. 153. S. Cespedes, A. A. Cardenas, and T. Iwao, “Comparison of Data Forwarding Mechanisms for AMI networks,” Innov. Smart Grid Technol. (ISGT), 2012 IEEE PES, pp. 1 – 8, 2012. DOI: 10.1109/ISGT.2012.6175683 C. Scordino and G. Lipari, “A Resource Reservation Algorithm for Power-Aware Scheduling of Periodic and Aperiodic Real-Time Tasks,” Comput. IEEE Trans., vol. 55, no. 12, pp. 1509 – 1522, 2006. DOI: 10.1109/TC.2006.190 L. Duan, J. Huang, and B. Shou, “Cognitive Mobile Virtual Network Operator : Investment and Pricing with Supply Uncertainty,” INFOCOM, 2010 Proc. IEEE, pp. 1 – 9, 2010. DOI: 10.1109/INFCOM.2010.5462146 Z. Fan and R. Zhang, “Spectrum allocation and medium access in cognitive radio wireless networks,” 2009 Eur. Wirel. Conf. IEEE, pp. 90–95, May 2009. DOI: 10.1109/EW.2009.5357757 L. Mastroeni and M. Naldi, “Spectrum reservation options for Mobile Virtual Network Operators,” IEEE 6th EURO-NGI Conf. Next Gener. Internet, vol. 13, p. 15, Jun. 2010. DOI: 10.1109/NGI.2010.5534477 E. Inga, G. Arévalo, and R. Hincapié, “Optimal Deployment of Cellular Networks for Advanced Measurement Infrastructure in Smart Grid,” 2014 IEEE Colomb. Conf. Commun. Comput., no. 1The 2014 IEEE Colombian Conference on Communications and Computing, p. 6, 2014. DOI: 10.1109/ColComCon.2014.6860421 A. D. Dabbagh, R. Ratasuk, and A. Ghosh, “On UMTS-LTE Physical Uplink Shared and Control Channels,” Veh. Technol. Conf. 2008. VTC 2008-Fall. IEEE 68th, pp. 1 – 8, 2008. DOI: 10.1109/VETECF.2008.323 R. Agrawal, R. Berry, J. Huang, and V. Subramanian, “Optimal Scheduling for OFDMA Systems,” Signals, Syst. Comput. 2006. ACSSC ’06. Fortieth Asilomar Conf. IEEE, pp. 1347 – 1351, 2006. DOI: 10.1109/ACSSC.2006.354976 S. Sesia, I. Toufik, and M. Baker, LTE the UMTS Long Term Evolution from theory to practice, Second edi. Great Britain, 2011, p. 794. J. Markkula and J. Haapola, “Impact of smart grid traffic peak loads on shared LTE network performance,” Commun. (ICC), 2013 IEEE Int. Conf., pp. 4046 – 4051, 2013. DOI: 10.1109/ICC.2013.6655193 X. Qin and R. Berry, “Distributed Resource Allocation and Scheduling in OFDMA Wireless Networks,” Signals, Syst. Comput. 2006. ACSSC ’06. Fortieth Asilomar Conf. IEEE, pp. 1942 – 1946, 2006. DOI: 10.1109/ACSSC.2006.355102 E. Ortega, D. Cazco, V. Luna, and J. Ortega, “Comunicaciones celulares para medición inteligente de energía eléctrica en sistemas de distribución,” ingenius.ups.edu.ec, pp. 21–33, 2013. I. Joe, J. Y. J. Zhang, and Fu-Quan, “Design and Implementation of AMI System Using Binary CDMA for Smart Grid,” Intell. Syst. Des. Eng. Appl. (ISDEA), 2013 Third Int. Conf. IEEE, pp. 544 – 549, 2013. DOI: 10.1109/ISDEA.2012.133 K. S. Zigangirov, Theory Of Code Division Multiple Access Communication, First edit. Canada, 2004, p. 412. |
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Masache, Andrés0362534b72f1f817e4e204f0e1ea6184500Inga, Esteban622e8e8eedb01c15a357b777b71f77f4500Hincapié, Robertoc71af5129bbbb7bba4ae9e25e79536195002015-06-01 00:00:002024-04-09T20:13:45Z2015-06-01 00:00:002024-04-09T20:13:45Z2015-06-010122-6517https://hdl.handle.net/11323/12121https://doi.org/10.17981/ingecuc.11.2.2015.0510.17981/ingecuc.11.2.2015.052382-4700La medición inteligente se emplea para controlar, monitorear y conocer el estado del sistema en tiempo real; por ese motivo, la incorporación de redes inteligentes beneficia primordialmente al sistema eléctrico. Así mismo, con la reutilización de la infraestructura y del espectro celular, ayuda a mitigar el tiempo y el costo de su implementación. Con la finalidad de reducir el tráfico y la saturación de las redes celulares, se propone determinar la ruta óptima para el envío de la información, para ello se analiza un ruteo óptimo por medio de distancias y un ruteo óptimo por medio de flujo de tráfico. Gracias a este análisis, se determina cuál es la ruta óptima cuando no existe tráfico en la red celular o cuando existe un tráfico prolongado, y cuáles son las tendencias de tráfico que se pueden producir por el envío excesivo de la información de los medidores inteligentes hacia las empresas eléctricas de distribución.Smart metering is used to control, monitor and know the system status in real time; to this effect, the incorporation of smart grids primarily benefits the electrical system; similarly, the reuse of infrastructure and cellular spectrum help mitigate the time and cost of its implementation. In order to reduce traffic and saturation of cellular networks, this paper aims at determining the optimal route for information transmission analyzing the optimal routing through distances and optimal routing through traffic flow. This analysis helps determine what the optimal route is, when there is no traffic on the wireless network, or when there is prolonged traffic, and what the traffic tendencies are, that may occur by excessive information transmission of smart meters to electric distribution companies.application/pdfspaUniversidad de la CostaINGE CUC - 2015https://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2https://revistascientificas.cuc.edu.co/ingecuc/article/view/509Red Eléctrica InteligenteMedición InteligenteAMIRed CelularÓptima PlaneaciónTráficoEnrutamiento ÓptimoSmart GridSmart MeteringAMICellular NetworkOptimal PlanningTrafficOptimal RoutingÓptima planeación de redes celulares para la infraestructura de medición inteligente en zonas rurales y remotasOptimal planning for cellular networks for smart metering infrastructure in rural and remote areasArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articleJournal articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85Inge CucR. F. Arritt and R. C. Dugan, “Distribution System Analysis and the Future Smart Grid,” IEEE Trans. Ind. Appl., vol. 47, no. 6, pp. 2343–2350, Nov. 2011. DOI: 10.1109/REPCON.2011.5756725J. Kim, S. Cho, and H. Shin, “Advanced Power Distribution System Con fi guration for Smart Grid,” IEEE Trans. Smart Grid, vol. 4, no. 1, pp. 353–358, 2013. DOI: 10.1109/TSG.2012.2233771C. Selva, K. Srinivas, G. Ayyappan, and M. Venkatachala, “Advanced Metering Infrastructure for Smart Grid Applications,” Recent Trends Inf. Technol. (ICRTIT), 2012 Int. Conf. IEEE, pp. 145–150, 2012. DOI: 10.1109/ICRTIT.2012.6206777S. SAydjari and V. Varadharajan, “The Smarter Grid,” Secur. Privacy, IEEE, vol. 8, no. 1, pp. 60 – 63, 2010. DOI: 10.1109/MSP.2010.52L. Chun-hao and N. Ansari, “CONSUMER : A Novel Hybrid Intrusion Detection System for Distribution Networks in Smart Grid,” IEEE Trans. Emerg. Top. Comput., vol. 1, no. 1, pp. 33 – 44, 2013. DOI: 10.1109/TETC.2013.2274043E. Inga and J. Inga, “Wireless Communications and Virtual Operator for Residential Electric Metering,” 12th Lat. Am. Caribb. Conf. Eng. Technol., pp. 1–9, 2014.B. Karimi and V. Namboodiri, “On the Capacity of a Wireless Backhaul for the Distribution Level of the Smart Grid,” Syst. Journal, IEEE, vol. 8, no. 2, pp. 521–532, 2014. DOI: 10.1109/JSYST.2013.2260701E. Inga, R. Hincapie, C. Suarez, and G. Arevalo, “Shortest path for optimal routing on Advanced Metering Infrastructure using cellular networks,” in Communications and Computing (COLCOM), 2015 IEEE Colombian Conference on, 2015, pp. 1 – 6.Z. Jia, J. Chen, and Y. Liao, “State estimation in distribution system considering effects of AMI data,” 2013 Proc. IEEE Southeastcon, pp. 1–6, Apr. 2013. DOI: 10.1109/SECON.2013.6567406R. R. Mohassel, A. Fung, F. Mohammadi, and K. Raahemifar, “Application of Advanced Metering Infrastructure in Smart Grids,” Control Autom. (MED), 2014 22nd Mediterr. Conf. IEEE, pp. 822 – 828, 2014. DOI: 10.1109/MED.2014.696147C. Lo and N. Ansari, “The Progressive Smart Grid System from Both Power and Communications Aspects,” Commun. Surv. Tutorials, IEEE, vol. 14, no. 3, pp. 799–821, 2012. DOI: 10.1109/SURV.2011.072811.00089P. Kulkarni, S. Gormus, Z. Fan, and F. Ramos, “AMI Mesh Networks—A Practical Solution and Its Performance Evaluation,” IEEE Trans. Smart Grid, vol. 3, no. 3, pp. 1469–1481, Sep. 2012. DOI: 10.1109/TSG.2012.2205023E. Hossain, Z. Han, and H. V. Poor, Smart Grid communication and networking, First edit. United Stated of America: Cambridge University Press, 2012, p. 481.H. Sui and W.-J. Lee, “An AMI based measurement and control system in smart distribution grid,” 2011 IEEE Ind. Commer. Power Syst. Tech. Conf., pp. 1–5, May 2011. DOI: 10.1109/ICPS.2011.5890876C. Andres and C. John, The Advanced Smart Grid Edge Power Driving Sustainability, First Edit. 2011, p. 268.M. R. Souryal and N. Golmie, “Analysis of advanced metering over a Wide Area Cellular Network,” 2011 IEEE Int. Conf. Smart Grid Commun., pp. 102–107, Oct. 2011. DOI: 10.1109/SmartGridComm.2011.6102299B. Saint, “Rural Distribution System Planning using Smart Grid Technologies,” Rural Electr. Power Conf. 2009. REPC ’09. IEEE, no. 09, pp. 0–8, 2009. DOI: 10.1109/REPCON.2009.4919421S. Li, J. Huang, and S. Member, “Dynamic Profit Maximization of Cognitive Mobile Virtual Network Operator,” IEEE Trans. Mob. Comput., vol. 13, no. 3, pp. 526–540, 2014. DOI: 10.1109/TMC.2013.10M. Gupta, S. Gupta, and T. Thakur, “Design and impact of wireless AMI for distribution utilities,” 2013 Annu. IEEE India Conf., pp. 1–6, Dec. 2013. DOI: 10.1109/INDCON.2013.6726103H. Li, S. Gong, L. Lai, Z. Han, S. Member, R. C. Qiu, and D. Yang, “Efficient and Secure Wireless Communications for Advanced Metering Infrastructure in Smart Grids,” IEEE Trans. Smart Grid, vol. 3, no. 3, pp. 1540–1551, 2012. DOI: 10.1109/TSG.2012.2203156A. Peralta-Sevilla, E. Inga, R. Cumbal, and R. Hincapie, “Optimum deployment of FiWi Networks using wireless sensors based on Universal Data Aggregation Points,” in Communications and Computing (COLCOM), 2015 IEEE Colombian Conference on, 2015, pp. 1 – 6. DOI: 10.1109/ColComCon.2015.7152079I. E. Reid and H. A. Stevens, Smart Meters and the Smart Grid: Privacy and Cybersecurity Considerations, First edit. Nova Science Publishers, Incorporated, 2012, p. 153.S. Cespedes, A. A. Cardenas, and T. Iwao, “Comparison of Data Forwarding Mechanisms for AMI networks,” Innov. Smart Grid Technol. (ISGT), 2012 IEEE PES, pp. 1 – 8, 2012. DOI: 10.1109/ISGT.2012.6175683C. Scordino and G. Lipari, “A Resource Reservation Algorithm for Power-Aware Scheduling of Periodic and Aperiodic Real-Time Tasks,” Comput. IEEE Trans., vol. 55, no. 12, pp. 1509 – 1522, 2006. DOI: 10.1109/TC.2006.190L. Duan, J. Huang, and B. Shou, “Cognitive Mobile Virtual Network Operator : Investment and Pricing with Supply Uncertainty,” INFOCOM, 2010 Proc. IEEE, pp. 1 – 9, 2010. DOI: 10.1109/INFCOM.2010.5462146Z. Fan and R. Zhang, “Spectrum allocation and medium access in cognitive radio wireless networks,” 2009 Eur. Wirel. Conf. IEEE, pp. 90–95, May 2009. DOI: 10.1109/EW.2009.5357757L. Mastroeni and M. Naldi, “Spectrum reservation options for Mobile Virtual Network Operators,” IEEE 6th EURO-NGI Conf. Next Gener. Internet, vol. 13, p. 15, Jun. 2010. DOI: 10.1109/NGI.2010.5534477E. Inga, G. Arévalo, and R. Hincapié, “Optimal Deployment of Cellular Networks for Advanced Measurement Infrastructure in Smart Grid,” 2014 IEEE Colomb. Conf. Commun. Comput., no. 1The 2014 IEEE Colombian Conference on Communications and Computing, p. 6, 2014. DOI: 10.1109/ColComCon.2014.6860421A. D. Dabbagh, R. Ratasuk, and A. Ghosh, “On UMTS-LTE Physical Uplink Shared and Control Channels,” Veh. Technol. Conf. 2008. VTC 2008-Fall. 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