IOT Based Intelligent Energy Monitoring of Grid connected Hybrid systems and controlling of Loads using PLC

Nowadays IOT becoming popularize in all the application especially in the power system network for data monitoring from the Hybrid power distribution system. Because of easy adaptability of IOT technology, it find its place in data monitoring for the remote system and data can also be logged in the...

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Autores:
Thulasingam, Muthukumaran
P, Ajay D Vimal Raj.
Krishnamoorthy, Muruagapermual
Tipo de recurso:
Article of journal
Fecha de publicación:
2024
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/13553
Acceso en línea:
https://doi.org/10.32397/tesea.vol5.n2.641
Palabra clave:
IoT systems
PLC
Multifunction meter
Mqtt Protocol
Demand Management
Rights
openAccess
License
Muthukumaran Thulasingam, Ajay D Vimal Raj. P, Muruagapermual Krishnamoorthy - 2024
id UTB2_801559edcddf9d896a4e77713da256b8
oai_identifier_str oai:repositorio.utb.edu.co:20.500.12585/13553
network_acronym_str UTB2
network_name_str Repositorio Institucional UTB
repository_id_str
dc.title.spa.fl_str_mv IOT Based Intelligent Energy Monitoring of Grid connected Hybrid systems and controlling of Loads using PLC
dc.title.translated.spa.fl_str_mv IOT Based Intelligent Energy Monitoring of Grid connected Hybrid systems and controlling of Loads using PLC
title IOT Based Intelligent Energy Monitoring of Grid connected Hybrid systems and controlling of Loads using PLC
spellingShingle IOT Based Intelligent Energy Monitoring of Grid connected Hybrid systems and controlling of Loads using PLC
IoT systems
PLC
Multifunction meter
Mqtt Protocol
Demand Management
title_short IOT Based Intelligent Energy Monitoring of Grid connected Hybrid systems and controlling of Loads using PLC
title_full IOT Based Intelligent Energy Monitoring of Grid connected Hybrid systems and controlling of Loads using PLC
title_fullStr IOT Based Intelligent Energy Monitoring of Grid connected Hybrid systems and controlling of Loads using PLC
title_full_unstemmed IOT Based Intelligent Energy Monitoring of Grid connected Hybrid systems and controlling of Loads using PLC
title_sort IOT Based Intelligent Energy Monitoring of Grid connected Hybrid systems and controlling of Loads using PLC
dc.creator.fl_str_mv Thulasingam, Muthukumaran
P, Ajay D Vimal Raj.
Krishnamoorthy, Muruagapermual
dc.contributor.author.eng.fl_str_mv Thulasingam, Muthukumaran
P, Ajay D Vimal Raj.
Krishnamoorthy, Muruagapermual
dc.subject.eng.fl_str_mv IoT systems
PLC
Multifunction meter
Mqtt Protocol
Demand Management
topic IoT systems
PLC
Multifunction meter
Mqtt Protocol
Demand Management
description Nowadays IOT becoming popularize in all the application especially in the power system network for data monitoring from the Hybrid power distribution system. Because of easy adaptability of IOT technology, it find its place in data monitoring for the remote system and data can also be logged in the cloud server for analysis of the system under surveillance. By having data enabled IOT system, which will make the complete system smarter in terms of monitoring and analysis of the performance of the power distribution network. In these research paper, concept IOT technology for data monitoring of grid connected Hybrid system consist of PV source for the typical educational institute was developed and implemented in the campus. Apart from the data monitoring, controlling of the critical loads connected to this hybrid system was developed using Programmable Logic Controller (PLC). The MyQtt based cloud server was used to store the data pushed from the IOT device and user interactive mobile Application was developed using MIT inventor to monitor the data in the mobile itself, the command from the Mobile app was given to the PLC to control the loads. The energy data from the Multi-function energy meter (MFM) is pushed to PLC through gateway of Raspberry Pi. In this paper, Raspberry PI was used as IOT device and ILC 131 ETH PLC was used to control the loads. Performance of IOT device along with PLC was monitored for 3 months and results obtained were satisfactory.
publishDate 2024
dc.date.accessioned.none.fl_str_mv 2024-12-24 00:00:00
dc.date.available.none.fl_str_mv 2024-12-24 00:00:00
dc.date.issued.none.fl_str_mv 2024-12-24
dc.type.spa.fl_str_mv Artículo de revista
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dc.type.driver.eng.fl_str_mv info:eu-repo/semantics/article
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dc.type.local.eng.fl_str_mv Journal article
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dc.identifier.url.none.fl_str_mv https://doi.org/10.32397/tesea.vol5.n2.641
dc.identifier.doi.none.fl_str_mv 10.32397/tesea.vol5.n2.641
dc.identifier.eissn.none.fl_str_mv 2745-0120
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identifier_str_mv 10.32397/tesea.vol5.n2.641
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dc.language.iso.eng.fl_str_mv eng
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dc.relation.references.eng.fl_str_mv MohammedSamdani Shaik, Dipam Shah, Raghuram Chetty, and Rahul R Marathe. A lorawan based open source iot solution for monitoring rural electrification policy. January 2020. [2] José Miguel Paredes-Parra, Antonio Javier García-Sánchez, Antonio Mateo-Aroca, and Angel Molina-Garcia. An alternative internet-of-things solution based on lora for pv power plants: Data monitoring and management. Energies, 12(5):881, March 2019. [3] Ascensión López-Vargas, Manuel Fuentes, and Marta Vivar. Current challenges for the advanced mass scale monitoring of solar home systems: A review. Renewable Energy, 163:2098–2114, January 2021. [4] J.E. Shuda, A.J. Rix, and M.J. Booysen. Towards module-level performance and health monitoring of solar pv plants using lora wireless sensor networks. 2018 IEEE PES/IAS PowerAfrica, June 2018. [5] Neeraj Kumar Gupta, Aditya Kumar Singh, Ashish D. Thombre, and Kirti Pal. Smart solar energy management to power computer lab in rural areas. November 2018. [6] Congduc Pham, Abdur Rahim, and Philippe Cousin. Low-cost, long-range open iot for smarter rural african villages. September 2016. [7] P. Papageorgas, D. Piromalis, K. Antonakoglou, G. Vokas, D. Tseles, and K.G. Arvanitis. Smart solar panels: In-situ monitoring of photovoltaic panels based on wired and wireless sensor networks. Energy Procedia, 36:535–545, January 2013. [8] Venkat Subramanian Arumuga Perumal, Krishnamoorthy Baskaran, and Suleman Khalid Rai. Implementation of effective and low-cost building monitoring system(bms) using raspberry pi. Energy Procedia, 143:179–185, December 2017. [9] Mani Dheeraj Mudaliar and N. Sivakumar. Iot based real time energy monitoring system using raspberry pi. Internet of Things, 12:100292, December 2020. [10] K COKAFOR,G.Ononiwu, Udechukwu Precious, and A. C Godis. Development of arduino based iot metering system for on-demand energy monitoring. 2017. [11] Sanket Thakare, Akshay Shriyan, Vikas Thale, Prakash Yasarp, and Keerthi Unni. Implementation of an energy monitoring and control device based on iot. December 2016. [12] Swati Arora, Aditi Thakur, Abinash Singh, Sahil Rana, and Dhawan Singh. A review on smart energy meters and their market trends. November 2022. [13] J. Bennilo Fernandes, Sangeetha Dp, G. Padmapriya, and K. Sekar. Iot based energy assistive meter to analyse the electricity usage in commercial and household uses via wirelessly in a cloud network. December 2022. [14] Michael Opoku Agyeman, Zainab Al-Waisi, and Igla Hoxha. Design and implementation of an iot-based energy monitoring system for managing smart homes. June 2019. [15] Amam Hossain Bagdadee, Li Zhang, and Md. Saddam Hossain Remus. A brief review of the iot-based energy management system in the smart industry. Advances in Intelligent Systems and Computing, page 443–459, January 2020. [16] L. Niranjan, Husna Tabassum, B. Sreekantha, T. Pushpa, and Mantri Gayatri. Design and Implementation of Smart Home Automation System Using the Proteus Design Tool, page 95–106. January 2023. [17] Wajdi Alhakami. Computational study of security risk evaluation in energy management and control systems based on a fuzzy mcdm method. Processes, 11(5):1366, April 2023. [18] None Jixuan Zheng, David Wenzhong Gao, and None Li Lin. Smart meters in smart grid: An overview. April 2013. [19] Souhaib Ben Taieb, Raphael Huser, Rob J. Hyndman, and Marc G. Genton. Forecasting uncertainty in electricity smart meter data by boosting additive quantile regression. IEEE Transactions on Smart Grid, 7(5):2448–2455, September 2016. [20] Julius Quarshie Azasoo, Eric Kuada, Kwame Osei Boateng, and Michael Opoku Agyeman. An algorithm for micro-load shedding in generation constrained electricity distribution network. June 2017. [21] P. Mathiyalagan, A. Shanmugapriya, and A. V. Geethu. Smart meter data analytics using r and hadoop. May 2017. [22] Tiefeng Zhang, Guangquan Zhang, Jie Lu, Xiaopu Feng, and Wanchun Yang. A new index and classification approach for load pattern analysis of large electricity customers. IEEE Transactions on Power Systems, 27(1):153–160, February 2012. [23] Giovanni Battista Gaggero, Mario Marchese, Aya Moheddine, and Fabio Patrone. A possible smart metering system evolution for rural and remote areas employing unmanned aerial vehicles and internet of things in smart grids. Sensors, 21(5):1627, February 2021. [24] Yasir Saleem, Noel Crespi, Mubashir Husain Rehmani, and Rebecca Copeland. Internet of things-aided smart grid: Technologies, architectures, applications, prototypes, and future research directions. IEEE Access, 7:62962–63003, January 2019. [25] Murugaperumal Krishnamoorthy, Md. Asif, Polamarasetty P. Kumar, Ramakrishna S. S. Nuvvula, Baseem Khan, and Ilhami Colak. A design and development of the smart forest alert monitoring system using iot. Journal of Sensors, 2023:1–12, February 2023. [26] Ilc 131 eth- controller- 2700973 | phoenix contact.
dc.relation.ispartofjournal.eng.fl_str_mv Transactions on Energy Systems and Engineering Applications
dc.relation.citationvolume.eng.fl_str_mv 5
dc.relation.citationstartpage.none.fl_str_mv 1
dc.relation.citationendpage.none.fl_str_mv 15
dc.relation.bitstream.none.fl_str_mv https://revistas.utb.edu.co/tesea/article/download/641/409
dc.relation.citationedition.eng.fl_str_mv Núm. 2 , Año 2024 : Transactions on Energy Systems and Engineering Applications
dc.relation.citationissue.eng.fl_str_mv 2
dc.rights.eng.fl_str_mv Muthukumaran Thulasingam, Ajay D Vimal Raj. P, Muruagapermual Krishnamoorthy - 2024
dc.rights.uri.eng.fl_str_mv https://creativecommons.org/licenses/by/4.0
dc.rights.accessrights.eng.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.creativecommons.eng.fl_str_mv This work is licensed under a Creative Commons Attribution 4.0 International License.
dc.rights.coar.eng.fl_str_mv http://purl.org/coar/access_right/c_abf2
rights_invalid_str_mv Muthukumaran Thulasingam, Ajay D Vimal Raj. P, Muruagapermual Krishnamoorthy - 2024
https://creativecommons.org/licenses/by/4.0
This work is licensed under a Creative Commons Attribution 4.0 International License.
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.mimetype.eng.fl_str_mv application/pdf
dc.publisher.eng.fl_str_mv Universidad Tecnológica de Bolívar
dc.source.eng.fl_str_mv https://revistas.utb.edu.co/tesea/article/view/641
institution Universidad Tecnológica de Bolívar
repository.name.fl_str_mv Repositorio Digital Universidad Tecnológica de Bolívar
repository.mail.fl_str_mv bdigital@metabiblioteca.com
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spelling Thulasingam, MuthukumaranP, Ajay D Vimal Raj.Krishnamoorthy, Muruagapermual2024-12-24 00:00:002024-12-24 00:00:002024-12-24Nowadays IOT becoming popularize in all the application especially in the power system network for data monitoring from the Hybrid power distribution system. Because of easy adaptability of IOT technology, it find its place in data monitoring for the remote system and data can also be logged in the cloud server for analysis of the system under surveillance. By having data enabled IOT system, which will make the complete system smarter in terms of monitoring and analysis of the performance of the power distribution network. In these research paper, concept IOT technology for data monitoring of grid connected Hybrid system consist of PV source for the typical educational institute was developed and implemented in the campus. Apart from the data monitoring, controlling of the critical loads connected to this hybrid system was developed using Programmable Logic Controller (PLC). The MyQtt based cloud server was used to store the data pushed from the IOT device and user interactive mobile Application was developed using MIT inventor to monitor the data in the mobile itself, the command from the Mobile app was given to the PLC to control the loads. The energy data from the Multi-function energy meter (MFM) is pushed to PLC through gateway of Raspberry Pi. In this paper, Raspberry PI was used as IOT device and ILC 131 ETH PLC was used to control the loads. Performance of IOT device along with PLC was monitored for 3 months and results obtained were satisfactory.application/pdfengUniversidad Tecnológica de BolívarMuthukumaran Thulasingam, Ajay D Vimal Raj. P, Muruagapermual Krishnamoorthy - 2024https://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessThis work is licensed under a Creative Commons Attribution 4.0 International License.http://purl.org/coar/access_right/c_abf2https://revistas.utb.edu.co/tesea/article/view/641IoT systemsPLCMultifunction meterMqtt ProtocolDemand ManagementIOT Based Intelligent Energy Monitoring of Grid connected Hybrid systems and controlling of Loads using PLCIOT Based Intelligent Energy Monitoring of Grid connected Hybrid systems and controlling of Loads using PLCArtículo de revistainfo:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Journal articleTextinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85https://doi.org/10.32397/tesea.vol5.n2.64110.32397/tesea.vol5.n2.6412745-0120MohammedSamdani Shaik, Dipam Shah, Raghuram Chetty, and Rahul R Marathe. A lorawan based open source iot solution for monitoring rural electrification policy. January 2020. [2] José Miguel Paredes-Parra, Antonio Javier García-Sánchez, Antonio Mateo-Aroca, and Angel Molina-Garcia. An alternative internet-of-things solution based on lora for pv power plants: Data monitoring and management. Energies, 12(5):881, March 2019. [3] Ascensión López-Vargas, Manuel Fuentes, and Marta Vivar. Current challenges for the advanced mass scale monitoring of solar home systems: A review. Renewable Energy, 163:2098–2114, January 2021. [4] J.E. Shuda, A.J. Rix, and M.J. Booysen. Towards module-level performance and health monitoring of solar pv plants using lora wireless sensor networks. 2018 IEEE PES/IAS PowerAfrica, June 2018. [5] Neeraj Kumar Gupta, Aditya Kumar Singh, Ashish D. Thombre, and Kirti Pal. Smart solar energy management to power computer lab in rural areas. November 2018. [6] Congduc Pham, Abdur Rahim, and Philippe Cousin. Low-cost, long-range open iot for smarter rural african villages. September 2016. [7] P. Papageorgas, D. Piromalis, K. Antonakoglou, G. Vokas, D. Tseles, and K.G. Arvanitis. Smart solar panels: In-situ monitoring of photovoltaic panels based on wired and wireless sensor networks. Energy Procedia, 36:535–545, January 2013. [8] Venkat Subramanian Arumuga Perumal, Krishnamoorthy Baskaran, and Suleman Khalid Rai. Implementation of effective and low-cost building monitoring system(bms) using raspberry pi. Energy Procedia, 143:179–185, December 2017. [9] Mani Dheeraj Mudaliar and N. Sivakumar. Iot based real time energy monitoring system using raspberry pi. Internet of Things, 12:100292, December 2020. [10] K COKAFOR,G.Ononiwu, Udechukwu Precious, and A. C Godis. Development of arduino based iot metering system for on-demand energy monitoring. 2017. [11] Sanket Thakare, Akshay Shriyan, Vikas Thale, Prakash Yasarp, and Keerthi Unni. Implementation of an energy monitoring and control device based on iot. December 2016. [12] Swati Arora, Aditi Thakur, Abinash Singh, Sahil Rana, and Dhawan Singh. A review on smart energy meters and their market trends. November 2022. [13] J. Bennilo Fernandes, Sangeetha Dp, G. Padmapriya, and K. Sekar. Iot based energy assistive meter to analyse the electricity usage in commercial and household uses via wirelessly in a cloud network. December 2022. [14] Michael Opoku Agyeman, Zainab Al-Waisi, and Igla Hoxha. Design and implementation of an iot-based energy monitoring system for managing smart homes. June 2019. [15] Amam Hossain Bagdadee, Li Zhang, and Md. Saddam Hossain Remus. A brief review of the iot-based energy management system in the smart industry. Advances in Intelligent Systems and Computing, page 443–459, January 2020. [16] L. Niranjan, Husna Tabassum, B. Sreekantha, T. Pushpa, and Mantri Gayatri. Design and Implementation of Smart Home Automation System Using the Proteus Design Tool, page 95–106. January 2023. [17] Wajdi Alhakami. Computational study of security risk evaluation in energy management and control systems based on a fuzzy mcdm method. Processes, 11(5):1366, April 2023. [18] None Jixuan Zheng, David Wenzhong Gao, and None Li Lin. Smart meters in smart grid: An overview. April 2013. [19] Souhaib Ben Taieb, Raphael Huser, Rob J. Hyndman, and Marc G. Genton. Forecasting uncertainty in electricity smart meter data by boosting additive quantile regression. IEEE Transactions on Smart Grid, 7(5):2448–2455, September 2016. [20] Julius Quarshie Azasoo, Eric Kuada, Kwame Osei Boateng, and Michael Opoku Agyeman. An algorithm for micro-load shedding in generation constrained electricity distribution network. June 2017. [21] P. Mathiyalagan, A. Shanmugapriya, and A. V. Geethu. Smart meter data analytics using r and hadoop. May 2017. [22] Tiefeng Zhang, Guangquan Zhang, Jie Lu, Xiaopu Feng, and Wanchun Yang. A new index and classification approach for load pattern analysis of large electricity customers. IEEE Transactions on Power Systems, 27(1):153–160, February 2012. [23] Giovanni Battista Gaggero, Mario Marchese, Aya Moheddine, and Fabio Patrone. A possible smart metering system evolution for rural and remote areas employing unmanned aerial vehicles and internet of things in smart grids. Sensors, 21(5):1627, February 2021. [24] Yasir Saleem, Noel Crespi, Mubashir Husain Rehmani, and Rebecca Copeland. Internet of things-aided smart grid: Technologies, architectures, applications, prototypes, and future research directions. IEEE Access, 7:62962–63003, January 2019. [25] Murugaperumal Krishnamoorthy, Md. Asif, Polamarasetty P. Kumar, Ramakrishna S. S. Nuvvula, Baseem Khan, and Ilhami Colak. A design and development of the smart forest alert monitoring system using iot. Journal of Sensors, 2023:1–12, February 2023. [26] Ilc 131 eth- controller- 2700973 | phoenix contact.Transactions on Energy Systems and Engineering Applications5115https://revistas.utb.edu.co/tesea/article/download/641/409Núm. 2 , Año 2024 : Transactions on Energy Systems and Engineering Applications220.500.12585/13553oai:repositorio.utb.edu.co:20.500.12585/135532025-09-16 09:15:15.9https://creativecommons.org/licenses/by/4.0Muthukumaran Thulasingam, Ajay D Vimal Raj. P, Muruagapermual Krishnamoorthy - 2024metadata.onlyhttps://repositorio.utb.edu.coRepositorio Digital Universidad Tecnológica de Bolívarbdigital@metabiblioteca.com

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