Multi-agent System for Management of Data from Electrical Smart Meters

Автор: Yazid Hambally Yacouba, Amadou Diabagaté, Abdou Maiga, Adama Coulibaly

Журнал: International Journal of Information Technology and Computer Science @ijitcs

Статья в выпуске: 1 Vol. 13, 2021 года.

Бесплатный доступ

The smart meter can process sensor data in a residential grid. These sensors transmit different parameters or measurement data (index, power, temperature, fluctuation of voltage and electricity, etc.) to the smart meter. All of these measurement data can come in different ways at the smart meter. The sensors transmit each measurement data to the smart meter. In addition, the collection of this data to a central system is a significant concern to ensure data integrity and protect the privacy of residents. The complexity of these data management also lies in their volume, frequency, and scheduling. This work presents a scheduling and a collection mechanism in private power consumption data between both sensors and smart meters on one hand and between smart meters and the central data collection system on other hand. We have found several approaches to intelligent meter data management in scientific researches. We propose another approach in response to this concern for the scheduling and collection of measurement data to a central system from residential areas of sensors’ network connected to smart meters. This work is also an example of a link between data collection and data scheduling in intelligent information management, transmission, and protection. We also propose a modeling of the measurement objects of smart grid and highlight the changes made to these objects throughout the process of data processing. It should be noted that this smart grid system consists of three main active systems namely sensors, smart meters and central system. In addition to these three systems, there are other systems that communicate with the smart meters and the central system. We have identified three implementation models for the smart metering system. We also present an intelligent architecture based on multi-agent systems for the smart grid. Most current electricity management systems are not adapted to the new challenges imposed by social and economic development in Africa. The objectives of this study are to initiate the design of a smart grid system for the management of electricity data.

Еще

Sensor, residential smart grid, smart meter, measurement data, collection mechanism, power consumption data, central data collection system, multi-agent system

Короткий адрес: https://sciup.org/15017478

IDR: 15017478 | DOI: 10.5815/ijitcs.2021.01.02

Список литературы Multi-agent System for Management of Data from Electrical Smart Meters

Fadi Shrouf, Giovanni Miragliotta. Energy management based on Internet of Things: practices and framework for adoption in production management. Journal of Cleaner Production, Volume 100, 1 August 2015, Pages 235-246
Alexander Martin Tureczek and Per Sieverts Nielsen. Structured Literature Review of Electricity, Consumption Classification Using Smart Meter Data. Energies 2017, 10(5), 584; https://doi.org/10.3390/en10050584.
Athila Quaresma Santos, Renato Machado Monaro, Denis Vinicius Coury, Mario Oleskovicz. A new real-time multi-agent system for under frequency load shedding in a smart grid context. Electric Power Systems Research 174 (2019) 105851.
Madeline Martinez-Pabon, Timothy Eveleigh, Bereket Tanju. Optimizing residential energy management using an autonomous scheduler system. Expert Systems With Applications 96 (2018) 373–387.
Markus Mäsker, Lars Nagel, AndréBrinkmann, Foad Lotfifar, Matthew Johnson. Smart Grid-aware scheduling in data centres. Computer Communications 96 (2016) 73–85.
Ilze Laicane, Dagnija Blumberga, Andra Blumberga, Marika Rosa. Reducing household electricity consumption through demand side management: the role of home appliance scheduling and peak load reduction. Energy Procedia 72 ( 2015 ) 222 – 229.
Joshua D. Rhodes, Charles R. Upshaw, Chioke B. Harris, Colin M. Meehan, David A. Walling, Paul A. Navrátil, Ariane L. Beck, Kazunori Nagasawa, Robert L. Fares, Wesley J. Cole, Harsha Kumar, Roger D. Duncan, Chris L. Holcomb, Thomas F. Edgar, Alexis Kwasinski, Michael E. Webber. Experimental and data collection methods for a large-scale smart grid deployment: Methods and first results. Energy 65 (2014) 462-471.
Xi Fang, Student Member, IEEE, Satyajayant Misra, Member, IEEE, Guoliang Xue, Fellow, IEEE, and Dejun Yang, Student Member, IEEE. Smart grid—the new and improved power grid: A survey. IEEE Communications Surveys & Tutorials, Vol. 14, No. 4, Fourth quarter 2012.
Nicola Bui ; Angelo P. Castellani ; Paolo Casari ; Michele Zorzi. The internet of energy: a web-enabled smart grid system. IEEE Network ( Volume: 26 , Issue: 4 , July-August 2012 ).
Hongxun Hui, Yi Ding, Qingxin Shi, Fangxing Li, Yonghua Song, Jinyue Yan. 5G network-based Internet of Things for demand response in smart grid: A survey on application potential. Applied Energy, Volume 257, 1 January 2020, 113972.
Alireza Zakariazadeh, Shahram Jadid, Pierluigi Siano. Multi-objective scheduling of electric vehicles in smart distribution System. Energy Conversion and Management 79 (2014) 43–53.
M.M. Eissa, A.A. Ali, K.M. Abdel-Latif, A.F. Al-Kady. Emergency frequency control by using heavy thermal conditioning loads in commercial buildings at smart grids. Electric Power Systems Research 173 (2019) 202–213.
Raghu K. Ganti, Fan Ye, and Hui Lei, IBM T. J. Watson Research Center. Mobile Crowdsensing: Current State and Future Challenges. IEEE Communications Magazine • November 2011.
Tanveer Ahmad, Hongcai Zhang, Biao Yan. A review on renewable energy and electricity requirement forecasting models for smart grid and buildings. Sustainable Cities and Society, Volume 55, April 2020, 102052.
Rabiya Khalid, Nadeem Javaid, Fahad A. Al-zahrani, Khursheed Aurangzeb, Emad-ul-Haq Qazi and Tehreem Ashfaq. Electricity Load and Price Forecasting Using Jaya-Long Short Term Memory (JLSTM) in Smart Grids. Entropy 2020, 22(1), 10; https://doi.org/10.3390/e22010010.
Géremi Gilson Dranka, Paula Ferreira. Towards a smart grid power system in Brazil: Challenges and opportunities. Energy Policy, Volume 136, January 2020, 111033.
Gerwin Evers, Maryse M.H.Chappin. Knowledge sharing in smart grid pilot projects. Energy Policy, Volume 143, August 2020, 111577.
M. Ourahou, W. Ayrir, B. EL Hassouni, A. Haddi. Review on mart grid control and reliability in presence of renewable energies: challenges and prospects. Mathematics and Computers in Simulation, Volume 167, January 2020, Pages 19-31.
Dileep G. A survey on smart grid technologies and applications. Renewable Energy, Volume 146, February 2020, Pages 2589-2625.
Mostafa Farhadi Moghadam, Morteza Nikooghadam, Amir Hossein Mohajerzadeh, Behzad Movali. A lightweight key management protocol for secure communication in smart grids. Electric Power Systems Research Volume 178, January 2020, 106024.
Monica Alonso, Hortensia Amaris, Daniel Alcala and Diana M. Florez R. Smart Sensors for Smart Grid Reliability. Sensors (ISSN 1424-8220; CODEN: SENSC9).
Muhammed Zekeriya Gunduz, Resul Das. Cyber-security on smart grid: Threats and potential solutions. Computer Networks, Volume 169, 14 March 2020, 107094.
Ameema Zainab, Shady S. Refaat, Haitham Abu-Rub and Othmane Bouhali. Distributed Computing for Smart Meter Data Management for Electrical Utility Applications. 2020 Cybernetics & Informatics (K&I), DOI: 10.1109/KI48306.2020.9039899, IEEE
Bassirou Diène, Joel J.P.C.Rodrigues, Ousmane Diallo, EL Hadji Malick Ndoye, Valery V. Korotaev. Data management techniques for Internet of Things. Mechanical Systems and Signal Processing, Volume 138, April 2020, 106564.
Ayesha Afzaal , Faria Kanwal , Ayesha Haider Ali , Komal Bashir , and Fatima Anjum. Agent-Based Energy Consumption Scheduling for Smart Grids: An Auction-Theoretic Approach. 13 April 2020, DOI: 10.1109/ACCESS.2020.2987770, IEEE.
Aditya Sundararajan, Alexander S. Hernandez, Arif I. Sarwat. Adapting Big Data Standards, Maturity Models to Smart Grid Distributed Generation: Critical Review. IET Smart Grid, 2020, ISSN 1751-8644.
Sibo Nan, Ming Zhou, Gengyin Li. Optimal residential community demand response scheduling in smart grid. Applied Energy, Volume 210, 15 January 2018, Pages 1280-1289.
Mohammad Tasdighi, Hassan Ghasemi, and Ashkan Rahimi-Kian. Residential Microgrid Scheduling Based on Smart Meters Data and Temperature Dependent Thermal Load Modeling. IEEE Transactions on Smart Grid ( Volume: 5 , Issue: 1 , Jan. 2014 ).
D. Strickland, M.A. Varnosfederani, J. Scott, P. Quintela, A. Duran, R. Bravery, A. Corliss, K. Ashworth, S. Blois-Brooke. A review of community electrical energy systems. Proceedings of the IEEE International Conference on Renewable Energy Research and Applications, IEEE (2016), pp. 49-54.
Luc F.M. van Summeren, Anna J. Wieczorek Gunter J.T. Bombaerts Geert P.J. Verbong. Community energy meets smart grids: Reviewing goals, structure, and roles in Virtual Power Plants in Ireland, Belgium and the Netherlands. Energy Research & Social Science Volume 63, May 2020, 101415.
Derek Machalek, Aaron Young, Landen Blackburn, Pratt Rogers, Kody M.Powell. Mine operations as a smart grid resource: Leveraging excess process storage capacity to better enable renewable energy sources. Minerals Engineering Volume 145, 1 January 2020, 106103.
Marie Chan, Daniel Estève, Christophe Escriba, Eric Campo. A review of smart homes—Present state and future challenges. Computer methods and programs in biomedicine 91 (2008) 55–81.
Yi Ren, Dongming Fan, Qiang Feng, Zili Wang, Bo Sun, Dezhen Yang. Agent-based restoration approach for reliability with load balancing on smart grids. Applied Energy 249 (2019) 46–57.
D. Kolokotsa et al. A roadmap towards intelligent net zero-and positive-energy buildings. Solar Energy xxx (2010) xxx–xxx. R. Stephen Carr, Julius N. Dalzell, J. Fred Holmes, John M. Hunt. Oregon Graduate Institute of Science and Technology. 1984-09-14.
Mehdi Ahrarinouri ; Mohammad Rastegar ; Ali Reza Seifi. Multi-Agent Reinforcement Learning for Energy Management in Residential Buildings. IEEE, 28 February 2020, 10.1109/TII.2020.2977104.
Dimitrios Thomas, Olivier Deblecker, Christos S. Ioakimidis. Optimal operation of an energy management system for a grid-connected smart building considering photovoltaics’ uncertainty and stochastic electric vehicles’ driving schedule. Applied Energy 210 (2018) 1188–1206.
Gungor V.C., Sahin Dilan, Kocak Taskin, Ergut S., Cecati C., Buccella C., Hancke G.P., A survey on smart grid potential applications and communication requirements, IEEE Transactions on Industrial Informatics, vol. 9, no. 1, pp. 28–42 (2013).
Alfredo Garro, Max Mühlhäuser, Andrea Tundis, Matteo Baldoni, Cristina Baroglio, Federico Bergenti, Paolo Torroni. Intelligent Agents: Multi-Agent Systems. Encyclopedia of Bioinformatics and Computational Biology, Volume 1, 2019, Pages 315-320.
Khadija Tazi, Fouad Mohamed Abbou & Farid Abdi. Multi-agent system for microgrids: design, optimization and performance. Applied Energy Volume 259, 1 February 2020, 114140.
Xu Xu, Youwei Jia, Yan Xu, Zhao Xu, Songjian Chai, Chun Sing Lai. A Multi-agent Reinforcement Learning based Datadriven Method for Home Energy Management. IEEE, 04 February 2020, 10.1109/TSG.2020.2971427.
Linyun Xiong, Penghan Li, Ziqiang Wang, Jie Wan. Multi-agent based multi objective renewable energy management for diversified community power consumers. Applied Energy Volume 259, 1 February 2020, 114140.
Ibrahim Abaker Targio Hashem, Victor Chang, Nor Badrul Anuar, Kayode Adewole Ibrar Yaqoob, Abdullah Gani, Ejaz Ahmed, Haruna Chiroma. The role of big data in a smart city. International Journal of Information Management 36 (2016) 748–758.
Fengming Ran, Dian-ce Gao, Xu Zhang, Shuyue Chen. A virtual sensor based self-adjusting control for HVAC fast demand response in commercial buildings towards smart grid applications. Applied Energy Volume 269, 1 July 2020, 115103.
Alberto Fernández-Isabel, Rubén Fuentes-Fernández, Isaac Martín de Diego. Modeling multi-agent systems to simulate sensor-based Smart Roads. Simulation Modelling Practice and Theory Volume 99, February 2020, 101994.
Soo Wan Yen, Stella Morris, Morris A.G. Ezra, Tang Jun Huat. Effect of smart meter data collection frequency in an early detection ofshorter-duration voltage anomalies in smart grids. Electrical Power and Energy Systems 109 (2019) 1–8.
Geerten van de Kaa, Jafar Rezaei, Behnam Taebi, Ibo van de Poel & Abhilash Kizhakenath. How to Weigh Values in Value Sensitive Design: A Best Worst Method Approach for the Case of Smart Metering. Science and Engineering Ethics volume 26, pages 475–494(2020).
Szewczyk, Robert Osterweil, Eric Polastre, Joseph et al. Habitat monitoring with sensor networks. Center for Embedded Network Sensing, 47 (6), 2004-05-05.
Atefeh Alirezazadeh, Masoud Rashidinejad, Amir Abdollahi, Peyman Afzali, Alireza Bakhshai. A new flexible model for generation scheduling in a smart grid. Energy Volume 191, 15 January 2020, 116438.
Nipendra Kayastha, Dusit Niyato, Ekram Hossain and Zhu Han. Smart grid sensor data collection, communication, and networking: a tutorial. 23 July 2012 in Wiley Online Library.
Mohamed Elgamal, Nikolay Korovkin, Akram Elmitwally, Zhe Chen. Robust multi-agent system for efficient online energy management and security enforcement in a grid-connected microgrid with hybrid resources. IET Generation, Transmission & Distribution, Volume 14, Issue 9, 11 May 2020, p. 1726 – 1737.
Bin Zhou, WentaoLi, KaWingChan, YijiaCao, YonghongKuang, XiLiu, Xiong Wang. Smart home energy management systems: Concept, configurations, and scheduling strategies. Renewable and Sustainable Energy Reviews 61 (2016) 30–40.
Melike Erol-Kantarci, Member, IEEE, and Hussein T. Mouftah, Fellow, IEEE. Energy-Efﬁcient Information and Communication Infrastructures in the Smart Grid: A Survey on Interactions and Open Issues. IEEE Transactions on Industrial Informatics, Vol. 12, No. 1, February 2016. IEEE Communication surveys & Tutorials, Vol. 17, No. 1, First Quarter 2015.
Murat Kuzlu, Manisa Pipattanasomporn, Saifur Rahman. Communication network requirements for major smart grid applications in HAN, NAN, and WAN. Computer Networks 67 (2014) 74–88.
Saber Talari, Miadreza Shafie-Khah, Pierluigi Siano, Vincenzo Loia, Aurelio Tommasetti and João P. S. Cataloão. A review of smart cities based on the internet of thongs concept. Energies 2017, 10, 421.

Еще

Статья научная