Araştırma Makalesi
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Efficient Monitoring and Control System for Hybrid Smart Grids Using Fuzzy Logic and IOT

Yıl 2020, Cilt: 4 Sayı: 1, 93 - 102, 30.06.2020

Öz

Smart grids are electric grids that are composed of multiple power sources and devices connected to each other to provide better reliability in power generation and power management, modern developments of the smart grid aim at either improving the control of power sources and loads connected to the smart grid by developing a specialized software/hardware, or by improving the communication between the components of the smart grid and the central control. In this paper we aim at improving both sides of the smart grid system (communication and control), we propose a fuzzy logic based controller for renewable energy and fossil fuel sources in a smart grid and an internet of things based monitoring system which oversees the state of the smart grid, faults that occur in the smart grid , and how the fuzzy controller overcomes those faults, all in which provide an extra layer of support to the smart grid.

Teşekkür

thank you for your efforts

Kaynakça

  • Alamri,A. 2018. Energy Management with a World-Wide Adaptive Thermostat Using Fuzzy Inference System. IEEE Access 6, 33489–502.
  • Alaqeel, T.A., and Suryanarayanan,S. 2018. A Fuzzy Analytic Hierarchy Process Algorithm to Prioritize Smart Grid Technologies for the Saudi Electricity Infrastructure. Sustainable Energy Grids and Networks 13, 122–33.
  • Alnasser,A., and Sun,H. 2017. A Fuzzy Logic Trust Model for Secure Routing in Smart Grid Networks. IEEE Access 5(c), 17896–903.
  • Gope, P., and Sikdar,B. 2019. Privacy-Aware Authenticated Key Agreement Scheme for Secure Smart Grid Communication. IEEE Transactions on Smart Grid 10(4), 3953–62.
  • Gorgel, P., Sertbas, A., Kilic,N., Ucan, O.N., Osman, O. 2009. Mammographic Mass Classification Using Wavelet Based Support Vector Machine. Istanbul University - Journal of Electrical and Electronics Engineering 9(1), 867–75.
  • Gorgel, P., Sertbaş,A., Kilic,N., Ucan, O.N. 2013. Mammographical Mass Detection and Classification Using Local Seed Region Growing-Spherical Wavelet Transform (LSRG-SWT) Hybrid Scheme. Computers in Biology and Medicine 43(6), 765–74.
  • Gumus, E., Kilic, N., Sertbas,A., and Ucan, O.N. 2010. Evaluation of Face Recognition Techniques Using PCA, Wavelets and SVM. Expert Systems with Applications 37(9), 6404–8.
  • Khalid, R., Javaid,N., Rahim,M.H., Aslam,S., and Sher,A. 2019. Fuzzy Energy Management Controller and Scheduler for Smart Homes. Sustainable Computing: Informatics and Systems 21, 103–18.
  • Macedo, M. N. Q., Galo, J. J. M., Almeida, L. A. L., and Lima. A. C. C. 2016. Methodology for the Calculation of the Factor of Priority for Smart Grid Implantation Using Fuzzy Logic. International Journal of Electrical Power and Energy Systems 78, 563–68.
  • Mansiri, K., Sukchai,S., and Sirisamphanwong,C. 2018. Fuzzy Control for Smart Pv-Battery System Management to Stabilize Grid Voltage of 22 Kv Distribution System in Thailand. Energies 11(7).
  • Molina, A., Ponce,P., Reyes,G.E.B., and Soriano,L.A. 2019. Learning Perceptions of Smart Grid Class with Laboratory for Undergraduate Students. International Journal on Interactive Design and Manufacturing 13(4), 1423–39.
  • Osman, O., Ozekes,S., and Ucan.O.N. 2007. Lung Nodule Diagnosis Using 3D Template Matching. Computers in Biology and Medicine 37(8), 1167–72.
  • Panda, M. 2017. Intelligent Data Analysis for Sustainable Smart Grids Using Hybrid Classification by Genetic Algorithm Based Discretization. Intelligent Decision Technologies 11(2), 137–51.
  • Radhakrishnan, B.M., Srinivasan,D., and Mehta,R. 2016. Fuzzy-Based Multi-Agent System for Distributed Energy Management in Smart Grids. International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems 24(5), 781–803.
  • Riaz,M.H., Riaz, M.T., Khan,M.A.,Khan,L. 2018. Energy Management and Switching Control of PHEV Charging Stations in a Hybrid Smart Micro-Grid System. Electronics (Switzerland) 7(9).
  • Rocha-Osorio, C. M., Solís-Chaves, J. S., Casella, I.R.S., Capovilla,C.E., Puma, J. L. A., and Filho, A. J. S. 2017. GPRS/EGPRS Standards Applied to DTC of a DFIG Using Fuzzy – PI Controllers. International Journal of Electrical Power and Energy Systems 93, 365–73.
  • Simões, M. G., and Bubshait,A. 2019. Frequency Support of Smart Grid Using Fuzzy Logic-Based Controller for Wind Energy Systems. Energies 12(8).
  • Soares, J., Borges,N., Ghazvini, M.A.F., Vale,Z., and Oliveira, P.B.M. 2016. Scenario Generation for Electric Vehicles’ Uncertain Behavior in a Smart City Environment. Energy 111, 664–75.
  • Soetedjo, A., Nakhoda,Y.I., and Saleh,C. 2018. Embedded Fuzzy Logic Controller and Wireless Communication for Home Energy Management Systems. Electronics (Switzerland) 7(9).
  • Tiar, M., Achour B., Drid,S., Abdeddaim,S., Sellali,M., and Medjmadj, S. 2019. Fault-Tolerant Control of a Smart PV-Grid Hybrid System. IET Renewable Power Generation 13(13), 2451–61.
  • Tsao, Y.C., Thanh, V. V., and Lu, J. C. 2019. Multiobjective Robust Fuzzy Stochastic Approach for Sustainable Smart Grid Design. Energy 176, 929–39.
  • Velusamy, D., and Pugalendhi, G.K. 2019. Fuzzy Integrated Bayesian Dempster–Shafer Theory to Defend Cross-Layer Heterogeneity Attacks in Communication Network of Smart Grid. Information Sciences 479, 542–66.
  • Wu, J., Ota,K., Dong,M., Li,J., and Wang, H. 2016. Big Data Analysis-Based Security Situational Awareness for Smart Grid. IEEE Transactions on Big Data 4(3), 408–17.
  • Zeng, B., Wei,X., Sun,B., Qiu,F., Zhang,J., and Quan,X. 2020. Assessing Capacity Credit of Demand Response in Smart Distribution Grids with Behavior-Driven Modeling Framework. International Journal of Electrical Power and Energy Systems 118(July 2019), 105745.
  • Zhao, H., and Li,N. 2016. Performance Evaluation for Sustainability of Strong Smart Grid by Using Stochastic AHP and Fuzzy TOPSIS Methods. Sustainability (Switzerland) 8(2), 1–22.
  • Zhou, K., Yang,C., and Shen,J. 2017. Discovering Residential Electricity Consumption Patterns through Smart-Meter Data Mining: A Case Study from China. Utilities Policy 44, 73–84.

Bulanık Mantık ve IOT Kullanarak Hibrit Akıllı Şebekeler İçin Verimli İzleme ve Kontrol Sistemi

Yıl 2020, Cilt: 4 Sayı: 1, 93 - 102, 30.06.2020

Öz

Akıllı şebekeler, güç üretimi ve güç yönetiminde daha iyi güvenilirlik sağlamak için birbirine bağlı birden fazla güç kaynağı ve cihazdan oluşan elektrik şebekeleridir; akıllı şebekenin modern gelişmeleri, güç kaynaklarının kontrolünü ve akıllıya bağlı yükleri kontrol etmeyi amaçlamaktadır. özel bir yazılım / donanım geliştirerek veya akıllı şebekenin bileşenleri ile merkezi kontrol arasındaki iletişimi geliştirerek. Bu makalede akıllı şebeke sisteminin (iletişim ve kontrol) her iki tarafını da geliştirmeyi hedefliyoruz, akıllı bir şebekede yenilenebilir enerji ve fosil yakıt kaynakları ve devleti denetleyen şeylere dayalı bir izleme sistemi için bulanık mantık tabanlı bir kontrolör öneriyoruz akıllı şebekeye, akıllı şebekede meydana gelen arızalara ve bulanık denetleyicinin bu hataların üstesinden nasıl geldiği, bunların hepsi de akıllı şebekeye ekstra destek katmanı sağlar.

Kaynakça

  • Alamri,A. 2018. Energy Management with a World-Wide Adaptive Thermostat Using Fuzzy Inference System. IEEE Access 6, 33489–502.
  • Alaqeel, T.A., and Suryanarayanan,S. 2018. A Fuzzy Analytic Hierarchy Process Algorithm to Prioritize Smart Grid Technologies for the Saudi Electricity Infrastructure. Sustainable Energy Grids and Networks 13, 122–33.
  • Alnasser,A., and Sun,H. 2017. A Fuzzy Logic Trust Model for Secure Routing in Smart Grid Networks. IEEE Access 5(c), 17896–903.
  • Gope, P., and Sikdar,B. 2019. Privacy-Aware Authenticated Key Agreement Scheme for Secure Smart Grid Communication. IEEE Transactions on Smart Grid 10(4), 3953–62.
  • Gorgel, P., Sertbas, A., Kilic,N., Ucan, O.N., Osman, O. 2009. Mammographic Mass Classification Using Wavelet Based Support Vector Machine. Istanbul University - Journal of Electrical and Electronics Engineering 9(1), 867–75.
  • Gorgel, P., Sertbaş,A., Kilic,N., Ucan, O.N. 2013. Mammographical Mass Detection and Classification Using Local Seed Region Growing-Spherical Wavelet Transform (LSRG-SWT) Hybrid Scheme. Computers in Biology and Medicine 43(6), 765–74.
  • Gumus, E., Kilic, N., Sertbas,A., and Ucan, O.N. 2010. Evaluation of Face Recognition Techniques Using PCA, Wavelets and SVM. Expert Systems with Applications 37(9), 6404–8.
  • Khalid, R., Javaid,N., Rahim,M.H., Aslam,S., and Sher,A. 2019. Fuzzy Energy Management Controller and Scheduler for Smart Homes. Sustainable Computing: Informatics and Systems 21, 103–18.
  • Macedo, M. N. Q., Galo, J. J. M., Almeida, L. A. L., and Lima. A. C. C. 2016. Methodology for the Calculation of the Factor of Priority for Smart Grid Implantation Using Fuzzy Logic. International Journal of Electrical Power and Energy Systems 78, 563–68.
  • Mansiri, K., Sukchai,S., and Sirisamphanwong,C. 2018. Fuzzy Control for Smart Pv-Battery System Management to Stabilize Grid Voltage of 22 Kv Distribution System in Thailand. Energies 11(7).
  • Molina, A., Ponce,P., Reyes,G.E.B., and Soriano,L.A. 2019. Learning Perceptions of Smart Grid Class with Laboratory for Undergraduate Students. International Journal on Interactive Design and Manufacturing 13(4), 1423–39.
  • Osman, O., Ozekes,S., and Ucan.O.N. 2007. Lung Nodule Diagnosis Using 3D Template Matching. Computers in Biology and Medicine 37(8), 1167–72.
  • Panda, M. 2017. Intelligent Data Analysis for Sustainable Smart Grids Using Hybrid Classification by Genetic Algorithm Based Discretization. Intelligent Decision Technologies 11(2), 137–51.
  • Radhakrishnan, B.M., Srinivasan,D., and Mehta,R. 2016. Fuzzy-Based Multi-Agent System for Distributed Energy Management in Smart Grids. International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems 24(5), 781–803.
  • Riaz,M.H., Riaz, M.T., Khan,M.A.,Khan,L. 2018. Energy Management and Switching Control of PHEV Charging Stations in a Hybrid Smart Micro-Grid System. Electronics (Switzerland) 7(9).
  • Rocha-Osorio, C. M., Solís-Chaves, J. S., Casella, I.R.S., Capovilla,C.E., Puma, J. L. A., and Filho, A. J. S. 2017. GPRS/EGPRS Standards Applied to DTC of a DFIG Using Fuzzy – PI Controllers. International Journal of Electrical Power and Energy Systems 93, 365–73.
  • Simões, M. G., and Bubshait,A. 2019. Frequency Support of Smart Grid Using Fuzzy Logic-Based Controller for Wind Energy Systems. Energies 12(8).
  • Soares, J., Borges,N., Ghazvini, M.A.F., Vale,Z., and Oliveira, P.B.M. 2016. Scenario Generation for Electric Vehicles’ Uncertain Behavior in a Smart City Environment. Energy 111, 664–75.
  • Soetedjo, A., Nakhoda,Y.I., and Saleh,C. 2018. Embedded Fuzzy Logic Controller and Wireless Communication for Home Energy Management Systems. Electronics (Switzerland) 7(9).
  • Tiar, M., Achour B., Drid,S., Abdeddaim,S., Sellali,M., and Medjmadj, S. 2019. Fault-Tolerant Control of a Smart PV-Grid Hybrid System. IET Renewable Power Generation 13(13), 2451–61.
  • Tsao, Y.C., Thanh, V. V., and Lu, J. C. 2019. Multiobjective Robust Fuzzy Stochastic Approach for Sustainable Smart Grid Design. Energy 176, 929–39.
  • Velusamy, D., and Pugalendhi, G.K. 2019. Fuzzy Integrated Bayesian Dempster–Shafer Theory to Defend Cross-Layer Heterogeneity Attacks in Communication Network of Smart Grid. Information Sciences 479, 542–66.
  • Wu, J., Ota,K., Dong,M., Li,J., and Wang, H. 2016. Big Data Analysis-Based Security Situational Awareness for Smart Grid. IEEE Transactions on Big Data 4(3), 408–17.
  • Zeng, B., Wei,X., Sun,B., Qiu,F., Zhang,J., and Quan,X. 2020. Assessing Capacity Credit of Demand Response in Smart Distribution Grids with Behavior-Driven Modeling Framework. International Journal of Electrical Power and Energy Systems 118(July 2019), 105745.
  • Zhao, H., and Li,N. 2016. Performance Evaluation for Sustainability of Strong Smart Grid by Using Stochastic AHP and Fuzzy TOPSIS Methods. Sustainability (Switzerland) 8(2), 1–22.
  • Zhou, K., Yang,C., and Shen,J. 2017. Discovering Residential Electricity Consumption Patterns through Smart-Meter Data Mining: A Case Study from China. Utilities Policy 44, 73–84.
Toplam 26 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Elektrik Mühendisliği
Bölüm Araştırma Makalesi
Yazarlar

Teiseer Alzubaidi 0000-0003-0187-794X

Osman Nuri Uçan 0000-0002-4100-0045

Yayımlanma Tarihi 30 Haziran 2020
Gönderilme Tarihi 8 Nisan 2020
Kabul Tarihi 25 Mayıs 2020
Yayımlandığı Sayı Yıl 2020 Cilt: 4 Sayı: 1

Kaynak Göster

APA Alzubaidi, T., & Uçan, O. N. (2020). Efficient Monitoring and Control System for Hybrid Smart Grids Using Fuzzy Logic and IOT. AURUM Journal of Engineering Systems and Architecture, 4(1), 93-102.