Yıl 2019, Cilt 15 , Sayı 4, Sayfalar 337 - 342 2019-12-30

IoT and Cloud Based Remote Monitoring of Wind Turbine

Batın Demircan [1] , Ersin Akyüz [2]



With the industry 4.0 revolution, the concept of industrial production will be reshaped with information technologies and will rapidly shift to a new production understanding. The Internet of things and cloud computing will play a vital role as the most important elements of this transformation. In this study, parameters that are crucial for the performance evaluation of a small power wind turbine are measured. Measurements can be used to evaluate the performance of the system and to avoid errors in the system. In the designed system, basic parameters such as wind speed, air temperature, battery voltage and battery current were measured and recorded through datalogger. These measurements were sent to the Microsoft Azure cloud computing system and recorded here. At the same time, visualization with the aid of the cloud system was performed and viewed in real time on the web via Microsoft Power BI platform.

Internet of things, Wind turbine, Cloud computing, Industry 4.0
  • 1. Zabala Innovation Consulting, Plan for Dissemination of Results, https://www.romeoproject.eu/wp-content/uploads/2017/09/D9.1ROMEO_Dissemination_Plan.pdf (accessed August 27, 2018).
  • 2. Annual combined onshore and offshore wind energy statistics, Wind in power 2017 Annual combined onshore and offshore wind energy Statistics. https://windeurope.org/wp-content/uploads/files/about-wind/statistics/WindEurope-Annual-Statistics-2017.pdf (accessed 14.03.2019).
  • 3. Horn, G, Eliassen, F, Salvatore, Venticinque, S, Martino, BD, Bücher, M, Wood, L. 2016. An Architecture for Using Commodity Devices and Smart Phones in Health Systems. IEEE Workshop on ICT solutions for eHealth, 255-260.
  • 4. Internet of Things in 2020: Roadmap for the future. Internet of Things 27, https://docbox.etsi.org/erm/Open/CERP%2020080609-10/Internet-of-Things_in_2020_EC-EPoSS_Workshop_Report_2008_v1-1.pdf (accessed 14.03.2019).
  • 5. Fioccola, GB, Sommese R, Tufano, I, Canonico, R, Ventre G. 2016. Polluino: An Efficient Cloud-based Management of IoT Devices for Air Quality Monitoring. Control. Instrumentation, Energy & Communication (CIEC).
  • 6. Manzano, S, Ortiz, RP, Guevara, D, Villacorta, A. 2014. An overview of remote monitoring PV Systems: Acquisition, Storage processing and publication of Real Time Data based on cloud computing. 4th International Workshop on Integration of Solar Power into Power Systems.
  • 7. Zhao, JC, Zhang, JF, Feng, Y, Guo, J. The Study and Application of the IoT Technology in Agriculture. 3rd IEEE International Conference on Computer Science and Information Technology (ICCSIT), Chengdu, China, 2010, pp462-465.
  • 8. Illic, MD, Xie, L, Khan, UA. 2010. Modeling of Future Cyber–Physical Energy Systems for Distributed Sensing and Control. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 825-838.
  • 9. Jayavardhana, G, Rajkumar B, Slaven, M, Marimuthu, P. 2013. Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29, 1645-1660.
  • 10. Vuppala, SK, Kumar, HSK. Service Applications Exploiting the Internet of Things. SRII Global Conference, San Jose, CA, USA, 2014, pp195-202.
  • 11. Internet of Things, Research and Innovation to Market Development. River Publishers Series in Communication, 2014
  • 12. Atzori, L, Iera, A, Morabito, G. 2010. The Internet of Things: A survey. Computer Networks, 2787-2805.
  • 13. Jamali, MS, Kumar, P, Khan, UA. Internet of Things: Architecture& Integration with Other Networks. First International Conference on Modern Communication & Computing Technologies (MCCT-14), Nawabshah, Pakistan, 2014, pp 88.
  • 14. Bin, S,Yuan, L,Xiayoi, W. Research on Data mining Models for the Internet of Things. International Conference on Image Analysis and Signal Processing, Zhejiang, China, 2010, pp127-132.
  • 15. Wang, Q, Gao, J. 2012. Research and application of risk and condition-based maintenance task optimization technology in an oil transfer station. Journal of Loss Prevention in the Process Industries, 6, 1018-1027.
  • 16. Rannat, K, Lotus, M, Meriste, M, Preden, J. 2012. On dynamic models for wind farms as systems of systems. 7th International Conference on System of Systems Engineering (SoSE), 113-118.
  • 17. Sajid, A., Abbas, H, Saleem, K. 2016. Cloud-Assisted IoT-Based SCADA Systems Security: A Review of the State of the Art and Future Challenges. IEEE Access, 1375 – 1384.
  • 18. Moness, M, Moustafa, AM. 2016. A Survey of Cyber-Physical Advances and Challenges of Wind Energy Conversion Systems: Prospects for Internet of Energy. IEEE Internet of Thinks Journal, 3, 2.
  • 19. Karnouskos, S, Colombo, AW. Architecting the next generation of service-based SCADA/DCS system of systems. IECON 2011 - 37th Annual Conference of the IEEE Industrial Electronics Society, Melbourne, VIC, Australia, 2011, pp359-364.
  • 20. Community Research and Development Information Service, Reliable OM decision tools and strategies for high LCoE reduction on Offshore wind, https://cordis.europa.eu/project/rcn/210289_en.html (accessed August 09, 2018).
  • 21. Sujatha, K, Deepalakshmi, B, Cao, SQ. 2018. Optimal condition monitoring of wind turbines using intelligent image processing and Internet of Things. International Journal of Renewable Energy Technology, 9, 1-2.
  • 22. Kalyanraj, D, Lenin, S, Sabareswar, S. Wind Turbine Monitoring and Control Systems Using Internet of Things. 21st Century Energy Needs - Materials, Systems and Applications (ICTFCEN), Kharagpur, India, 2016.
  • 23. Microsoft Corporation, What is Azure?. https://azure.microsoft.com/en-us/ (accessed July 15, 2018).
  • 24. Deneysan, YE-1040 Rüzgâr Türbini Eğitim Seti, http://deneysan.com/tr/urunler/yenilenebilir-enerji/ye-1040-ruzgar-turbini-egitim-seti/119 (accessed June 02, 2018).
  • 25. Akyuz, E, Oktay, Z, Dincer, E. 2012. Performance investigation of hydrogen production from a hybrid wind-PV system. International Journal of Hydrogen Energy, 37, 21, 15841-16758.
  • 26. Raspberry Pi Community, What is a Raspberry Pi?,https://www.raspberrypi.org/help/faqs/#introWhatIs (accessed July 15,2018).
  • 27. CR1000 Measurement and Control Datalogger, https://www.campbellsci.com/cr1000 (accessed June 06,2018).
  • 28. IBM’s Emerging Technology Services, Node-RED Flow-based programming for the Internet of Things, https://nodered.org (accessed June 03, 2018).
  • 29. OASIS, A Comparison of AMQP and MQTT, https://lists.oasis-open.org/archives/amqp/201202/msg00086/StormMQ_WhitePaper_-_A_Comparison_of_AMQP_and_MQTT.pdf (accessed April 07, 2018).
Birincil Dil en
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Orcid: 0000-0002-0765-458X
Yazar: Batın Demircan
Kurum: İŞBİR Elektrik San. A.Ş.
Ülke: Turkey


Orcid: 0000-0001-9786-3221
Yazar: Ersin Akyüz (Sorumlu Yazar)
Kurum: BALIKESİR ÜNİVERSİTESİ, BALIKESİR MESLEK YÜKSEKOKULU
Ülke: Turkey


Tarihler

Yayımlanma Tarihi : 30 Aralık 2019

Bibtex @araştırma makalesi { cbayarfbe540812, journal = {Celal Bayar University Journal of Science}, issn = {1305-130X}, eissn = {1305-1385}, address = {}, publisher = {Celal Bayar Üniversitesi}, year = {2019}, volume = {15}, pages = {337 - 342}, doi = {10.18466/cbayarfbe.540812}, title = {IoT and Cloud Based Remote Monitoring of Wind Turbine}, key = {cite}, author = {Demircan, Batın and Akyüz, Ersin} }
APA Demircan, B , Akyüz, E . (2019). IoT and Cloud Based Remote Monitoring of Wind Turbine. Celal Bayar University Journal of Science , 15 (4) , 337-342 . DOI: 10.18466/cbayarfbe.540812
MLA Demircan, B , Akyüz, E . "IoT and Cloud Based Remote Monitoring of Wind Turbine". Celal Bayar University Journal of Science 15 (2019 ): 337-342 <https://dergipark.org.tr/tr/pub/cbayarfbe/issue/50875/540812>
Chicago Demircan, B , Akyüz, E . "IoT and Cloud Based Remote Monitoring of Wind Turbine". Celal Bayar University Journal of Science 15 (2019 ): 337-342
RIS TY - JOUR T1 - IoT and Cloud Based Remote Monitoring of Wind Turbine AU - Batın Demircan , Ersin Akyüz Y1 - 2019 PY - 2019 N1 - doi: 10.18466/cbayarfbe.540812 DO - 10.18466/cbayarfbe.540812 T2 - Celal Bayar University Journal of Science JF - Journal JO - JOR SP - 337 EP - 342 VL - 15 IS - 4 SN - 1305-130X-1305-1385 M3 - doi: 10.18466/cbayarfbe.540812 UR - https://doi.org/10.18466/cbayarfbe.540812 Y2 - 2019 ER -
EndNote %0 Celal Bayar Üniversitesi Fen Bilimleri Dergisi IoT and Cloud Based Remote Monitoring of Wind Turbine %A Batın Demircan , Ersin Akyüz %T IoT and Cloud Based Remote Monitoring of Wind Turbine %D 2019 %J Celal Bayar University Journal of Science %P 1305-130X-1305-1385 %V 15 %N 4 %R doi: 10.18466/cbayarfbe.540812 %U 10.18466/cbayarfbe.540812
ISNAD Demircan, Batın , Akyüz, Ersin . "IoT and Cloud Based Remote Monitoring of Wind Turbine". Celal Bayar University Journal of Science 15 / 4 (Aralık 2020): 337-342 . https://doi.org/10.18466/cbayarfbe.540812
AMA Demircan B , Akyüz E . IoT and Cloud Based Remote Monitoring of Wind Turbine. Celal Bayar Univ J Sci. 2019; 15(4): 337-342.
Vancouver Demircan B , Akyüz E . IoT and Cloud Based Remote Monitoring of Wind Turbine. Celal Bayar University Journal of Science. 2019; 15(4): 342-337.