Sensorless Voltage Estimation for Total Harmonic Distortion Calculation using Artificial Neural Networks in Microgrids


Adineh B., Habibi M. R., AKPOLAT A. N., Blaabjerg F.

IEEE Transactions on Circuits and Systems II: Express Briefs, cilt.68, ss.2583-2587, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 68
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1109/tcsii.2021.3059410
  • Dergi Adı: IEEE Transactions on Circuits and Systems II: Express Briefs
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.2583-2587
  • Anahtar Kelimeler: Microgrids, Voltage control, Voltage measurement, Estimation, Sensors, Neurons, Data centers, Total harmonic distortion (THD), microgrids, artificial neural networks, voltage estimation, power electronics
  • Marmara Üniversitesi Adresli: Evet

Özet

IEEEIn this work, a sensorless voltage estimation approach for total harmonic distortion (THD) calculation is proposed to reduce number of voltage sensors in the microgrids. The intelligent proposed method provides a cost-effective and reliable voltage estimation and THD calculation of the desired bus in the multi-bus microgrid based on the artificial neural networks (ANNs). In the proposed method, the output voltage and current of distributed generation units along with the voltage of the desired bus are used to train the ANN offline. The trained ANN is then used to estimate the voltage and calculate both harmonic components, and THD online at the desired bus. The Simulation results show that the proposed approach can effectively estimate the voltage and calculate THD of buses in the multi-bus islanded microgrids.