Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2019, Cilt: 23 Sayı: 1, 35 - 42, 01.02.2019
https://doi.org/10.16984/saufenbilder.407323

Öz

Kaynakça

  • Dugan, R.C., Mcgranaghan, M.F. Santoso, S. and Beaty, H.W., 2002. Electrical power systems quality, McGraw-Hill, New York.
  • Bollen, M.H.J. and Gu, I.Y.H., 2006, Signal processing of power quality disturbances, John Wiley&Sons, New York.
  • Khokhar, S., Zin, A. M., Mokhtar, A. S., & Ismail, N. A. M. (2014, October). MATLAB/Simulink based modeling and simulation of power quality disturbances. In Energy Conversion (CENCON), 2014 IEEE Conference on (pp. 445-450). IEEE.
  • Haykin, S. 2008. “Neural networks and learning machines”, Pearson, 3rd edition.
  • Burges, C J.C. 1998. “A tutorial on support vector machines for pattern recognition”, Data Mining and Knowledge Discovery, 2, 121-167.
  • Silva, K.M., Souza, B.A., Brito, N.S.D. 2006. “Fault detection and classification in transmission lines based on wavelet transform and ANN”, IEEE Trans Power Deliv, 21, 2058–63.
  • Dash, P.K., Samantaray, S.R., Panda, G. 2007. “Fault classification and section identification of an advanced series-compensated transmission line using support vector machine”, IEEE Trans Power Deliv, 22, 67–73.
  • Valtierra-Rodriguez, M., de Jesus Romero-Troncoso, R., Osornio-Rios, R. A., & Garcia-Perez, A. (2014). Detection and classification of single and combined power quality disturbances using neural networks. IEEE Transactions on Industrial Electronics, 61(5), 2473-2482.
  • Rodriguez-Guerrero, M. A., Carranza-Lopez-Padilla, R., Osornio-Rios, R. A., & Romero-Troncoso, R. D. J. (2017). A novel methodology for modeling waveforms for power quality disturbance analysis. Electric Power Systems Research, 143, 14-24.
  • Simić, M., Kokolanski, Z., Denić, D., Dimcev, V., Živanović, D., & Taskovski, D. (2017). Design and evaluation of computer-based electrical power quality signal generator. Measurement, 107, 77-88.
  • Mohanty, S. R., Ray, P. K., Kishor, N., & Panigrahi, B. K. (2013). Classification of disturbances in hybrid DG system using modular PNN and SVM. International Journal of Electrical Power & Energy Systems, 44(1), 764-777.
  • Zhang, M., Li, K., & Hu, Y. (2011). A real-time classification method of power quality disturbances. Electric power systems Research, 81(2), 660-666.
  • IEEE Std. 1547, IEEE standard for interconnecting distributed resources with electric power systems, 2015.
  • IEEE Std 519, IEEE recommended practices and requirements for harmonic control in electrical power systems, 2014.
  • IEEE Std 1159, IEEE Recommended Practice for Monitoring Electric Power Quality, 2009.
  • Electromagnetic Compatibility (EMC)- Part 3-3, Limits – Limitation of voltage changes, voltage fluctuations and flicker in public low-voltage supply systems, for equipment with rated current ≤ 16 A per phase and not subject to conditional connection, IEC 61000-3-3, 2013.
  • Regina Lamedica, Alberto Prudenzi, Enrico Tironi, Dario Zaninelli – Analysis of Harmonics Distortion Limits in IEC and IEEE Standards – Electrical Power Quality and Utilisation Journal, vol. 5, iss. 2, sept. 1999, pp. 47-52.
  • M. H. Bollen, Understanding power quality problems vol. 3: IEEE press New York, 2000.
  • Bayrak. G., Cebeci. M. 2014. Grid connected fuel cell and PV hybrid power generating system design with Matlab Simulink. International Journal of Hydrogen Energy. 39(1):8803-8812.
  • Bayrak, G., Yilmaz, A., “Design and Performance Assessment of A Grid-Connected PV System for Residential Power Generation”, 7th International 100% Renewable Energy Conference, pp: 62-67,18-20 Mayıs 2017, İstanbul, TURKEY
  • Bayrak, G., Kabalci, E., “Implementation of a new remote islanding detection method for wind–solar hybrid power plants”, Renewable and Sustainable Energy Reviews, 58:1-15, 2016.

Assesment of Power Quality Disturbances For Grid Integration of PV Power Plants

Yıl 2019, Cilt: 23 Sayı: 1, 35 - 42, 01.02.2019
https://doi.org/10.16984/saufenbilder.407323

Öz

Power Quality problems, which have become an
important consumer issue in recent years, are defined as changes in voltage,
current, or frequency in the power system. Among the factors affecting energy
quality in grid-connected PV systems are island mode operation, current and
voltage harmonics, transients, flicker, interruption, DC offset, notches,
frequency changes, voltage sag / swell, voltage imbalances in the system and
power factor. Because of the power quality problems, several transmission and
distribution losses can occur due to both the consumers and the generators.
Also, the integration of PV power plants to the main grid will cause several
power quality problems, and a reliable operation of the grid with PV power
plants is a significant issue for distributed generation. Thus, the first step
in preparing a reliable algorithm for detecting power quality events occurring
in the current grid is to model a power system in which power quality
impairments can be analyzed. In this work, the power quality disturbances that
occur in the low-voltage grid that is fed through both the main grid and the
grid-connected PV system are modeled and investigated. Developed electric power
distribution model includes simulation of voltage sags caused by three phase
fault, transformer energization and asynchronous motor switching, voltage
swells caused by three phase fault, transients due to large capacitor bank
switching, harmonics and notches caused by the load connected via the power
converter. Examination of the power quality disturbances with simulation
clearly revealed the resulting waveforms, the response of the electrical power
system to the fault conditions. Another advantage of the realized study is that
the developed model can be used to measure the performance of the PV connected
distributed generation system in fault detection and classification studies.

Kaynakça

  • Dugan, R.C., Mcgranaghan, M.F. Santoso, S. and Beaty, H.W., 2002. Electrical power systems quality, McGraw-Hill, New York.
  • Bollen, M.H.J. and Gu, I.Y.H., 2006, Signal processing of power quality disturbances, John Wiley&Sons, New York.
  • Khokhar, S., Zin, A. M., Mokhtar, A. S., & Ismail, N. A. M. (2014, October). MATLAB/Simulink based modeling and simulation of power quality disturbances. In Energy Conversion (CENCON), 2014 IEEE Conference on (pp. 445-450). IEEE.
  • Haykin, S. 2008. “Neural networks and learning machines”, Pearson, 3rd edition.
  • Burges, C J.C. 1998. “A tutorial on support vector machines for pattern recognition”, Data Mining and Knowledge Discovery, 2, 121-167.
  • Silva, K.M., Souza, B.A., Brito, N.S.D. 2006. “Fault detection and classification in transmission lines based on wavelet transform and ANN”, IEEE Trans Power Deliv, 21, 2058–63.
  • Dash, P.K., Samantaray, S.R., Panda, G. 2007. “Fault classification and section identification of an advanced series-compensated transmission line using support vector machine”, IEEE Trans Power Deliv, 22, 67–73.
  • Valtierra-Rodriguez, M., de Jesus Romero-Troncoso, R., Osornio-Rios, R. A., & Garcia-Perez, A. (2014). Detection and classification of single and combined power quality disturbances using neural networks. IEEE Transactions on Industrial Electronics, 61(5), 2473-2482.
  • Rodriguez-Guerrero, M. A., Carranza-Lopez-Padilla, R., Osornio-Rios, R. A., & Romero-Troncoso, R. D. J. (2017). A novel methodology for modeling waveforms for power quality disturbance analysis. Electric Power Systems Research, 143, 14-24.
  • Simić, M., Kokolanski, Z., Denić, D., Dimcev, V., Živanović, D., & Taskovski, D. (2017). Design and evaluation of computer-based electrical power quality signal generator. Measurement, 107, 77-88.
  • Mohanty, S. R., Ray, P. K., Kishor, N., & Panigrahi, B. K. (2013). Classification of disturbances in hybrid DG system using modular PNN and SVM. International Journal of Electrical Power & Energy Systems, 44(1), 764-777.
  • Zhang, M., Li, K., & Hu, Y. (2011). A real-time classification method of power quality disturbances. Electric power systems Research, 81(2), 660-666.
  • IEEE Std. 1547, IEEE standard for interconnecting distributed resources with electric power systems, 2015.
  • IEEE Std 519, IEEE recommended practices and requirements for harmonic control in electrical power systems, 2014.
  • IEEE Std 1159, IEEE Recommended Practice for Monitoring Electric Power Quality, 2009.
  • Electromagnetic Compatibility (EMC)- Part 3-3, Limits – Limitation of voltage changes, voltage fluctuations and flicker in public low-voltage supply systems, for equipment with rated current ≤ 16 A per phase and not subject to conditional connection, IEC 61000-3-3, 2013.
  • Regina Lamedica, Alberto Prudenzi, Enrico Tironi, Dario Zaninelli – Analysis of Harmonics Distortion Limits in IEC and IEEE Standards – Electrical Power Quality and Utilisation Journal, vol. 5, iss. 2, sept. 1999, pp. 47-52.
  • M. H. Bollen, Understanding power quality problems vol. 3: IEEE press New York, 2000.
  • Bayrak. G., Cebeci. M. 2014. Grid connected fuel cell and PV hybrid power generating system design with Matlab Simulink. International Journal of Hydrogen Energy. 39(1):8803-8812.
  • Bayrak, G., Yilmaz, A., “Design and Performance Assessment of A Grid-Connected PV System for Residential Power Generation”, 7th International 100% Renewable Energy Conference, pp: 62-67,18-20 Mayıs 2017, İstanbul, TURKEY
  • Bayrak, G., Kabalci, E., “Implementation of a new remote islanding detection method for wind–solar hybrid power plants”, Renewable and Sustainable Energy Reviews, 58:1-15, 2016.
Toplam 21 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Elektrik Mühendisliği
Bölüm Araştırma Makalesi
Yazarlar

Gökay Bayrak 0000-0002-5136-0829

Alper Yılmaz 0000-0003-3736-3668

Yayımlanma Tarihi 1 Şubat 2019
Gönderilme Tarihi 27 Mart 2018
Kabul Tarihi 20 Temmuz 2018
Yayımlandığı Sayı Yıl 2019 Cilt: 23 Sayı: 1

Kaynak Göster

APA Bayrak, G., & Yılmaz, A. (2019). Assesment of Power Quality Disturbances For Grid Integration of PV Power Plants. Sakarya University Journal of Science, 23(1), 35-42. https://doi.org/10.16984/saufenbilder.407323
AMA Bayrak G, Yılmaz A. Assesment of Power Quality Disturbances For Grid Integration of PV Power Plants. SAUJS. Şubat 2019;23(1):35-42. doi:10.16984/saufenbilder.407323
Chicago Bayrak, Gökay, ve Alper Yılmaz. “Assesment of Power Quality Disturbances For Grid Integration of PV Power Plants”. Sakarya University Journal of Science 23, sy. 1 (Şubat 2019): 35-42. https://doi.org/10.16984/saufenbilder.407323.
EndNote Bayrak G, Yılmaz A (01 Şubat 2019) Assesment of Power Quality Disturbances For Grid Integration of PV Power Plants. Sakarya University Journal of Science 23 1 35–42.
IEEE G. Bayrak ve A. Yılmaz, “Assesment of Power Quality Disturbances For Grid Integration of PV Power Plants”, SAUJS, c. 23, sy. 1, ss. 35–42, 2019, doi: 10.16984/saufenbilder.407323.
ISNAD Bayrak, Gökay - Yılmaz, Alper. “Assesment of Power Quality Disturbances For Grid Integration of PV Power Plants”. Sakarya University Journal of Science 23/1 (Şubat 2019), 35-42. https://doi.org/10.16984/saufenbilder.407323.
JAMA Bayrak G, Yılmaz A. Assesment of Power Quality Disturbances For Grid Integration of PV Power Plants. SAUJS. 2019;23:35–42.
MLA Bayrak, Gökay ve Alper Yılmaz. “Assesment of Power Quality Disturbances For Grid Integration of PV Power Plants”. Sakarya University Journal of Science, c. 23, sy. 1, 2019, ss. 35-42, doi:10.16984/saufenbilder.407323.
Vancouver Bayrak G, Yılmaz A. Assesment of Power Quality Disturbances For Grid Integration of PV Power Plants. SAUJS. 2019;23(1):35-42.

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