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Uyarlamalı Sinirsel Bulanık Çıkarım (ANFIS) Tabanlı Güneş Takip Sistemi

Year 2017, Volume: 17 Issue: 2, 546 - 554, 31.08.2017

Hayrettin Toylan Engin Hüner

Abstract

Fotovoltaik panellerin güç toplama verimliliğini artırmak için genellikle güneş takip sistemleri (GTS) ile entegre edilmelidir. Bu çalışmada, uyarlamalı sinirsel bulanık çıkarım uygulaması ile GTS sunulmuştur. GTS, zenit ve azimut açılarını kontrol eden iki motora sahip çift eksenli olarak tasarlanmıştır. Bu motorların hızının kontrol edilmesi için ANFIS’in tasarlanmasından sonra bulanık mantık kontrolörünün giriş-çıkış ilişkisini öğrenmek için yapay sinir ağı eğitilmiştir. Pozisyon hatası ve hatanın değişimi modellerin girişi olarak alınmıştır. Motora uygulanan gerilim modellerin çıkışı olarak alınmıştır. ANFIS modelde, deneysel verilerden doğrudan üretilen kurallar kümesine sahip yapay sinir ağının öğrenme yeteneği ile bulanık çıkarım modeli birleştirilir. Sonuç olarak, elde edilen sonuçlar GTS için amaçlanan kontrol yaklaşımının doğru cevap ve takip etme etkinliğini doğrular.

Keywords

Güneş Enerjisi” “ANFIS” “Fotovoltaik; “Güneş Takip” “Bulanık Mantık ”

References

  • Abdallah, S. and Nijmeh, S., 2004. Two axes sun tracking system with PLC control. Energy Conversion and Management, 45, 1931–1939.
  • Alata, M., Al-Nimr, M.A. and Qaroush, Y., 2005. Developing a multipurpose sun tracking system using fuzzy control. Energy Conversion and Management, 46, 1229–1245.
  • Batayneh, W., Owais, A. and Nairoukh, M., 2013. An intelligent fuzzy based tracking controller for a dual-axis solar PV system. Automation in Construction, 29, 100–106.
  • Buragohain, M. and Mahanta, C., 2008. A novel approach for ANFIS modelling based on full factorial design. Applied Soft Computing, 8, 609-625.
  • Chin, C.S, Babu, A. and McBride, W., 2011. Design, modeling and testing of a standalone single axis active solar tracker using MATLAB/Simulink. Renewable Energy, 36, 3075-3090.
  • Clifford, M.J. and Eastwood, D., 2004. Design of a novel passive solar tracker. Solar Energy, 77, 269–280.
  • Cooper, P.I., 1969. The absorption of solar radiation in solar stills. Solar Energy, 12, 333–346.
  • Daraban, S., Petreus, D. and Morel, C., 2014. A novel MPPT (maximum power point tracking) algorithm based on a modified genetic algorithm specialized on tracking the global maximum power point in photovoltaic systems affected by partial shading. Energy, 74, 374-388.
  • Eke, R. and Senturk, A., 2012. Performance comparison of a double-axis sun tracking versus fixed PV system. Solar Energy, 86, 2665–2672.
  • Eldin, S.A.S., Abd-Elhady, M.S. and Kandil, H.A., 2016. Feasibility of solar tracking systems for PV panels in hot and cold regions. Renewable Energy, 85, 228-233.
  • Guo, M., Wang, Z., Zhang, J., Sun, F. and Zhang, X., 2011. Accurate altitude–azimuth tracking angle formulas for a heliostat with mirror–pivot offset and other fixed geometrical errors. Solar Energy, 85, 1091–1100.
  • Jang, J-S.R., 1993. ANFIS: Adaptive-Network-Based Fuzzy Inference System. IEEE transactions on systems, man, and cybernetics, 23. Li, D.H.W., Cheung, G.H.W. and Lam J.C., 2005. Analysis of the operational performance and efficiency characteristic for photovoltaic system in Hong Kong. Energy Conversion and Management, 46, 1107–1118. Oelhafen, P. and Schuler, A., 2005. Nanostructured materials for solar energy conversion. Solar Energy, 79, 110–121.
  • Pradhan, R. and Subudhi, B., 2015. Design and real-time implementation of a new auto-tuned adaptive MPPT control for a photovoltaic system. Electrical Power and Energy Systems, 64, 792–800.
  • Singh, R., Kainthola , A. and Singh, T.N., 2012. Estimation of elastic constant of rocks using an ANFIS approach. Applied Soft Computing, 12, 40-45.
  • Stamatescu, I., Făgărășan, I., Stamatescu, G., Arghira, N. and Iliescu, S.S., 2014. Design and Implementation of a Solar-Tracking Algorithm. Procedia Engineering, 69, 500-507.
  • Stanciu, C. and Stanciu, D., 2014. Optimum tilt angle for flat plate collectors all over the World – A declination dependence formula and comparisons of three solar radiation models. Energy Conversion and Management, 81, 133–143.
  • Sun, S., Brooks, J., Nguyen, T., 2014. Harding, A., Wang, D. and David, T., Novel Organic and Polymeric Materials for Solar Energy. Procedia, 57, 79-88.
  • Tudorache, T. and Kreindler, L., 2010. Design of a solar tracker system for PV power plants. Acta Polytechnica Hungarica, 7, 23-39.

Year 2017, Volume: 17 Issue: 2, 546 - 554, 31.08.2017

Hayrettin Toylan Engin Hüner

Abstract

References

  • Abdallah, S. and Nijmeh, S., 2004. Two axes sun tracking system with PLC control. Energy Conversion and Management, 45, 1931–1939.
  • Alata, M., Al-Nimr, M.A. and Qaroush, Y., 2005. Developing a multipurpose sun tracking system using fuzzy control. Energy Conversion and Management, 46, 1229–1245.
  • Batayneh, W., Owais, A. and Nairoukh, M., 2013. An intelligent fuzzy based tracking controller for a dual-axis solar PV system. Automation in Construction, 29, 100–106.
  • Buragohain, M. and Mahanta, C., 2008. A novel approach for ANFIS modelling based on full factorial design. Applied Soft Computing, 8, 609-625.
  • Chin, C.S, Babu, A. and McBride, W., 2011. Design, modeling and testing of a standalone single axis active solar tracker using MATLAB/Simulink. Renewable Energy, 36, 3075-3090.
  • Clifford, M.J. and Eastwood, D., 2004. Design of a novel passive solar tracker. Solar Energy, 77, 269–280.
  • Cooper, P.I., 1969. The absorption of solar radiation in solar stills. Solar Energy, 12, 333–346.
  • Daraban, S., Petreus, D. and Morel, C., 2014. A novel MPPT (maximum power point tracking) algorithm based on a modified genetic algorithm specialized on tracking the global maximum power point in photovoltaic systems affected by partial shading. Energy, 74, 374-388.
  • Eke, R. and Senturk, A., 2012. Performance comparison of a double-axis sun tracking versus fixed PV system. Solar Energy, 86, 2665–2672.
  • Eldin, S.A.S., Abd-Elhady, M.S. and Kandil, H.A., 2016. Feasibility of solar tracking systems for PV panels in hot and cold regions. Renewable Energy, 85, 228-233.
  • Guo, M., Wang, Z., Zhang, J., Sun, F. and Zhang, X., 2011. Accurate altitude–azimuth tracking angle formulas for a heliostat with mirror–pivot offset and other fixed geometrical errors. Solar Energy, 85, 1091–1100.
  • Jang, J-S.R., 1993. ANFIS: Adaptive-Network-Based Fuzzy Inference System. IEEE transactions on systems, man, and cybernetics, 23. Li, D.H.W., Cheung, G.H.W. and Lam J.C., 2005. Analysis of the operational performance and efficiency characteristic for photovoltaic system in Hong Kong. Energy Conversion and Management, 46, 1107–1118. Oelhafen, P. and Schuler, A., 2005. Nanostructured materials for solar energy conversion. Solar Energy, 79, 110–121.
  • Pradhan, R. and Subudhi, B., 2015. Design and real-time implementation of a new auto-tuned adaptive MPPT control for a photovoltaic system. Electrical Power and Energy Systems, 64, 792–800.
  • Singh, R., Kainthola , A. and Singh, T.N., 2012. Estimation of elastic constant of rocks using an ANFIS approach. Applied Soft Computing, 12, 40-45.
  • Stamatescu, I., Făgărășan, I., Stamatescu, G., Arghira, N. and Iliescu, S.S., 2014. Design and Implementation of a Solar-Tracking Algorithm. Procedia Engineering, 69, 500-507.
  • Stanciu, C. and Stanciu, D., 2014. Optimum tilt angle for flat plate collectors all over the World – A declination dependence formula and comparisons of three solar radiation models. Energy Conversion and Management, 81, 133–143.
  • Sun, S., Brooks, J., Nguyen, T., 2014. Harding, A., Wang, D. and David, T., Novel Organic and Polymeric Materials for Solar Energy. Procedia, 57, 79-88.
  • Tudorache, T. and Kreindler, L., 2010. Design of a solar tracker system for PV power plants. Acta Polytechnica Hungarica, 7, 23-39.
There are 18 citations in total.

Details

Primary Language Turkish
Journal Section Articles
Authors

Hayrettin Toylan

Engin Hüner This is me

Publication Date August 31, 2017
Submission Date November 9, 2016
Published in Issue Year 2017 Volume: 17 Issue: 2

Cite

APA Toylan, H., & Hüner, E. (2017). Uyarlamalı Sinirsel Bulanık Çıkarım (ANFIS) Tabanlı Güneş Takip Sistemi. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, 17(2), 546-554.
AMA Toylan H, Hüner E. Uyarlamalı Sinirsel Bulanık Çıkarım (ANFIS) Tabanlı Güneş Takip Sistemi. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi. August 2017;17(2):546-554.
Chicago Toylan, Hayrettin, and Engin Hüner. “Uyarlamalı Sinirsel Bulanık Çıkarım (ANFIS) Tabanlı Güneş Takip Sistemi”. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi 17, no. 2 (August 2017): 546-54.
EndNote Toylan H, Hüner E (August 1, 2017) Uyarlamalı Sinirsel Bulanık Çıkarım (ANFIS) Tabanlı Güneş Takip Sistemi. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi 17 2 546–554.
IEEE H. Toylan and E. Hüner, “Uyarlamalı Sinirsel Bulanık Çıkarım (ANFIS) Tabanlı Güneş Takip Sistemi”, Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, vol. 17, no. 2, pp. 546–554, 2017.
ISNAD Toylan, Hayrettin - Hüner, Engin. “Uyarlamalı Sinirsel Bulanık Çıkarım (ANFIS) Tabanlı Güneş Takip Sistemi”. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi 17/2 (August 2017), 546-554.
JAMA Toylan H, Hüner E. Uyarlamalı Sinirsel Bulanık Çıkarım (ANFIS) Tabanlı Güneş Takip Sistemi. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi. 2017;17:546–554.
MLA Toylan, Hayrettin and Engin Hüner. “Uyarlamalı Sinirsel Bulanık Çıkarım (ANFIS) Tabanlı Güneş Takip Sistemi”. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, vol. 17, no. 2, 2017, pp. 546-54.
Vancouver Toylan H, Hüner E. Uyarlamalı Sinirsel Bulanık Çıkarım (ANFIS) Tabanlı Güneş Takip Sistemi. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi. 2017;17(2):546-54.