IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v87y2016ip2p965-976.html
   My bibliography  Save this article

Investigation and analysis of high performance green energy induction motor drive with intelligent estimator

Author

Listed:
  • Chitra, A.
  • Himavathi, S.

Abstract

This paper attempts to enhance the performance of a green energy induction motor drive. The electronic power converters become indispensable part of the renewable energy systems (RES). The solar photovoltaic (PV) system is efficiently operated with artificial neural network (ANN) based maximum power point tracking (MPPT) algorithm. The inverter topologies for the green drive scheme are analyzed. To improve the drive performance a reduced switch multilevel inverter (RSMLI) is employed. As indirect field oriented control (IFOC) is used, the drive demands on-line estimation of rotor resistance. A neural learning model reference adaptive scheme (NL-MRAS) based rotor resistance estimator is found to exhibit good dynamic performance. This work also investigates the performance of the green drive with an intelligent estimator. The performance enhancement of the green energy drive obtained by ANN based MPPT for the PV system, a reduced switch MLI and an intelligent estimator is presented.

Suggested Citation

  • Chitra, A. & Himavathi, S., 2016. "Investigation and analysis of high performance green energy induction motor drive with intelligent estimator," Renewable Energy, Elsevier, vol. 87(P2), pages 965-976.
    • Handle: RePEc:eee:renene:v:87:y:2016:i:p2:p:965-976
    DOI: 10.1016/j.renene.2015.07.084
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148115301804
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2015.07.084?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Reza Reisi, Ali & Hassan Moradi, Mohammad & Jamasb, Shahriar, 2013. "Classification and comparison of maximum power point tracking techniques for photovoltaic system: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 433-443.
    2. Salam, Zainal & Ahmed, Jubaer & Merugu, Benny S., 2013. "The application of soft computing methods for MPPT of PV system: A technological and status review," Applied Energy, Elsevier, vol. 107(C), pages 135-148.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tuan Pham Van & Dung Vo Tien & Zbigniew Leonowicz & Michal Jasinski & Tomasz Sikorski & Prasun Chakrabarti, 2020. "Online Rotor and Stator Resistance Estimation Based on Artificial Neural Network Applied in Sensorless Induction Motor Drive," Energies, MDPI, vol. 13(18), pages 1-16, September.
    2. Ahmed A. Zaki Diab & Mohammed A. Elsawy & Kotin A. Denis & Salem Alkhalaf & Ziad M. Ali, 2022. "Artificial Neural Based Speed and Flux Estimators for Induction Machine Drives with Matlab/Simulink," Mathematics, MDPI, vol. 10(8), pages 1-22, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ramli, Makbul A.M. & Twaha, Ssennoga & Ishaque, Kashif & Al-Turki, Yusuf A., 2017. "A review on maximum power point tracking for photovoltaic systems with and without shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 144-159.
    2. Ram, J.Prasanth & Rajasekar, N. & Miyatake, Masafumi, 2017. "Design and overview of maximum power point tracking techniques in wind and solar photovoltaic systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 1138-1159.
    3. Joshi, Puneet & Arora, Sudha, 2017. "Maximum power point tracking methodologies for solar PV systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1154-1177.
    4. Mellit, Adel & Kalogirou, Soteris A., 2014. "MPPT-based artificial intelligence techniques for photovoltaic systems and its implementation into field programmable gate array chips: Review of current status and future perspectives," Energy, Elsevier, vol. 70(C), pages 1-21.
    5. Liu, Yi-Hua & Chen, Jing-Hsiao & Huang, Jia-Wei, 2015. "A review of maximum power point tracking techniques for use in partially shaded conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 436-453.
    6. Bahrami, Milad & Gavagsaz-Ghoachani, Roghayeh & Zandi, Majid & Phattanasak, Matheepot & Maranzanaa, Gaël & Nahid-Mobarakeh, Babak & Pierfederici, Serge & Meibody-Tabar, Farid, 2019. "Hybrid maximum power point tracking algorithm with improved dynamic performance," Renewable Energy, Elsevier, vol. 130(C), pages 982-991.
    7. Bhatti, Abdul Rauf & Salam, Zainal & Aziz, Mohd Junaidi Bin Abdul & Yee, Kong Pui & Ashique, Ratil H., 2016. "Electric vehicles charging using photovoltaic: Status and technological review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 34-47.
    8. Gao, Xian-Zhong & Hou, Zhong-Xi & Guo, Zheng & Chen, Xiao-Qian, 2015. "Reviews of methods to extract and store energy for solar-powered aircraft," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 96-108.
    9. Çelik, Özgür & Teke, Ahmet & Tan, Adnan, 2018. "Overview of micro-inverters as a challenging technology in photovoltaic applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3191-3206.
    10. Amir, A. & Amir, A. & Selvaraj, J. & Rahim, N.A., 2016. "Study of the MPP tracking algorithms: Focusing the numerical method techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 350-371.
    11. Seyedmahmoudian, M. & Horan, B. & Soon, T. Kok & Rahmani, R. & Than Oo, A. Muang & Mekhilef, S. & Stojcevski, A., 2016. "State of the art artificial intelligence-based MPPT techniques for mitigating partial shading effects on PV systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 435-455.
    12. Amjad Ali & K. Almutairi & Muhammad Zeeshan Malik & Kashif Irshad & Vineet Tirth & Salem Algarni & Md. Hasan Zahir & Saiful Islam & Md Shafiullah & Neeraj Kumar Shukla, 2020. "Review of Online and Soft Computing Maximum Power Point Tracking Techniques under Non-Uniform Solar Irradiation Conditions," Energies, MDPI, vol. 13(12), pages 1-37, June.
    13. Das, Soubhagya K. & Verma, Deepak & Nema, Savita & Nema, R.K., 2017. "Shading mitigation techniques: State-of-the-art in photovoltaic applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 369-390.
    14. Ram, J. Prasanth & Babu, T. Sudhakar & Rajasekar, N., 2017. "A comprehensive review on solar PV maximum power point tracking techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 826-847.
    15. Yao, Ganzhou & Luo, Zirong & Lu, Zhongyue & Wang, Mangkuan & Shang, Jianzhong & Guerrerob, Josep M., 2023. "Unlocking the potential of wave energy conversion: A comprehensive evaluation of advanced maximum power point tracking techniques and hybrid strategies for sustainable energy harvesting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).
    16. Mohammad R. Altimania & Nadia A. Elsonbaty & Mohamed A. Enany & Mahmoud M. Gamil & Saeed Alzahrani & Musfer Hasan Alraddadi & Ruwaybih Alsulami & Mohammad Alhartomi & Moahd Alghuson & Fares Alatawi & , 2023. "Optimal Performance of Photovoltaic-Powered Water Pumping System," Mathematics, MDPI, vol. 11(3), pages 1-21, February.
    17. Pasta, Edoardo & Faedo, Nicolás & Mattiazzo, Giuliana & Ringwood, John V., 2023. "Towards data-driven and data-based control of wave energy systems: Classification, overview, and critical assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    18. Chatterjee, Shantanu & Kumar, Prashant & Chatterjee, Saibal, 2018. "A techno-commercial review on grid connected photovoltaic system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2371-2397.
    19. Jiang, Joe-Air & Su, Yu-Li & Kuo, Kun-Chang & Wang, Chien-Hao & Liao, Min-Sheng & Wang, Jen-Cheng & Huang, Chen-Kang & Chou, Cheng-Ying & Lee, Chien-Hsing & Shieh, Jyh-Cherng, 2017. "On a hybrid MPPT control scheme to improve energy harvesting performance of traditional two-stage inverters used in photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1113-1128.
    20. Başoğlu, Mustafa Engin & Çakır, Bekir, 2016. "Comparisons of MPPT performances of isolated and non-isolated DC–DC converters by using a new approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1100-1113.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:87:y:2016:i:p2:p:965-976. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.