IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v49y2015icp907-920.html
   My bibliography  Save this article

Efficiency optimization of a DSP-based standalone PV system using a stable single input fuzzy logic controller

Author

Listed:
  • Farhat, Maissa
  • Barambones, Oscar
  • Sbita, Lassaâd

Abstract

This paper presents a new digital maximum power point tracking control scheme for a standalone photovoltaic (PV) system. It is built up on a single input fuzzy-logic (SIFLC), and based on the constant voltage algorithm. The SIFLC generates a duty cycle (D) signal which is the control one for the DC–DC Boost converter. The proposed SIFLC performances will be compared to these of the well-known P&O algorithm. A stability study for the Mamdani SIFLC controllers is performed and proposed. The Lyapunov method is considered for the stability analysis of the proposed control systems. This MPPT algorithm is then experimentally implemented all around a DSP1104 for a real-time driving. The obtained results show that the proposed SIFLC-MPPT clearly succeeds to track the maximum power point and shows a higher performance than regular MPPTs such as the P&O algorithm. Results of the experimental tests also prove the validity and robustness of the proposed overall PV system control scheme.

Suggested Citation

  • Farhat, Maissa & Barambones, Oscar & Sbita, Lassaâd, 2015. "Efficiency optimization of a DSP-based standalone PV system using a stable single input fuzzy logic controller," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 907-920.
    • Handle: RePEc:eee:rensus:v:49:y:2015:i:c:p:907-920
    DOI: 10.1016/j.rser.2015.04.123
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032115003937
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2015.04.123?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. Jiang, Joe-Air & Su, Yu-Li & Shieh, Jyh-Cherng & Kuo, Kun-Chang & Lin, Tzu-Shiang & Lin, Ta-Te & Fang, Wei & Chou, Jui-Jen & Wang, Jen-Cheng, 2014. "On application of a new hybrid maximum power point tracking (MPPT) based photovoltaic system to the closed plant factory," Applied Energy, Elsevier, vol. 124(C), pages 309-324.
    2. Lo Brano, Valerio & Ciulla, Giuseppina, 2013. "An efficient analytical approach for obtaining a five parameters model of photovoltaic modules using only reference data," Applied Energy, Elsevier, vol. 111(C), pages 894-903.
    3. 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.
    4. Mohanty, Parimita & Bhuvaneswari, G. & Balasubramanian, R. & Dhaliwal, Navdeep Kaur, 2014. "MATLAB based modeling to study the performance of different MPPT techniques used for solar PV system under various operating conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 581-593.
    5. Kim, Younghyun & Lee, Woojoo & Pedram, Massoud & Chang, Naehyuck, 2013. "Dual-mode power regulator for photovoltaic module emulation," Applied Energy, Elsevier, vol. 101(C), pages 730-739.
    6. Balezentiene, Ligita & Streimikiene, Dalia & Balezentis, Tomas, 2013. "Fuzzy decision support methodology for sustainable energy crop selection," Renewable and Sustainable Energy Reviews, Elsevier, vol. 17(C), pages 83-93.
    7. Eltawil, Mohamed A. & Zhao, Zhengming, 2013. "MPPT techniques for photovoltaic applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 793-813.
    8. Taghvaee, M.H. & Radzi, M.A.M. & Moosavain, S.M. & Hizam, Hashim & Hamiruce Marhaban, M., 2013. "A current and future study on non-isolated DC–DC converters for photovoltaic applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 17(C), pages 216-227.
    9. Bo Long & Ji Hyoung Ryu & Shin Teak Lim & Kil To Chong, 2014. "Design and Control of a Multi-Functional Energy Recovery Power Accumulator Battery Pack Testing System for Electric Vehicles," Energies, MDPI, vol. 7(3), pages 1-17, March.
    10. Sheng-Yu Tseng & Hung-Yuan Wang, 2013. "A Photovoltaic Power System Using a High Step-up Converter for DC Load Applications," Energies, MDPI, vol. 6(2), pages 1-33, February.
    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. Maissa Farhat & Oscar Barambones & Lassaâd Sbita, 2020. "A Real-Time Implementation of Novel and Stable Variable Step Size MPPT," Energies, MDPI, vol. 13(18), pages 1-18, September.
    2. Haidar Islam & Saad Mekhilef & Noraisyah Binti Mohamed Shah & Tey Kok Soon & Mehdi Seyedmahmousian & Ben Horan & Alex Stojcevski, 2018. "Performance Evaluation of Maximum Power Point Tracking Approaches and Photovoltaic Systems," Energies, MDPI, vol. 11(2), pages 1-24, February.
    3. Nabipour, M. & Razaz, M. & Seifossadat, S.GH & Mortazavi, S.S., 2017. "A new MPPT scheme based on a novel fuzzy approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1147-1169.
    4. 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.
    5. Enany, Mohamed A. & Farahat, Mohamed A. & Nasr, Ahmed, 2016. "Modeling and evaluation of main maximum power point tracking algorithms for photovoltaics systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1578-1586.
    6. Mohamed Redha Rezoug & Rachid Chenni & Djamel Taibi, 2018. "Fuzzy Logic-Based Perturb and Observe Algorithm with Variable Step of a Reference Voltage for Solar Permanent Magnet Synchronous Motor Drive System Fed by Direct-Connected Photovoltaic Array," Energies, MDPI, vol. 11(2), pages 1-15, February.
    7. 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.
    8. Maen Takruri & Maissa Farhat & Oscar Barambones & José Antonio Ramos-Hernanz & Mohammed Jawdat Turkieh & Mohammed Badawi & Hanin AlZoubi & Maswood Abdus Sakur, 2020. "Maximum Power Point Tracking of PV System Based on Machine Learning," Energies, MDPI, vol. 13(3), pages 1-14, February.
    9. 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.
    10. Farhat, Maissa & Barambones, Oscar & Sbita, Lassaad, 2017. "A new maximum power point method based on a sliding mode approach for solar energy harvesting," Applied Energy, Elsevier, vol. 185(P2), pages 1185-1198.
    11. Ben Ali, I. & Turki, M. & Belhadj, J. & Roboam, X., 2018. "Optimized fuzzy rule-based energy management for a battery-less PV/wind-BWRO desalination system," Energy, Elsevier, vol. 159(C), pages 216-228.

    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. 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.
    2. 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.
    3. 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.
    4. Boukenoui, R. & Ghanes, M. & Barbot, J.-P. & Bradai, R. & Mellit, A. & Salhi, H., 2017. "Experimental assessment of Maximum Power Point Tracking methods for photovoltaic systems," Energy, Elsevier, vol. 132(C), pages 324-340.
    5. 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.
    6. 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.
    7. Bizon, Nicu, 2016. "Global Maximum Power Point Tracking (GMPPT) of Photovoltaic array using the Extremum Seeking Control (ESC): A review and a new GMPPT ESC scheme," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 524-539.
    8. Belhaouas, N. & Cheikh, M.-S. Ait & Agathoklis, P. & Oularbi, M.-R. & Amrouche, B. & Sedraoui, K. & Djilali, N., 2017. "PV array power output maximization under partial shading using new shifted PV array arrangements," Applied Energy, Elsevier, vol. 187(C), pages 326-337.
    9. 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.
    10. Enany, Mohamed A. & Farahat, Mohamed A. & Nasr, Ahmed, 2016. "Modeling and evaluation of main maximum power point tracking algorithms for photovoltaics systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1578-1586.
    11. 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.
    12. Musong L. Katche & Augustine B. Makokha & Siagi O. Zachary & Muyiwa S. Adaramola, 2023. "A Comprehensive Review of Maximum Power Point Tracking (MPPT) Techniques Used in Solar PV Systems," Energies, MDPI, vol. 16(5), pages 1-23, February.
    13. Kebir, Anouer & Woodward, Lyne & Akhrif, Ouassima, 2019. "Real-time optimization of renewable energy sources power using neural network-based anticipative extremum-seeking control," Renewable Energy, Elsevier, vol. 134(C), pages 914-926.
    14. 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.
    15. Li, Shaowu, 2016. "Linear equivalent models at the maximum power point based on variable weather parameters for photovoltaic cell," Applied Energy, Elsevier, vol. 182(C), pages 94-104.
    16. Nabipour, M. & Razaz, M. & Seifossadat, S.GH & Mortazavi, S.S., 2017. "A new MPPT scheme based on a novel fuzzy approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1147-1169.
    17. Marcus Evandro Teixeira Souza Junior & Luiz Carlos Gomes Freitas, 2022. "Power Electronics for Modern Sustainable Power Systems: Distributed Generation, Microgrids and Smart Grids—A Review," Sustainability, MDPI, vol. 14(6), pages 1-22, March.
    18. Jately, Vibhu & Azzopardi, Brian & Joshi, Jyoti & Venkateswaran V, Balaji & Sharma, Abhinav & Arora, Sudha, 2021. "Experimental Analysis of hill-climbing MPPT algorithms under low irradiance levels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    19. Kermadi, Mostefa & Berkouk, El Madjid, 2017. "Artificial intelligence-based maximum power point tracking controllers for Photovoltaic systems: Comparative study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 369-386.
    20. 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.

    More about this item

    Keywords

    BOOST; FUZZY; MPPT; PVG; P&O;
    All these keywords.

    Statistics

    Access and download statistics

    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:rensus:v:49:y:2015:i:c:p:907-920. 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.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    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.