IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i4p1652-d1060399.html
   My bibliography  Save this article

Multiple Input-Single Output DC-DC Converters Assessment for Low Power Renewable Sources Integration

Author

Listed:
  • Joaquin Soldado-Guamán

    (Independent Researcher, Riobamba 060101, Ecuador)

  • Victor Herrera-Perez

    (Colegio de Ciencias e Ingenierías, Universidad San Francisco de Quito—USFQ, Quito 170901, Ecuador)

  • Mayra Pacheco-Cunduri

    (Facultad de Informática y Electrónica, Escuela Superior Politécnica de Chimborazo (ESPOCH), Riobamba 060101, Ecuador)

  • Alejandro Paredes-Camacho

    (Departamento de Ingeniería Electrónica, Grupo de Investigación MCIA, Universitat Politécnica de Catalunya—UPC, 08222 Barcelona, Spain)

  • Miguel Delgado-Prieto

    (Departamento de Ingeniería Electrónica, Grupo de Investigación MCIA, Universitat Politécnica de Catalunya—UPC, 08222 Barcelona, Spain)

  • Jorge Hernandez-Ambato

    (Facultad de Informática y Electrónica, Escuela Superior Politécnica de Chimborazo (ESPOCH), Riobamba 060101, Ecuador)

Abstract

This paper presents a comparison of Isolated (Flyback) and non-Isolated (Buck) multiple input-single output (MISO) DC-DC converters. The analysis of DC-DC converters is based on pulsed voltage source cells (PVSC). The modeling of both converter types is detailed through their mathematical models and electrical simulations using Matlab/Simulink and PSIM. The comparison focuses on the sizing parameters, non-ideal output characteristics and efficiency. Results show that the output voltage of the MISO Buck converter exhibits a linear dependence on the duty cycles control signal and has slightly higher efficiency than the Flyback converter. To validate the operation of both converters, a scenario with two inputs (low-power hydroelectric and photovoltaic voltage sources) is considered. The modeling and control of both source systems are detailed and the MISO converter performance response is evaluated under sources changes and efficiency point of view.

Suggested Citation

  • Joaquin Soldado-Guamán & Victor Herrera-Perez & Mayra Pacheco-Cunduri & Alejandro Paredes-Camacho & Miguel Delgado-Prieto & Jorge Hernandez-Ambato, 2023. "Multiple Input-Single Output DC-DC Converters Assessment for Low Power Renewable Sources Integration," Energies, MDPI, vol. 16(4), pages 1-28, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:1652-:d:1060399
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/4/1652/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/4/1652/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Yujie & Tian, Jiaqiang & Sun, Zhendong & Wang, Li & Xu, Ruilong & Li, Mince & Chen, Zonghai, 2020. "A comprehensive review of battery modeling and state estimation approaches for advanced battery management systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    2. Affam, Azuka & Buswig, Yonis M. & Othman, Al-Khalid Bin Hj & Julai, Norhuzaimin Bin & Qays, Ohirul, 2021. "A review of multiple input DC-DC converter topologies linked with hybrid electric vehicles and renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    3. Rehman, Zubair & Al-Bahadly, Ibrahim & Mukhopadhyay, Subhas, 2015. "Multiinput DC–DC converters in renewable energy applications – An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 521-539.
    4. Hossain, M.Z. & Rahim, N.A. & Selvaraj, Jeyraj a/l, 2018. "Recent progress and development on power DC-DC converter topology, control, design and applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 205-230.
    Full references (including those not matched with items on IDEAS)

    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. Amir, Asim & Amir, Aamir & Che, Hang Seng & Elkhateb, Ahmad & Rahim, Nasrudin Abd, 2019. "Comparative analysis of high voltage gain DC-DC converter topologies for photovoltaic systems," Renewable Energy, Elsevier, vol. 136(C), pages 1147-1163.
    2. Reddi Khasim, Shaik & Dhanamjayulu, C., 2021. "Selection parameters and synthesis of multi-input converters for electric vehicles: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    3. Naseri, F. & Gil, S. & Barbu, C. & Cetkin, E. & Yarimca, G. & Jensen, A.C. & Larsen, P.G. & Gomes, C., 2023. "Digital twin of electric vehicle battery systems: Comprehensive review of the use cases, requirements, and platforms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 179(C).
    4. Takyi-Aninakwa, Paul & Wang, Shunli & Zhang, Hongying & Yang, Xiao & Fernandez, Carlos, 2023. "A hybrid probabilistic correction model for the state of charge estimation of lithium-ion batteries considering dynamic currents and temperatures," Energy, Elsevier, vol. 273(C).
    5. Ester Vasta & Tommaso Scimone & Giovanni Nobile & Otto Eberhardt & Daniele Dugo & Massimiliano Maurizio De Benedetti & Luigi Lanuzza & Giuseppe Scarcella & Luca Patanè & Paolo Arena & Mario Cacciato, 2023. "Models for Battery Health Assessment: A Comparative Evaluation," Energies, MDPI, vol. 16(2), pages 1-34, January.
    6. Okay, Kamil & Eray, Sermet & Eray, Aynur, 2022. "Development of prototype battery management system for PV system," Renewable Energy, Elsevier, vol. 181(C), pages 1294-1304.
    7. Qi, Kaijian & Zhang, Weigang & Zhou, Wei & Cheng, Jifu, 2022. "Integrated battery power capability prediction and driving torque regulation for electric vehicles: A reduced order MPC approach," Applied Energy, Elsevier, vol. 317(C).
    8. Liu, Xinghua & Li, Siqi & Tian, Jiaqiang & Wei, Zhongbao & Wang, Peng, 2023. "Health estimation of lithium-ion batteries with voltage reconstruction and fusion model," Energy, Elsevier, vol. 282(C).
    9. Belqasem Aljafari & Gunapriya Devarajan & Sivaranjani Subramani & Subramaniyaswamy Vairavasundaram, 2023. "Intelligent RBF-Fuzzy Controller Based Non-Isolated DC-DC Multi-Port Converter for Renewable Energy Applications," Sustainability, MDPI, vol. 15(12), pages 1-22, June.
    10. Fabian Rücker & Ilka Schoeneberger & Till Wilmschen & Ahmed Chahbaz & Philipp Dechent & Felix Hildenbrand & Elias Barbers & Matthias Kuipers & Jan Figgener & Dirk Uwe Sauer, 2022. "A Comprehensive Electric Vehicle Model for Vehicle-to-Grid Strategy Development," Energies, MDPI, vol. 15(12), pages 1-31, June.
    11. Adrian Ostermann & Yann Fabel & Kim Ouan & Hyein Koo, 2022. "Forecasting Charging Point Occupancy Using Supervised Learning Algorithms," Energies, MDPI, vol. 15(9), pages 1-23, May.
    12. Hernandez-Matheus, Alejandro & Löschenbrand, Markus & Berg, Kjersti & Fuchs, Ida & Aragüés-Peñalba, Mònica & Bullich-Massagué, Eduard & Sumper, Andreas, 2022. "A systematic review of machine learning techniques related to local energy communities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    13. Chein-Chung Sun & Chun-Hung Chou & Yu-Liang Lin & Yu-Hua Huang, 2022. "A Cost-Effective Passive/Active Hybrid Equalizer Circuit Design," Energies, MDPI, vol. 15(6), pages 1-20, March.
    14. Saad Khan Baloch & Abdul Sattar Larik & Mukhtiar Ahmed Mahar, 2023. "Analyzing the Effectiveness of Single Active Bridge DC-DC Converter under Transient and Load Variation," Sustainability, MDPI, vol. 15(6), pages 1-18, March.
    15. Saikumar Bairabathina & Balamurugan S, 2022. "Design and Validation of a SEPIC-Based Novel Multi-Input DC-DC Converter for Grid-Independent Hybrid Electric Vehicles," Energies, MDPI, vol. 15(15), pages 1-27, August.
    16. Yang, Bowen & Wang, Dafang & Sun, Xu & Chen, Shiqin & Wang, Xingcheng, 2023. "Offline order recognition for state estimation of Lithium-ion battery using fractional order model," Applied Energy, Elsevier, vol. 341(C).
    17. Li, Alan G. & West, Alan C. & Preindl, Matthias, 2022. "Towards unified machine learning characterization of lithium-ion battery degradation across multiple levels: A critical review," Applied Energy, Elsevier, vol. 316(C).
    18. Lai, Xin & Huang, Yunfeng & Gu, Huanghui & Han, Xuebing & Feng, Xuning & Dai, Haifeng & Zheng, Yuejiu & Ouyang, Minggao, 2022. "Remaining discharge energy estimation for lithium-ion batteries based on future load prediction considering temperature and ageing effects," Energy, Elsevier, vol. 238(PA).
    19. Jiang, Bo & Zhu, Jiangong & Wang, Xueyuan & Wei, Xuezhe & Shang, Wenlong & Dai, Haifeng, 2022. "A comparative study of different features extracted from electrochemical impedance spectroscopy in state of health estimation for lithium-ion batteries," Applied Energy, Elsevier, vol. 322(C).
    20. Hoque, M.M. & Hannan, M.A. & Mohamed, A. & Ayob, A., 2017. "Battery charge equalization controller in electric vehicle applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 1363-1385.

    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:gam:jeners:v:16:y:2023:i:4:p:1652-:d:1060399. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.