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A small-scale standalone wind energy conversion system featuring SCIG, CSI and a novel storage integration scheme

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  • Alnasir, Zuher
  • Kazerani, Mehrdad

Abstract

In this paper, a small-scale standalone wind energy conversion system composed of a squirrel-cage induction generator, a buck converter and a current-source inverter is proposed, as an attractive renewable energy solution for off-grid communities. Geared squirrel-cage induction generators are well-known for their robustness, simplicity, light weight and low cost. Current-source inverters, even though mainly used in medium-voltage, high power applications, and proposed for megawatt-level grid-connected wind energy conversion systems, offer potential benefits in small-scale off-grid wind energy conversion systems that are yet to be investigated and evaluated against those of commonly-used voltage-source inverters. In the proposed system, the generator's shaft speed is controlled by a buck converter to extract maximum available wind power in normal mode of operation, and the wind power is dumped when it is not possible to absorb maximum available power by the storage system and the load. A novel scheme for integration of a battery energy storage system is proposed and an effective power management algorithm is employed to maintain the supply-demand power balance through direct control of dc-link current. A systematic approach for the dc-link inductor design is presented. The feasibility of the proposed system and its performance under variable wind and load conditions are analyzed and demonstrated through simulation.

Suggested Citation

  • Alnasir, Zuher & Kazerani, Mehrdad, 2016. "A small-scale standalone wind energy conversion system featuring SCIG, CSI and a novel storage integration scheme," Renewable Energy, Elsevier, vol. 89(C), pages 360-370.
  • Handle: RePEc:eee:renene:v:89:y:2016:i:c:p:360-370
    DOI: 10.1016/j.renene.2015.12.041
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    References listed on IDEAS

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    1. Alnasir, Zuher & Kazerani, Mehrdad, 2013. "An analytical literature review of stand-alone wind energy conversion systems from generator viewpoint," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 597-615.
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    1. Dhibi, Khaled & Mansouri, Majdi & Bouzrara, Kais & Nounou, Hazem & Nounou, Mohamed, 2022. "Reduced neural network based ensemble approach for fault detection and diagnosis of wind energy converter systems," Renewable Energy, Elsevier, vol. 194(C), pages 778-787.
    2. Tiwari, Ramji & Babu, N. Ramesh, 2016. "Recent developments of control strategies for wind energy conversion system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 268-285.
    3. Andrés Peña Asensio & Santiago Arnaltes Gómez & Jose Luis Rodriguez-Amenedo & Manuel García Plaza & Joaquín Eloy-García Carrasco & Jaime Manuel Alonso-Martínez de las Morenas, 2018. "A Voltage and Frequency Control Strategy for Stand-Alone Full Converter Wind Energy Conversion Systems," Energies, MDPI, vol. 11(3), pages 1-19, February.
    4. Pali, Bahadur Singh & Vadhera, Shelly, 2018. "A novel pumped hydro-energy storage scheme with wind energy for power generation at constant voltage in rural areas," Renewable Energy, Elsevier, vol. 127(C), pages 802-810.

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