Battery capacity estimation in wind power generation system

Ryo Furuyama, Yohei Watanabe, Shinji Wakao

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    For the spread of wind power generations, the technology of reducing fluctuations in wind power output is indispensable. In this research, we perform computational analyses of a wind power generation system with storage battery, and propose a novel approach for deriving the proper battery capacity. This research is to achieve sufficient smoothing of wind power output and efficient use of wind power energy. In the proposed method, numerically investigating the trade-off relationship among the smoothing effect, battery capacity, and output efficiency characteristics, we can derive the battery capacity on the basis of cost/performance. Furthermore, we performed the investigation of the system using wind power prediction method, i.e., Just-In-Time Modeling. By predicting the wind power output, we can properly update the smoothing time constant according to the short-term wind condition, which results in the reduction of battery capacity. To verify the proposed approach, we also present some computational results based on the measured data of small wind power generation system.

    Original languageEnglish
    Title of host publicationProceedings of the IASTED International Conference on Energy and Power Systems
    Pages321-325
    Number of pages5
    Publication statusPublished - 2007
    Event9th IASTED International Conference on Power and Energy Systems, PES 2007 - Clearwater, FL
    Duration: 2007 Jan 32007 Jan 5

    Other

    Other9th IASTED International Conference on Power and Energy Systems, PES 2007
    CityClearwater, FL
    Period07/1/307/1/5

    Fingerprint

    Wind power
    Power generation
    electric batteries
    smoothing
    output
    storage batteries
    time constant
    costs
    predictions
    Costs

    Keywords

    • Battery capacity
    • Computer simulation
    • Just-in-time modeling
    • Short-term prediction
    • Smoothing of wind power output
    • Wind power generation

    ASJC Scopus subject areas

    • Energy Engineering and Power Technology
    • Electrical and Electronic Engineering
    • Condensed Matter Physics

    Cite this

    Furuyama, R., Watanabe, Y., & Wakao, S. (2007). Battery capacity estimation in wind power generation system. In Proceedings of the IASTED International Conference on Energy and Power Systems (pp. 321-325)

    Battery capacity estimation in wind power generation system. / Furuyama, Ryo; Watanabe, Yohei; Wakao, Shinji.

    Proceedings of the IASTED International Conference on Energy and Power Systems. 2007. p. 321-325.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Furuyama, R, Watanabe, Y & Wakao, S 2007, Battery capacity estimation in wind power generation system. in Proceedings of the IASTED International Conference on Energy and Power Systems. pp. 321-325, 9th IASTED International Conference on Power and Energy Systems, PES 2007, Clearwater, FL, 07/1/3.
    Furuyama R, Watanabe Y, Wakao S. Battery capacity estimation in wind power generation system. In Proceedings of the IASTED International Conference on Energy and Power Systems. 2007. p. 321-325
    Furuyama, Ryo ; Watanabe, Yohei ; Wakao, Shinji. / Battery capacity estimation in wind power generation system. Proceedings of the IASTED International Conference on Energy and Power Systems. 2007. pp. 321-325
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    AB - For the spread of wind power generations, the technology of reducing fluctuations in wind power output is indispensable. In this research, we perform computational analyses of a wind power generation system with storage battery, and propose a novel approach for deriving the proper battery capacity. This research is to achieve sufficient smoothing of wind power output and efficient use of wind power energy. In the proposed method, numerically investigating the trade-off relationship among the smoothing effect, battery capacity, and output efficiency characteristics, we can derive the battery capacity on the basis of cost/performance. Furthermore, we performed the investigation of the system using wind power prediction method, i.e., Just-In-Time Modeling. By predicting the wind power output, we can properly update the smoothing time constant according to the short-term wind condition, which results in the reduction of battery capacity. To verify the proposed approach, we also present some computational results based on the measured data of small wind power generation system.

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