An improved interval fuzzy modeling method: Applications to the estimation of photovoltaic/wind/battery power in renewable energy systems

Nguyen Gia Minh Thao, Kenko Uchida

    研究成果: Article査読

    2 被引用数 (Scopus)

    抄録

    This paper proposes an improved interval fuzzy modeling (imIFML) technique based on modified linear programming and actual boundary points of data. The imIFML technique comprises four design stages. The first stage is based on conventional interval fuzzy modeling (coIFML) with first-order model and linear programming. The second stage defines reference lower and upper bounds of data using MATLAB. The third stage initially adjusts scaling parameters in the modified linear programming. The last stage automatically fine-tunes parameters in the modified linear programming to realize the best possible model. Lower and upper bounds approximated by the imIFML technique are closely fitted to the reference lower and upper bounds, respectively. The proposed imIFML is thus significantly less conservative in cases of large variation in data, while robustness is inherited from the coIFML. Design flowcharts, equations, and sample MATLAB code are presented for reference in future experiments. Performance and efficacy of the introduced imIFML are evaluated to estimate solar photovoltaic, wind and battery power in a demonstrative renewable energy system under large data changes. The effectiveness of the proposed imIFML technique is also compared with the coIFML technique.

    本文言語English
    論文番号482
    ジャーナルEnergies
    11
    3
    DOI
    出版ステータスPublished - 2018 2 1

    ASJC Scopus subject areas

    • 再生可能エネルギー、持続可能性、環境
    • エネルギー工学および電力技術
    • エネルギー(その他)
    • 制御と最適化
    • 電子工学および電気工学

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