A comparison of optimal operation of a residential fuel cell co-generation system using clustered demand patterns based on Kullback-Leibler divergence

Akira Yoshida*, Yoshiharu Amano, Noboru Murata, Koichi Ito, Takumi Hasizume

*この研究の対応する著者

研究成果: Article査読

10 被引用数 (Scopus)

抄録

When evaluating residential energy systems like co-generation systems, hot water and electricity demand profiles are critical. In this paper, the authors aim to extract basic time-series demand patterns from two kinds of measured demand (electricity and domestic hot water), and also aim to reveal effective demand patterns for primary energy saving. Time-series demand data are categorized with a hierarchical clustering method using a statistical pseudo-distance, which is represented by the generalized Kullback-Leibler divergence of two Gaussian mixture distributions. The classified demand patterns are built using hierarchical clustering and then a comparison is made between the optimal operation of a polymer electrolyte membrane fuel cell co-generation system and the operation of a reference system (a conventional combination of a condensing gas boiler and electricity purchased from the grid) using the appropriately built demand profiles. Our results show that basic demand patterns are extracted by the proposed method, and the heat-to-power ratio of demand, the amount of daily demand, and demand patterns affect the primary energy saving of the co-generation system.

本文言語English
ページ(範囲)374-399
ページ数26
ジャーナルEnergies
6
1
DOI
出版ステータスPublished - 2013 1

ASJC Scopus subject areas

  • 再生可能エネルギー、持続可能性、環境
  • 燃料技術
  • 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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