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Volumn , Issue , 2007, Pages 612-618

Controlling residential co-generation system based on hierarchical decentralized model

Author keywords

[No Author keywords available]

Indexed keywords

DECENTRALIZED MODELS; DEMAND DATUMS; ENERGY DEMANDS; GENERATION SYSTEMS; GENERATION UNITS; SHARING INFORMATIONS; SIMULATION MODELS;

EID: 47849083835     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/EFTA.2007.4416825     Document Type: Conference Paper
Times cited : (2)

References (10)
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    • S. Obara, K. Kudo and A. Kuroda, "Study on Small-Scale Co-generation System for Domestic House Considering Partial Load and Load Fluctuation", Journal of the Japan Society of Mechanical Engineers, Vol. 67, No. 655B, pp. 229 - 237, 2001.
    • (2001) Journal of the Japan Society of Mechanical Engineers , vol.67 , Issue.655 B , pp. 229-237
    • Obara, S.1    Kudo, K.2    Kuroda, A.3
  • 3
    • 84890804490 scopus 로고    scopus 로고
    • The Potential for Distributed Generation in Japanese Prototype Buildings: A DER-CAM Analysis of Policy, Tariff Design, Building Energy Use, and Technology
    • N. Zhou, C. Marnay, R. Firestone, W. Gao, M. Nishida, "The Potential for Distributed Generation in Japanese Prototype Buildings: A DER-CAM Analysis of Policy, Tariff Design, Building Energy Use, and Technology Development", LBNL-56359, 2004.
    • (2004) Development , vol.LBNL-56359
    • Zhou, N.1    Marnay, C.2    Firestone, R.3    Gao, W.4    Nishida, M.5
  • 5
    • 0000383868 scopus 로고
    • Parallel Networks that Learn to Pronounce English Text
    • T. J. Sejinowski and C. R. Rosenberg, "Parallel Networks that Learn to Pronounce English Text", Complex System, Vol. 1, pp. 145 - 168, 1987.
    • (1987) Complex System , vol.1 , pp. 145-168
    • Sejinowski, T.J.1    Rosenberg, C.R.2
  • 6
    • 0024137490 scopus 로고
    • Increased Rates of Convergence Through Learning Rate Adaptation
    • R. A. Jacobs, "Increased Rates of Convergence Through Learning Rate Adaptation", Neural Networks, Vol. 1, pp. 295 - 307, 1988.
    • (1988) Neural Networks , vol.1 , pp. 295-307
    • Jacobs, R.A.1
  • 7
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    • A New Training Method for Analyzable Structured Neural Network and Application of Daily Peak Load Forecasting
    • T. Iino, T. Matsui and Y. Fukuyama, "A New Training Method for Analyzable Structured Neural Network and Application of Daily Peak Load Forecasting" IEEJ Transactions on Power and Energy, Vol. 124, No. 3, pp. 347 - 354, 2004.
    • (2004) IEEJ Transactions on Power and Energy , vol.124 , Issue.3 , pp. 347-354
    • Iino, T.1    Matsui, T.2    Fukuyama, Y.3
  • 8
    • 85010234960 scopus 로고    scopus 로고
    • Selection of the Optimal Neural Network Architecture for Next Day Peak Load Forecasting
    • T. Onoda and E. Ohba, "Selection of the Optimal Neural Network Architecture for Next Day Peak Load Forecasting", IEEJ Transactions on Power and Energy, Vol. 118, No. 5, pp. 497 - 504, 1998.
    • (1998) IEEJ Transactions on Power and Energy , vol.118 , Issue.5 , pp. 497-504
    • Onoda, T.1    Ohba, E.2
  • 9
    • 47849103017 scopus 로고    scopus 로고
    • Forecast of Daily Maximum Electric Load by Neural Networks using the Standard Electric Load
    • Y.Sugai, H.Horibe and T.Kawase, "Forecast of Daily Maximum Electric Load by Neural Networks using the Standard Electric Load", IEEJ Transactions on Power and Energy, Vol. 117, No. 6, pp. 872 - 879, 1997.
    • (1997) IEEJ Transactions on Power and Energy , vol.117 , Issue.6 , pp. 872-879
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  • 10
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    • A Daily Start and Stop Algorithm for Residential Fuel Cell Systems Considering Information Settings of Day-ahead Hot Water Demand
    • E. Sugihara, T. Kato, Y. Suzuoki and K. Tsuji, "A Daily Start and Stop Algorithm for Residential Fuel Cell Systems Considering Information Settings of Day-ahead Hot Water Demand", IEEJ Transactions on Power and Energy, Vol. 124, No. 5, pp. 705 - 713, 2004.
    • (2004) IEEJ Transactions on Power and Energy , vol.124 , Issue.5 , pp. 705-713
    • Sugihara, E.1    Kato, T.2    Suzuoki, Y.3    Tsuji, K.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.