NDLI: Application of artificial intelligence and non-intrusive energy-managing system to economic dispatch strategy for cogeneration system and utility

Content Provider	IEEE Xplore Digital Library
Author	Hsueh-Hsien Chang Ching-Lung Lin Lin-Song Weng
Copyright Year	2009
Description	Author affiliation: Dept. of Electrical Engineering, Ming Hsin University of Science and Technology, Hsinchu, Taiwan (Ching-Lung Lin) \|\| Dept. of Electronic Engineering, Ming Hsin University of Science and Technology, Hsinchu, Taiwan (Lin-Song Weng) \|\| Dept. of Electronic Engineering, Jin Wen University of Science and Technology, Taipei, Taiwan (Hsueh-Hsien Chang)
Abstract	This paper proposes that artificial intelligence techniques and non-intrusive energy-managing technology (NIEM) will effectively manage energy demands within economic dispatch strategy analysis for the cogeneration plant and power utility. To test the performance of the proposed approach, data sets for electrical loads in the factories were analyzed and established using an electromagnetic transient program (EMTP) and onsite load measurement. The artificial intelligence techniques were applied to data extraction and factory load identification, especially for non-intrusive energy management. The effectiveness of factory load identification was analyzed and compared using different classifier methods. The strategy analysis revealed that the analysis of economic dispatch strategy for the cogeneration plant and power utility in the way of energy demands using the NIEM can estimate reasonably energy contribution from the cogeneration plant and/or power utility, and further improve air pollution. The application of artificial intelligence can reduce greatly the computation time and the size of memory for factory load identification and energy calculation.
Starting Page	740
Ending Page	745
File Size	415379
Page Count	6
File Format	PDF
ISBN	9781424435340
DOI	10.1109/CSCWD.2009.4968147
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-04-22
Publisher Place	Chile
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Artificial intelligence Power generation economics Cogeneration Production facilities Power system economics Energy management EMTP Load management Technology management Power system management Cogeneration system Load identification Economic dispatch Non-intrusive energy-managing system
Content Type	Text
Resource Type	Article

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