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Title: PATTERN RECOGNITION TOOL FOR ENERGY CONSUMPTION PROFILES IDENTIFICATION
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PATTERN RECOGNITION TOOL FOR ENERGY CONSUMPTION PROFILES IDENTIFICATION
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1314-2704
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English
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17
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42
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This article proposes a software tool, based on artificial intelligence technics, to grid operators and energy companies, to optimize the power system. Precisely, it uses pattern recognition capabilities of neural networks, in order to enable a higher share of renewable energy to consumers. The applied analysis on PV power and other related electrical grid data, such as smart energy meter readings, are based on pattern recognition technics. The neural networks used for this approach will identify days of the week with similar energy consumption profiles.
In this respect, firstly are presented concepts of: pattern recognition and neural networks. Secondly, these intelligent tools are implemented using Matlab programming language, in order to develop a graphical user interface for data monitoring and pattern recognition of load profiles. Thirdly, the software demonstrator is tested using real monitored data provided by Multidisciplinary Science and Technology Research Institute of Valhi University of Targoviste, Romania. |
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conference
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17th International Multidisciplinary Scientific GeoConference SGEM 2017
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17th International Multidisciplinary Scientific GeoConference SGEM 2017, 29 June - 5 July, 2017
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Proceedings Paper
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STEF92 Technology
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International Multidisciplinary Scientific GeoConference-SGEM
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Bulgarian Acad Sci; Acad Sci Czech Republ; Latvian Acad Sci; Polish Acad Sci; Russian Acad Sci; Serbian Acad Sci & Arts; Slovak Acad Sci; Natl Acad Sci Ukraine; Natl Acad Sci Armenia; Sci Council Japan; World Acad Sci; European Acad Sci, Arts & Letters; Ac
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467-474
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29 June - 5 July, 2017
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website
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cdrom
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3749
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pattern recognition; self organisig maps-SOM; neural network; load; energy
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