Application of the Artificial intelligence in the energy solving of Building services of intelligent buildings Areas

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F17%3A00317242" target="_blank" >RIV/68407700:21110/17:00317242 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.5593/sgem2017H/63" target="_blank" >http://dx.doi.org/10.5593/sgem2017H/63</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5593/sgem2017H/63" target="_blank" >10.5593/sgem2017H/63</a>

Result language

angličtina

Original language name

Application of the Artificial intelligence in the energy solving of Building services of intelligent buildings Areas

Original language description

Currently, a great emphasis is put on the environment, energy intensity, and therefore on applications of the renewable energy sources (RES). Putting a large amount of RES into the modern distribution systems represents certain problems we can address, inter alia, the variable energy outputs of RES aggregated together, including their accumulation managed by respective energy management system (EMS). The result may be the optimization unit commitment of RES distributed in the micro-grids of a fictitious intelligent city composed of an intelligent buildings (IB) complex. For this purpose, a computer program has been implemented to optimize operating costs to cover energy consumption of intelligent buildings, based on predicted load profiles. The underlying basis of EMS is, among other things, the optimization unit commitment of RES distributed in the micro-grid, distant from a fictitious intelligent city composed of an intelligent buildings complex. For this purpose, a computer program has been implemented to optimize operating costs to cover energy consumption of intelligent buildings, based on predicted load profiles. As an example of the self-organizing neural network used for cluster analysis (CA), we demonstrate its efficiency in the process of identifying type daily energy consumption diagrams of an intelligent buildings complex combined in the electric micro-grid for a typical working day and typical day off based on network’s annual history. The aforementioned type daily diagrams can be used to predict the power consumption.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

R - Projekt Ramcoveho programu EK

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

GREEN BUILDINGS TECHNOLOGIES AND MATERIALS

ISBN

978-619-7408-29-4

ISSN

1314-2704

e-ISSN

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Number of pages

10

Pages from-to

767-776

Publisher name

SGEM WORLD SCIENCE

Place of publication

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Event location

Vienna

Event date

Nov 27, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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