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- W3158650847 abstract "Consumption, in general, represents the process of using a type of resource where savings needs to be done. Energy consumption has become one the main issue of urbanization and energy crisis as the fossil depletion and global warming put under threat the planet energy utilization. In this thesis, an automatic control of energy was developed to reduce energy consumption in residential area and passive house buildings. A mathematical model founded on empirical measurements was developed to emphasize the behavior of a testing laboratory from Universitatea Politehnica din București - Universite Politechnica de Bucarest - Roumanie. The experimental protocol was carried out following actions such as: building parameters database, collecting weather data, intake of auxiliary flows while considering the controlling factors. The control algorithm is controlling the system which can maintain a comfortable temperature within the building with minimum energy consumption. Measurements and data acquisition have been setup on two different levels: weather and buildings data. The data collection is gathered on a server which was implemented into the testing facility running a complex algorithm which can control energy consumption. The thesis reports several numerical methods for estimating the energy consumption that is further used with the control algorithm. An experimental showcase based on dynamic calculation methods for building energy performance assessments was made in Granada, Spain, information which was later used in this thesis. Estimation of model parameters (resistances and capacities) with prediction of heat flow was made using nodal method, based on physical elements, input data and weather information. Prediction of energy consumption using state-space modeling show improved results while IoT data collection was uploaded on a Raspberry Pi system. All these results were stable showing impressive progress in the prediction of energy consumption and their application in energy field." @default.
- W3158650847 created "2021-05-10" @default.
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- W3158650847 date "2020-11-24" @default.
- W3158650847 modified "2023-09-26" @default.
- W3158650847 title "Optimization of energy efficiency for residential buildings by using artificial intelligence" @default.
- W3158650847 hasPublicationYear "2020" @default.
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