Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Quantitative correlation models between electricity consumption and behaviors about lighting, sockets and others for electricity consumption prediction in typical campus buildings
https://orcid.org/0000-0003-3467-4380
Highlights Derivation and solving methods of occupant behavior probability in buildings were proposed. Several novel parameters were proposed for measuring occupant behaviors. Quantitative models for predicting electricity consumption by occupant behaviors were proposed. Quantitative models for predicting occupant numbers by environment and time were proposed.
Abstract Energy consumption prediction for buildings and architectural complexes has become increasingly important. However, existing methods based on simulation software or statistical algorithms have distinct disadvantages. Consequently, this study introduces a novel prediction method based on models between occupant behavior and energy consumption. A new parameter––the occupant behavior characteristic parameter, is defined by coupling factors, including occupant behavior probability, occupant numbers, and building operation hours. Correlation models between this characteristic parameter (Parameter A) and electricity consumption (Parameter B) are established. Moreover, because of the difficulty in obtaining occupant numbers, models between environment, time influence factors (parameter C) and occupant numbers are proposed for occupant number prediction. In summary, models of the three parameters (A, B, and C) can be combined to obtain an electricity consumption prediction model. On the one hand, this model can reflect energy use laws with a higher accuracy than prediction methods based on temperature or other factors; on the other hand, it can be applied online without complex algorithms and software simulation. Moreover, it needs only model one equation for the same building types, which obviates modeling building-by-building like software simulation. Thus, the proposed model offers strong operability, especially the prediction for architectural complexes.
Quantitative correlation models between electricity consumption and behaviors about lighting, sockets and others for electricity consumption prediction in typical campus buildings
https://orcid.org/0000-0003-3467-4380
Highlights Derivation and solving methods of occupant behavior probability in buildings were proposed. Several novel parameters were proposed for measuring occupant behaviors. Quantitative models for predicting electricity consumption by occupant behaviors were proposed. Quantitative models for predicting occupant numbers by environment and time were proposed.
Abstract Energy consumption prediction for buildings and architectural complexes has become increasingly important. However, existing methods based on simulation software or statistical algorithms have distinct disadvantages. Consequently, this study introduces a novel prediction method based on models between occupant behavior and energy consumption. A new parameter––the occupant behavior characteristic parameter, is defined by coupling factors, including occupant behavior probability, occupant numbers, and building operation hours. Correlation models between this characteristic parameter (Parameter A) and electricity consumption (Parameter B) are established. Moreover, because of the difficulty in obtaining occupant numbers, models between environment, time influence factors (parameter C) and occupant numbers are proposed for occupant number prediction. In summary, models of the three parameters (A, B, and C) can be combined to obtain an electricity consumption prediction model. On the one hand, this model can reflect energy use laws with a higher accuracy than prediction methods based on temperature or other factors; on the other hand, it can be applied online without complex algorithms and software simulation. Moreover, it needs only model one equation for the same building types, which obviates modeling building-by-building like software simulation. Thus, the proposed model offers strong operability, especially the prediction for architectural complexes.
Quantitative correlation models between electricity consumption and behaviors about lighting, sockets and others for electricity consumption prediction in typical campus buildings
https://orcid.org/0000-0003-3467-4380
Highlights Derivation and solving methods of occupant behavior probability in buildings were proposed. Several novel parameters were proposed for measuring occupant behaviors. Quantitative models for predicting electricity consumption by occupant behaviors were proposed. Quantitative models for predicting occupant numbers by environment and time were proposed.
Abstract Energy consumption prediction for buildings and architectural complexes has become increasingly important. However, existing methods based on simulation software or statistical algorithms have distinct disadvantages. Consequently, this study introduces a novel prediction method based on models between occupant behavior and energy consumption. A new parameter––the occupant behavior characteristic parameter, is defined by coupling factors, including occupant behavior probability, occupant numbers, and building operation hours. Correlation models between this characteristic parameter (Parameter A) and electricity consumption (Parameter B) are established. Moreover, because of the difficulty in obtaining occupant numbers, models between environment, time influence factors (parameter C) and occupant numbers are proposed for occupant number prediction. In summary, models of the three parameters (A, B, and C) can be combined to obtain an electricity consumption prediction model. On the one hand, this model can reflect energy use laws with a higher accuracy than prediction methods based on temperature or other factors; on the other hand, it can be applied online without complex algorithms and software simulation. Moreover, it needs only model one equation for the same building types, which obviates modeling building-by-building like software simulation. Thus, the proposed model offers strong operability, especially the prediction for architectural complexes.
Quantitative correlation models between electricity consumption and behaviors about lighting, sockets and others for electricity consumption prediction in typical campus buildings
Zhang, Chengyu (Autor:in) / Zhao, Tianyi (Autor:in) / Li, Kuishan (Autor:in)
Energy and Buildings ; 253
24.09.2021
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Characteristics of electricity consumption in commercial buildings
| Online Contents | 1994
Characteristics of electricity consumption in commercial buildings
| Taylor & Francis Verlag | 1994
Prediction Model of City Electricity Consumption
| Springer Verlag | 2020