TY - JOUR
T1 - Total utility demand prediction for multi-dwelling sites by a bottom-up approach considering variations of inhabitants' behaviour schedules
AU - Tanimoto, Jun
AU - Hagishima, Aya
AU - Iwai, Takeshi
AU - Ikegaya, Naoki
N1 - Funding Information:
This study was partially supported by a Grant-in-Aid for Scientific Research by JSPS awarded to Dr Hagishima (#20686040) and by the Asahi Glass Foundation. We would like to express our gratitude to these funding sources.
Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.
PY - 2012/1
Y1 - 2012/1
N2 - This article reports systematic case studies based on a Total Utility Demand Prediction System presented in the authors' previous works, in which one can follow a bottom-up approach to accurately calculate the time series utility loads (energy, power, city water, hot water, etc.) for multi-dwelling systems, including residential buildings, residential block areas and even an entire city. This calculation considers the behavioural variations of the inhabitants of the dwellings. In the case studies, we assumed a residential building consisting of 100 independent dwellings to accurately predict various peak demands and seasonal or annual demands. A series of simulations reveals that considering time-varying inhabitant behaviour schedules significantly affects the peak loads. Hence, HVAC COP, inhabitants' age and their family type significantly influence the peak loads and their accurate time-series.
AB - This article reports systematic case studies based on a Total Utility Demand Prediction System presented in the authors' previous works, in which one can follow a bottom-up approach to accurately calculate the time series utility loads (energy, power, city water, hot water, etc.) for multi-dwelling systems, including residential buildings, residential block areas and even an entire city. This calculation considers the behavioural variations of the inhabitants of the dwellings. In the case studies, we assumed a residential building consisting of 100 independent dwellings to accurately predict various peak demands and seasonal or annual demands. A series of simulations reveals that considering time-varying inhabitant behaviour schedules significantly affects the peak loads. Hence, HVAC COP, inhabitants' age and their family type significantly influence the peak loads and their accurate time-series.
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U2 - 10.1080/19401493.2012.680498
DO - 10.1080/19401493.2012.680498
M3 - Article
AN - SCOPUS:84868333051
SN - 1940-1493
VL - 6
SP - 53
EP - 64
JO - Journal of Building Performance Simulation
JF - Journal of Building Performance Simulation
IS - 1
ER -