### 抄録

This paper describes a new methodology in calculating accurately the time series utility loads (energy, power, city water, hot water, etc.) in a dwelling. This calculation takes into account the behavioral variations of the dwelling inhabitants. The proposed method contains a procedure for cooling load calculations based on a series of Monte Carlo simulations where the HVAC on/off state and the indoor heat generation schedules are varied, time-step by time-step. A data set of time-varying inhabitant behavior schedules, with a 15 minute resolution, generated by the authors in previous studies and validated by a comparison analysis to several field measurement data sets, was integrated into the model. The established model, which is called the Total Utility Demand Prediction System (TUD-PS) can be applied to, for example, accurate estimation of an integrated space maximum requirement, such as the total load of a building or an urban area. In a series of numerical experiments, huge discrepancies were found between the conventional results and those considering the time-varying inhabitant behavior schedules. In particular, deriving the dynamic state change, of having the HVAC on/off from the inhabitant's schedules, was found to be a significant factor in the maximum cooling and heating loads.

元の言語 | 英語 |
---|---|

ホスト出版物のタイトル | IBPSA 2009 - International Building Performance Simulation Association 2009 |

ページ | 521-528 |

ページ数 | 8 |

出版物ステータス | 出版済み - 2009 |

イベント | 11th International IBPSA Conference - Building Simulation 2009, BS 2009 - Glasgow, 英国 継続期間: 7 27 2007 → 7 30 2007 |

### その他

その他 | 11th International IBPSA Conference - Building Simulation 2009, BS 2009 |
---|---|

国 | 英国 |

市 | Glasgow |

期間 | 7/27/07 → 7/30/07 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Computer Science Applications
- Building and Construction
- Architecture
- Modelling and Simulation

### これを引用

*IBPSA 2009 - International Building Performance Simulation Association 2009*(pp. 521-528)

**Total utility demand prediction based on probabilistically generated behaviroal schedules of actural inhabitants.** / Tanimoto, Jun; Hagishima, Aya.

研究成果: 著書/レポートタイプへの貢献 › 会議での発言

*IBPSA 2009 - International Building Performance Simulation Association 2009.*pp. 521-528, 11th International IBPSA Conference - Building Simulation 2009, BS 2009, Glasgow, 英国, 7/27/07.

}

TY - GEN

T1 - Total utility demand prediction based on probabilistically generated behaviroal schedules of actural inhabitants

AU - Tanimoto, Jun

AU - Hagishima, Aya

PY - 2009

Y1 - 2009

N2 - This paper describes a new methodology in calculating accurately the time series utility loads (energy, power, city water, hot water, etc.) in a dwelling. This calculation takes into account the behavioral variations of the dwelling inhabitants. The proposed method contains a procedure for cooling load calculations based on a series of Monte Carlo simulations where the HVAC on/off state and the indoor heat generation schedules are varied, time-step by time-step. A data set of time-varying inhabitant behavior schedules, with a 15 minute resolution, generated by the authors in previous studies and validated by a comparison analysis to several field measurement data sets, was integrated into the model. The established model, which is called the Total Utility Demand Prediction System (TUD-PS) can be applied to, for example, accurate estimation of an integrated space maximum requirement, such as the total load of a building or an urban area. In a series of numerical experiments, huge discrepancies were found between the conventional results and those considering the time-varying inhabitant behavior schedules. In particular, deriving the dynamic state change, of having the HVAC on/off from the inhabitant's schedules, was found to be a significant factor in the maximum cooling and heating loads.

AB - This paper describes a new methodology in calculating accurately the time series utility loads (energy, power, city water, hot water, etc.) in a dwelling. This calculation takes into account the behavioral variations of the dwelling inhabitants. The proposed method contains a procedure for cooling load calculations based on a series of Monte Carlo simulations where the HVAC on/off state and the indoor heat generation schedules are varied, time-step by time-step. A data set of time-varying inhabitant behavior schedules, with a 15 minute resolution, generated by the authors in previous studies and validated by a comparison analysis to several field measurement data sets, was integrated into the model. The established model, which is called the Total Utility Demand Prediction System (TUD-PS) can be applied to, for example, accurate estimation of an integrated space maximum requirement, such as the total load of a building or an urban area. In a series of numerical experiments, huge discrepancies were found between the conventional results and those considering the time-varying inhabitant behavior schedules. In particular, deriving the dynamic state change, of having the HVAC on/off from the inhabitant's schedules, was found to be a significant factor in the maximum cooling and heating loads.

UR - http://www.scopus.com/inward/record.url?scp=84870186780&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84870186780&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84870186780

SP - 521

EP - 528

BT - IBPSA 2009 - International Building Performance Simulation Association 2009

ER -