Abstract
Various building energy use modeling methods have been applied to existing buildings in order to understand building energy performance and improve energy efficiency. There are widely used models based on physical principles and historical data. This study has used temperature-based regression, artificial neural network and EnergyPlus models to predict energy use of a laboratory building. The paper discusses the accuracy of different methods when predicting short-term and long-term whole building energy use. It also discusses the feasibility and limitation of analyzing component level energy use and evaluating energy savings potential.
| Original language | English (US) |
|---|---|
| Pages | 743-749 |
| Number of pages | 7 |
| State | Published - 2011 |
| Externally published | Yes |
| Event | 12th Conference of International Building Performance Simulation Association Building Simulation 2011, BS 2011 - Sydney, NSW, Australia Duration: Nov 14 2011 → Nov 16 2011 |
Other
| Other | 12th Conference of International Building Performance Simulation Association Building Simulation 2011, BS 2011 |
|---|---|
| Country/Territory | Australia |
| City | Sydney, NSW |
| Period | 11/14/11 → 11/16/11 |
ASJC Scopus subject areas
- Computer Science Applications
- Building and Construction
- Architecture
- Modeling and Simulation