Development of models for prediction of cooling load and energy consumption for buildings in a tropical climate | |
| Author | Juntakan Taweekun |
| Call Number | AIT DISS. no. ET-03-02 |
| Subject(s) | Buildings--Energy consumption Cooling load |
| Note | A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Engineering, School of Environment, Resources and Development |
| Publisher | Asian Institute of Technology |
| Series Statement | Dissertation ; no. ET-03-02 |
| Abstract | This study focused on the development of cooling load and energy consumption prediction equations for commercial buildings. Firstly, studies on predicting cooling load and energy consumption at the Library and Regional Documentation Center Building in the Asian Institute of Technology are examined using a neural network and DOE-2 computer program. A three layer feed-forward neural network with backpropagation and orthogonal least square training algorithms were used in this study. The DOE-2 program was used to simulate the use of energy in the building under the climate condition of Bangkok, Thailand. The hourly and monthly results obtained from neural network and DOE-2 model were validated using data recorded over a one-year period. The CV, MBE and RMSE values for hourly predicting electrical demand are 10.35%, 1.11 %, 5.88 kW using neural network and 17.88%, -6.12%, 10.36 kW using DOE-2. For hourly predictions of cooling load, the CV, MBE and RMSE values are 22.32%, 2.57%, 11.83 RFT using neural network and 30.55%, -5.07%, 16.58 RFT using DOE-2. The results showed that neural network can provide hourly prediction results more accurately than the DOE-2 program. The data compiled from energy audit reports, such as building construction, lighting power density, equipment power density, and air-conditioning system characteristics were used to construct reference models for commercial and government buildings. These models were used to investigate energy consumption options through simulation using Bangkok climatic data. Energy savings for integrated retrofits are 16.1-22.6% of total energy use with payback period from 3 to 7.5 years for commercial buildings. For government buildings, integrated retrofit options save 56.8-59.3% of energy use in the air-conditioned space with payback period from 6 to 8 years. The results indicated that the whole building approach to be more cost effective than adopting individual retrofit options. Development and assessment of steady state and dynamic indicators of cooling requirement for four types of commercial buildings in tropical climate were also studied. Coolingdegree hour, dry-bulb temperature and enthalpy of ambient air were all shown to be good indicators of the weather-influenced component of cooling requirement of a building. A dynamic indicator developed as a performance indicator of the envelope of a building was found to be a good indicator and also was linearly related to the external factor of the cooling requirement of the building. Energy estimation models for commercial buildings were developed and validated using data obtained from energy audit reports. In this study, parametric simulations were used to obtain the correlation factors for cooling requirements and energy consumption. The equations provided cooling requirement and energy consumption estimation from simple calculations of the building envelope and internal loads of a building. The results showed that the model developed has high accuracy and can predict energy consumption very well. |
| Year | 2003 |
| Corresponding Series Added Entry | Asian Institute of Technology. Dissertation ; no. ET-03-02 |
| Type | Dissertation |
| School | School of Environment, Resources, and Development (SERD) |
| Department | Department of Energy and Climate Change (Former title: Department of Energy, Environment, and Climate Change (DEECC)) |
| Academic Program/FoS | Energy Technology (ET) |
| Chairperson(s) | Surapong C.; |
| Examination Committee(s) | Kumar, S.;Salokhe, Vilas M.; |
| Scholarship Donor(s) | Ministry of University Affairs Government of Thailand; |
| Degree | Thesis (Ph.D.) - Asian Institute of Technology, 2003 |