Theses and Dissertations
Issuing Body
Mississippi State University
Advisor
Cho, Heejin
Committee Member
Mago, Pedro J.
Committee Member
Luck, Rogelio
Date of Degree
8-14-2015
Document Type
Graduate Thesis - Open Access
Major
Mechanical Engineering
Degree Name
Master of Science
College
James Worth Bagley College of Engineering
Department
Department of Mechanical Engineering
Abstract
This thesis presents performance evaluation and a field validation study of a time and temperature indexed autoregressive with exogenous (4-3-5 ARX) building thermal load prediction model with an aim to integrate the model with actual predictive control systems. The 4-3-5 ARX model is very simple and computationally efficient with relatively high prediction accuracy compared to the existing sophisticated prediction models, such as artificial neural network prediction models. However, performance evaluation and field validation of the model are essential steps before implementing the model in actual practice. The performance of the model was evaluated under different climate conditions as well as under modeling uncertainty. A field validation study was carried out for three buildings at Mississippi State University. The results demonstrate that the 4-3-5 ARX model can predict building thermal loads in an accurate manner most of the times, indicating that the model can be readily implemented in predictive control systems.
URI
https://hdl.handle.net/11668/19740
Recommended Citation
Sarwar, Riasat Azim, "Performance Evaluation and Field Validation of Building Thermal Load Prediction Model" (2015). Theses and Dissertations. 3500.
https://scholarsjunction.msstate.edu/td/3500
Comments
load prediction accuracy||uncertainty analysis||field measurements||validation study||indexed prediction model||ARX models||cooling load||Building thermal load prediction