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NY Dahlan
Universiti Teknologi MARA

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Energy consumption prediction through linear and non-linear baseline energy model Rijalul Fahmi Mustapa; NY Dahlan; Ihsan Mohd Yassin; Atiqah Hamizah Mohd Nordin; Azlee Zabidi
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 1: January 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i1.pp102-109

Abstract

Accurate baseline energy models demand increase significantly as it lower the risk of energy savings quantification. It is achieved by performing energy consumption prediction with its respective independent variables through linear or non-linear modelling technique. Developing such model through linear modelling technique provide certain disadvantages due to the fact that the behavior of certain independent variables with respect to the energy consumption is non-linear in nature. Furthermore, linear modelling technique requires prior studies upon modelling to achieve accurate energy consumption prediction. Thus, to apprehend this situation, this paper main intention is to perform energy consumption prediction through a non-linear modelling technique to provide alternative option for developing a good and accurate baseline energy models. This study proposes energy consumption prediction based on Non-linear Auto Regressive with Exogenous Input – Artificial Neural Network (NARX-ANN) as a non-linear modelling technique that will be compared with Multiple Linear Regression Model (MLR) as linear modelling technique. A case study in Malaysian educational buildings during lecture week will be used for this purpose. The results demonstrate that NARX-ANN shows a higher accuracy through statistical error measurement.
Automated Calibration Of Greenhouse Energy Model Using Hybrid Evolutionary Programming (EP)-Energy Plus NY Dahlan; S. Z. Sakimin; M. Faizwan; N. Ajmain; A. A. Aris
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp648-654

Abstract

This paper presents an optimization approach of calibrating a tomato greenhouse energy model using hybrid Evolutionary Programming (EP)-EnergyPlus. The proposed methodology applies automated simulation-based approach by coupling Matlab and EnergyPlus to perform building energy simulation and obtain the best variables configuration with minimal error between the simulated and measured energy of the greenhouse. The proposed method is tested using a tomato greenhouse system located in Universiti Putra Malaysia (UPM). The greenhouse envelope is built using 0.15mm thick Transparency Plastic Film. Meanwhile, the electrical loads in the greenhouse consists of 6 exhaust fans, 2 axial fans, 5 fluorescent lamps and 1 irrigation pump. An Evolutionary Programming (EP) algorithm is chosen and programmed in Matlab to find the best configurations for optimum calibration of the greenhouse energy model. Three variables were chosen to find the best configuration which are the operating hours of Exhaust Fan, Axial Fan and Water Pump. The EP optimization algorithm in Matlab is coupled with building energy simulator, EnergyPlus using BCVTB as the coupling tool. Result shows that the EnergyPlus-EP model can provide NMBE and CV(RMSE) within the range recommended by the IPMVP protocol. The proposed method is not only requiring less computation time but also effective in searching for the best variables configuration with minimal error.
Co-Authors A. A. Aris Atiqah Hamizah Mohd Nordin Azlee Zabidi Ihsan Mohd Yassin M. Faizwan N. Ajmain Rijalul Fahmi Mustapa S. Z. Sakimin