Atiqah Hamizah Mohd Nordin
Universiti Teknologi MARA

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Life-cycle assessment of residential-scale grid-connected photovoltaic system in Malaysia based on monocrystalline silicon modules Atiqah Hamizah Mohd Nordin; Shahril Irwan Sulaiman; Sulaiman Shaari; Rijalul Fahmi Mustapa
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 11, No 2: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (377.052 KB) | DOI: 10.11591/ijpeds.v11.i2.pp677-684

Abstract

Even though PV systems have been promoted as a green form of electrification, such systems are still contributing to environmental impacts after considering life-cycle impact during material extraction, manufacturing processes of its components, installation, operation, and maintenance. This paper presents a life-cycle assessment to quantify the environmental impact of residential-scale grid-connected PV systems in Malaysia using monocrystalline silicon PV module. LCA had been carried out by using OpenLCA 1.8 software, Ecoinvent 3.5 database, and impact assessment method of IMPACT2002+ and CED. The influence of varying system capacity from 3 to 12 kWp, system lifetime of 21, 25 and 30 years, and solar irradiation of 1560.8, 1651.8, & 1935.5 kWh/m2/yr, were investigated. The results revealed that the greenhouse gas emissions rate, cumulative energy demand, and energy payback time of residential-scale grid-connected PV systems in Malaysia ranged from 37.97 to 67.26 g CO2-eq/kWh, 4387.10 to 4699.99 MJ/m2, and 6.37 to 7.90 years, respectively. This study also evaluated indicators of energy return on investment. The overall finding implies that the installation of residential-scale grid-connected PV systems in Malaysia offers significant potential for GHG emissions reduction in the country.
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.