Photovoltaic modules evaluation and dry-season energy yield prediction model for NEM in Malaysia

Syed Zahurul Islam; Mohammad Lutfi Othman; Muhammad Saufi; Rosli Omar; Arash Toudeshki; Syed Zahidul Islam

doi:10.1371/journal.pone.0241927

Photovoltaic modules evaluation and dry-season energy yield prediction model for NEM in Malaysia

PLoS One. 2020 Nov 12;15(11):e0241927. doi: 10.1371/journal.pone.0241927. eCollection 2020.

Authors

Syed Zahurul Islam¹, Mohammad Lutfi Othman², Muhammad Saufi¹, Rosli Omar¹, Arash Toudeshki³, Syed Zahidul Islam⁴

Affiliations

¹ Faculty of Electrical & Electronic Engineering, Universiti Tun Hussein Onn Malaysia(UTHM), Parit Raja, Johor, Malaysia.
² Department of Electrical and Electronics Engineering, Advanced Lightning, Power and Energy Research (ALPER), Faculty of Engineering, Universiti Putra Malaysia, Serdang, Selangor, Malaysia.
³ School of Engineering, University of California, Merced, CA, United States of America.
⁴ Radiation Solutions Inc, Mississauga, ON, Canada.

Abstract

This study analyzes the performance of two PV modules, amorphous silicon (a-Si) and crystalline silicon (c-Si) and predicts energy yield, which can be seen as facilitation to achieve the target of 35% reduction of greenhouse gases emission by 2030. Malaysia Energy Commission recommends crystalline PV modules for net energy metering (NEM), but the climate regime is a concern for output power and efficiency. Based on rainfall and irradiance data, this study aims to categorize the climate of peninsular Malaysia into rainy and dry seasons; and then the performance of the two modules are evaluated under the dry season. A new mathematical model is developed to predict energy yield and the results are validated through experimental and systematic error analysis. The parameters are collected using a self-developed ZigBeePRO-based wireless system with the rate of 3 samples/min over a period of five days. The results unveil that efficiency is inversely proportional to the irradiance due to negative temperature coefficient for crystalline modules. For this phenomenon, efficiency of c-Si (9.8%) is found always higher than a-Si (3.5%). However, a-Si shows better shadow tolerance compared to c-Si, observed from a lesser decrease rate in efficiency of the former with the increase in irradiance. Due to better spectrum response and temperature coefficient, a-Si shows greater performance on output power efficiency (OPE), performance ratio (PR), and yield factor. From the regression analysis, it is found that the coefficient of determination (R2) is between 0.7179 and 0.9611. The energy from the proposed model indicates that a-Si yields 15.07% higher kWh than c-Si when luminance for recorded days is 70% medium and 30% high. This study is important to determine the highest percentage of energy yield and to get faster NEM payback period, where as of now, there is no such model to indicate seasonal energy yield in Malaysia.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Greenhouse Gases / chemistry*
Malaysia
Models, Theoretical
Seasons
Silicon / chemistry*
Temperature

Substances

Greenhouse Gases
Silicon

Grants and funding

Syed Zahurul Islam, Research Management Center, Research Fund E15501, Universiti Tun Hussein Onn Malaysia (UTHM), www.uthm.edu.my. Mohammad Lutfi, 9671700, Geran Putra Berimpak, University Putra Malaysia (UPM), www.upm.edu.my. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Syed Zahidul Islam is an employee of the commercial Canadian company, Radiation Solutions Inc. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.