Modelling of Solar Power Generation in Malaysia: A Time Series Analysis

This study explores the dynamics of solar power generation in Malaysia using time series analysis, focusing on key environmental variables such as irradiance, ambient temperature, module temperature, and humidity. Data from a solar installation in Gading Kencana, Melaka, collected between July 2019 and January 2021, underwent stationarity testing, and multiple regression analysis to understand the factors influencing solar energy production. Results reveal that irradiance significantly enhances energy output, while module temperature and humidity negatively impact performance. Ambient temperature shows mixed effects depending on the context. Despite the statistical insignificance of humidity, its multicollinearity with other variables suggests a nuanced impact. The predictive model demonstrates robustness, offering reliable insights into optimizing solar panel efficiency and planning for variability in energy output. The findings aim to support energy managers, policymakers, and solar operators in improving solar power systems, ensuring sustainable energy development amidst Malaysia’s climate challenges.

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Publication Details

Journal
Future Energy and Environment Letters
Published
2025-06-30
DOI
https://doi.org/10.37934/feel.3.1.1930
Primary Topic
Solar Radiation and Photovoltaics
Type
article
Field-Weighted Citation Impact
0.00
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article

Modelling of Solar Power Generation in Malaysia: A Time Series Analysis

Nilanjan Chatterjee, Noor Ibrahim, N Abidin
Future Energy and Environment Letters
Solar Radiation and Photovoltaics
article

Modelling of Solar Power Generation in Malaysia: A Time Series Analysis

Nilanjan Chatterjee, Noor Ibrahim, N Abidin
article en

Abstract

This study explores the dynamics of solar power generation in Malaysia using time series analysis, focusing on key environmental variables such as irradiance, ambient temperature, module temperature, and humidity. Data from a solar installation in Gading Kencana, Melaka, collected between July 2019 and January 2021, underwent stationarity testing, and multiple regression analysis to understand the factors influencing solar energy production. Results reveal that irradiance significantly enhances energy output, while module temperature and humidity negatively impact performance. Ambient temperature shows mixed effects depending on the context. Despite the statistical insignificance of humidity, its multicollinearity with other variables suggests a nuanced impact. The predictive model demonstrates robustness, offering reliable insights into optimizing solar panel efficiency and planning for variability in energy output. The findings aim to support energy managers, policymakers, and solar operators in improving solar power systems, ensuring sustainable energy development amidst Malaysia’s climate challenges.

Future Energy and Environment LettersVol. 3(1)
Universiti Sains Islam Malaysia (MY)
Climate action
Openalex Percentile: Top 90%
Solar Radiation and Photovoltaics
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