Publication:
Study on electricity demand projection and energy policy implications in malaysia

dc.contributor.authorHo Chun Hanen_US
dc.date.accessioned2023-05-03T17:25:34Z
dc.date.available2023-05-03T17:25:34Z
dc.date.issued2020-02
dc.description.abstractThe ability to forecast electricity demand and determining factors affecting it has been crucial element for economic development and energy security of a country. Forecasting electricity demand allows policy makers to determine which sector has higher electricity demand in the future and it allows proper investment planning to improve the available facilities that generates electricity or build new power plants to prevent shortage in supply. In this thesis, the study emphasizes more on projection of electricity demand for year 2018 to 2035 for residential sector, industrial sector and commercial sector using multiple regression models meanwhile simple exponential smoothing method was used to project electricity demand in agriculture and transport sector. The variables that affects electricity demand was also determined through multiple regression model. The results demonstrate that industrial sector has the highest electricity demand at 48.53%, followed by commercial sector at 32.83%, residential sector at 17.81% meanwhile agriculture and transport sector has the lowest demand at 0.43% and 0.42% respectively. From the results, a number of policy implication was identified to help reduce electricity consumption of respective sector and reduce carbon emission. For example, by applying latest technology in iron and steel which allows electricity to be saved, moving towards industry 4.0, encouraging new and existing buildings to obtain green certificate and diversifying the types of energy sources for electricity generation.en_US
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/21612
dc.subjectElectricityen_US
dc.subjectProjectionen_US
dc.subjectPolicyen_US
dc.titleStudy on electricity demand projection and energy policy implications in malaysiaen_US
dspace.entity.typePublication
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