Open AccessSolar irradiance uncertainty management based on Monte Carlo-beta probability density function: case in Malaysian tropical climate
Author(s) -
Norazalina Saad,
Muhamad Zahim Sujod,
Mohd Ikhwan Muhammad Ridzuan,
M. F. Abas,
Mohd Shawal Jadin,
Mohd Shafie Bakar,
Abu Zaharin Ahmad
Publication year - 2019
Publication title -
bulletin of electrical engineering and informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.251
H-Index - 12
ISSN - 2302-9285
DOI - 10.11591/eei.v8i3.1581
Subject(s) - photovoltaic system , renewable energy , solar irradiance , environmental science , electricity generation , solar resource , monte carlo method , solar energy , irradiance , probability density function , meteorology , solar power , engineering , power (physics) , physics , mathematics , statistics , electrical engineering , quantum mechanics
In recent years, solar PV power generation has seen a rapid growth due to environmental benefits and zero fuel costs. In Malaysia, due to its location near the equator, makes solar energy the most utilized renewable energy resources. Unlike conventional power generation, solar energy is considered as uncertain generation sources which will cause unstable energy supplied. The uncertainty of solar resource needs to be managed for the planning of the PV system to produce its maximum power. The statistical method is the most prominent to manage and model the solar irradiance uncertainty patterns. Based on one-minute time interval meteorological data taken in Pekan, Pahang, West Malaysia, the Monte Carlo-Beta probability density function (Beta PDF) is performed to model continuous random variable of solar irradiance. The uncertainty studies are needed to optimally plan the photovoltaic system for the development of solar PV technologies in generating electricity and enhance the utilization of renewable energy; especially in tropical climate region.