Solar irradiance uncertainty management based on Monte Carlo-beta probability density function: Case in Malaysian tropical climate

• Main Authors: N., Md. Saad, Muhamad Zahim, Sujod, Mohd Ikhwan, Muhammad Ridzuan, M. F., Abas, M. S., Jadin, Mohd. Shafie, Bakar, Abu Zaharin, Ahmad
• Format: Article
• Language: English
• Published: IAES 2019
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/29380/7/Solar%20irradiance%20uncertainty%20management%20based%20on%20Monte.pdf; http://umpir.ump.edu.my/id/eprint/29380/; http://dx.doi.org/10.11591/eei.v8i3.1581; http://dx.doi.org/10.11591/eei.v8i3.1581
• Institution: Universiti Malaysia Pahang

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.