Numerical modelling of the power pack system for remote islands electrification

International Conference on Sustainable Energy and Green Technology 2018

能源学;生态环境科学

Saw, L.H.^1 ; Cheow, J.S.^1 ; King, Y.J.^1 ; Yeo, W.H.^1 ; Lim, B.H.^1 ; Tey, J.Y.^1 ; Ng, T.C.^1

Lee Kong Chian Faculty of Engineering and Science, UTAR, Kajang, Malaysia^1

关键词: Battery technology;    Depth of discharges;    Economic solutions;    Electrical performance;    Energy storage systems;    Geographical locations;    High energy densities;    Photovoltaic modules;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/268/1/012103/pdf
DOI  :  10.1088/1755-1315/268/1/012103

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Electricity is one of the indispensable elements in the daily life. From domestic to commercial sector, electricity has been used to provide a wide range of applications. However, access to electricity is only limited to the urban area while rural area electrification is always a challenge due to the geographical location and high cost of the electrification infrastructure. Therefore, electrification using solar energy is projected to be one of the feasible solutions in the rural area. A typical power pack system used for the rural area electrification consists of solar panels, voltage converters and battery pack. Although lead acid battery provides an economic solution for the energy storage system, they are also associated with other disadvantages such as low depth of discharge, bulky and low energy density. Li-ion battery is a new generation of battery technology with high energy density, light weight and high depth of discharge which offer a promising solution for an off grid power systems. In this study, an off grid power pack consists of Li-ion batteries, voltage converters and photovoltaic modules are modelled to evaluate the electrical performances of the system under Malaysia weather conditions. Then, the numerical modelling results are compared with experiments. It is found out that the numerical model correlated well with the experimental data with a relative error less than 5%.