Universiti Teknologi Malaysia Institutional Repository

Maximum power point tracking technique under partial shading condition for photovoltaic systems

Alik, Rozana (2017) Maximum power point tracking technique under partial shading condition for photovoltaic systems. PhD thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering.

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Abstract

Maximum Power Point Tracking (MPPT) technique extracts the maximum available power from the photovoltaic array (PV). Perturb and Observe (P&O) is the most preferable type of MPPT algorithm due to its simplicity, accuracy and low cost. However, when partial shading condition occurs, it produces multiple local maximum power points (MPPs) on the PV characteristics curve. This causes confusion for the conventional P&O algorithm to track the true MPP. This thesis studies the impact of partial shading on the PV system and to improve the P&O algorithm by adding a checking algorithm into the variable step size. This checking algorithm determines the global maximum power by first comparing all existing peak points before the P&O algorithm identifies the voltage at MPP to calculate the duty cycle of the boost converter. The PV power and voltage rating used for this research are 42 W and 17 V, respectively. The boost converter can double the PV output voltage. The simulation results have proven that the proposed algorithm is able to track the global MPP with a tracking efficiency of 99.96%. This has been verified by hardware implementation of the proposed algorithm using Arduino Mega 2560. The proposed MPPT algorithm also provides better stability with less percentage error on the PV output voltage and power compared to using the conventional P&O MPPT algorithm.

Item Type:Thesis (PhD)
Additional Information:Thesis (Sarjana Kejuruteraan (Elektrikal)) - Universiti Teknologi Malaysia, 2017; Supervisor : Assoc. Prof. Dr. Awang Jusoh
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:79023
Deposited By: Fazli Masari
Deposited On:27 Sep 2018 04:14
Last Modified:27 Sep 2018 04:14

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