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An improved perturbation and observation maximum power point tracking algorithm for PV panels

Title:

An improved perturbation and observation maximum power point tracking algorithm for PV panels

Liu, Xuejun (2004) An improved perturbation and observation maximum power point tracking algorithm for PV panels. Masters thesis, Concordia University.

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Abstract

Photovoltaic (PV) energy presents great potential for applications in distributed power systems. However, it still presents a low energy conversion rate even at the Maximum Power Point (MPP). For instance, the maximum efficiency for crystalline silicon cell technology is around 18%. The rest of the incident solar energy either becomes heat or is reflected back to the atmosphere. The actual average efficiency can be even lower if the operating point is allowed to drift according to uncontrolled load and atmospheric conditions variations, In order to maximize the energy conversion, power electronics converters controlled with Maximum Power Point Tracking (MPPT) algorithms that consider the nonlinear output characteristics of PV panels should be used. Various MPPT algorithms have been proposed in the literature. Despite some drawbacks, Perturbation and Observation (P&O) MPPT algorithms are widely used in PV generating systems because of the ease of implementation and capability to compensate for variations in the solar irradiation level and temperature. This thesis proposes a different implementation of a P&O MPPT algorithm that can mitigate/reduce the main drawbacks commonly related to the P&O method. This is achieved with Peak Current Control and Instantaneous Sampling methods. The operating principles of the proposed control scheme are discussed. Experimental results for a dc-dc converter controlled with a DSP system are presented to validate the analysis and verify the performance of the proposed control scheme. They are carried out with both a Solar Array Simulator (SAS) and a real PV panel.

Divisions:Concordia University > Faculty of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Thesis (Masters)
Authors:Liu, Xuejun
Pagination:xvii, 119 leaves : ill. ; 29 cm.
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Electrical and Computer Engineering
Date:2004
Thesis Supervisor(s):Lopes, Luiz A. C
ID Code:8033
Deposited By:Concordia University Libraries
Deposited On:18 Aug 2011 14:13
Last Modified:18 Aug 2011 14:13
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