Abstract

Maximum Power Point Tracking (MPPT) methods are used in photovoltaic (PV) systems to continually maximize the PV array output power, which strongly depends on both solar radiation and cell temperature. The PV power oscillations around the maximum power point (MPP) resulting from the conventional methods and complexity of the non-conventional ones are convincing reasons to look for novel MPPT methods. This paper deals with simple Genetic Algorithms (GAs) based MPPT method in order to improve the convergence, rapidity, and accuracy of the PV system. The proposed method can also efficiently track the global MPP, which is very useful for partial shading. At first, a review of the algorithm is given, followed with many test examples; then, a comparison by means Matlab/Simulink© (R2009b) is conducted between the proposed MPPT and, the popular Perturb and Observe (PO) and Incremental Conductance (IC) techniques. The results show clearly the superiority of the proposed controller. Indeed, with the proposed algorithm, oscillations around the MPP are dramatically minimized, a better stability is observed and increase in the output power efficiency is obtained. All these results are experimentally validated by a test bench developed at LIAS laboratory (Poitiers University, Poitiers, France) using real PV panels and a PV emulator which allows one to define a profile insolation model. In addition, the proposed method permits one to perform the test of linearity between the optimal current I mp (current at maximum power) and the short-circuit current I sc , and between the optimal voltage V mp and open-circuit voltage V oc , so the current and voltage factors can be easily obtained with our algorithm.

Highlights

  • PV energy has been widely used during recent years because of its advantages, the growth in the world demand of energy, and the lowering of the PV panels’ cost [1].The PV output power efficiency is low and can be even lower if the panels do not operate at theirmaximum power point (MPP), but this changes with atmospheric conditions so it is very important to ensure the panels operate around that point.Many methods are used to track the MPP, they can be divided in two groups: conventional and non-conventional methods

  • MPP, but this changes with atmospheric conditions so it is very important to ensure the panels operate around that point

  • The conventional methods are widely used (such as Perturb and Observe (PO) [2,3], Incremental Conductance (IC) [4,5]) because they are simple and easy to implement. Both the PO and IC methods result in oscillation of power around the MPP because the perturbation remains even when the system operates at MPP

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Summary

Introduction

PV energy has been widely used during recent years because of its advantages, the growth in the world demand of energy, and the lowering of the PV panels’ cost [1].The PV output power efficiency is low and can be even lower if the panels do not operate at theirMPP, but this changes with atmospheric conditions (insolation and temperature) so it is very important to ensure the panels operate around that point.Many methods are used to track the MPP, they can be divided in two groups: conventional and non-conventional methods. The conventional methods are widely used (such as Perturb and Observe (PO) [2,3], Incremental Conductance (IC) [4,5]) because they are simple and easy to implement. Both the PO and IC methods result in oscillation of power around the MPP because the perturbation remains even when the system operates at MPP. This problem can be reduced by decreasing the step of the duty cycle. The algorithm will track the MPP slowly in response to changing

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