Abstract

In this paper, we present a study of maximisation power tracking for photovoltaic energy conversion chain. We give a comparison between two techniques of tracking maximum power; Perturb &Observe (P&O) as first method versus a second method using artificial neural network (ANN). The two methods are designed, modelled and simulated in MATLAB/Simulink environment. The simulation results are discussed involving performance and constraints of these two algorithms.

Highlights

  • Photovoltaic energy conversion System (PECS) are used to produce electric power for utilities along sunny day

  • To maintain supplying load under variables irradiation the current and voltage are adjusted to maximum power available for climatic conditions, MPPT techniques are used for extracting the maximum power from the PV arrays at different environmental conditions such as temperature and solar irradiance

  • The training phase uses the data set obtained from the simulation of the PV array in Matlab / Simulink using the Perturb and observe (P&O) method, the artificial neural network (ANN) inputs variables are the voltage Vpv and current Ipv of PV array corresponding to a given solar radiation and ambient temperature temperature conditions, while the duty cycle D is chosen as output

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Summary

Introduction

Photovoltaic energy conversion System (PECS) are used to produce electric power for utilities along sunny day. The conventional MPPT algorithms include HillClimbing (HC) [1], Perturb and observe (P&O) [1,2], and incremental conductance (INC) [2] These techniques show obvious shortcomings, such as low tracking efficiency during quickly changing solar irradiation and fluctuations about the point of maximum power. The intelligent techniques, including fuzzy logic controller (FLC) [3,4], artificial neural network (ANN) [5], particle swarm optimization (PSO) [1], genetic algorithm (GA) [6] These algorithms present many advantages, such as low oscillations around the point of maximum power and a speedy tracking response to changing conditions. ANN is designed and compared with P&O technique

PV ARRAY
Boost converter
Perturb and Observe
MPPT based Artificial Neural Network
RESULTS AND DISCUSSION
Conclusion
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