Abstract

This paper deals with an analysis and implementation of a control method proposed in the maximum power point tracking (MPPT) for photovoltaic systems. The Improved Particle Swarm Optimization (IPSO) algorithm is developed and implemented in Matlab/Simulink environment. Many simulations have been done considering the different system responses as the current, voltage and essentially the power. The efficiency of the proposed MPPT algorithm have been carried out.

Highlights

  • In recent years, solar energy becomes one of the most popular areas of renewable energy due to intensive energy demand and several advantages related to availability and cleanness environment [1], [2]

  • One of the fundamental problems is how to carry out the maximum power point tracking (MPPT)

  • A number of researches synthesized different methods to resolve the problems related to MPPT controller such as power feedback, incremental conductance, short circuit current, open circuit voltage [4], ripple correlation control (RCC) and perturb and observe methods [5]

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Summary

INTRODUCTION

Solar energy becomes one of the most popular areas of renewable energy due to intensive energy demand and several advantages related to availability and cleanness environment [1], [2]. A number of researches synthesized different methods to resolve the problems related to MPPT controller such as power feedback, incremental conductance, short circuit current, open circuit voltage [4], ripple correlation control (RCC) and perturb and observe methods [5]. These traditional MPPT techniques have low equipment requirement and easy structures. The increase in solar radiation causes a slight increase in optimal voltage (Vmp) and augmentation in maximum power point (Pmp) and in optimal current (Imp) as shown in Fig. 1 and 2. the increase in temperature leads to decrease in Vmp and reduction in Imp and in Pmp as demonstrated in Fig. 3 and 4. In order to find the maximum power generated by PV array, a maximum power point controller must be synthesized

IMPROVED PARTICLE SWARM OPTIMIZATION BASED MPPT
RESULTS AND DISCUSSION
CONCLUSION
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