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A Modified Hybrid Alo–Pso-Based Maximum Power Point Tracking for Photovoltaic System

EasyChair Preprint no. 11950

14 pagesDate: February 5, 2024


  A photovoltaic system is a renewable energy system that converts sunlight into electricity. PV systems can be used for various applications, such as powering homes, remote off-grid locations, and providing electricity to utility power grids. PV systems can face several issues that can affect performance and efficiency. Some common problems include shading from trees, buildings, or other objects, which can reduce the amount of sunlight that reaches the PV modules. Temperature: the efficiency of PV modules decreases as the temperature increases; that is why the PV system has non-linear characteristics. Controlling photovoltaic systems is challenging due to their non-linear factors. As a result, the PV system must have a flexible controller that can adapt to changing weather conditions. This paper focuses on enhancing the performance of renewable energy sources by implementing intelligent control techniques. The study aims to apply these techniques to optimize the power output of the PV system under variable weather conditions. The paper proposes a new Maximum Power Point Tracking (MPPT technique called ALO (Ant Lion Optimizer). The proposed technique uses a hybrid ALO and PSO to increase the solar system's efficiency. The results show the proposed hybrid ALO-PSO MPPT algorithm offers an efficient and reliable method for maximizing power output in PV systems under changing environmental conditions.

Keyphrases: Ant Lion Optimization, Maximum Power Point Tracking, Particle Swarm Optimization

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Fanan Alshaikhli},
  title = {A Modified Hybrid Alo–Pso-Based Maximum Power Point Tracking for Photovoltaic System},
  howpublished = {EasyChair Preprint no. 11950},

  year = {EasyChair, 2024}}
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