ArticleSensors (Basel, Switzerland)2021
Promising MPPT Methods Combining Metaheuristic, Fuzzy-Logic and ANN Techniques for Grid-Connected Photovoltaic.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed.
- A Fuzzy Fishier Mantis Optimizer method for MPPT in PV solar system.Scientific reports · 2026Article
- Adaptive MPPT control for reliable transitions between grid connected and islanded operations in PV battery microgrids.Scientific reports · 2026Article
- Feasibility of a Center of Mass Based Fuzzy-Logic Phase Detection Algorithm for Post-Spinal Cord Injury Gait.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2026Article
- A smart single stage solar battery driven desalination system with hybrid MPPT and optimal control for brackish water treatment.Scientific reports · 2025Article
- Extraction of PEM fuel cell variables based on modified hippopotamus optimization algorithm.Scientific reports · 2025Article
- Comparative analysis of reinforcement learning and artificial neural networks for inverter control in improving the performance of grid-connected photovoltaic systems.Scientific reports · 2025Article
- Numerical modeling and neural network optimization for advanced solar panel efficiency.Scientific reports · 2025Article
- A new neuro-fuzzy controller based maximum power point tracking for a partially shaded grid-connected photovoltaic system.Heliyon · 2024Article
- An efficient MPPT techniques for inter-harmonic reduction in grid connected hybrid wind and solar energy systems.Heliyon · 2024Article
- Maximum Power Point Tracking-Based Model Predictive Control for Photovoltaic Systems: Investigation and New Perspective.Sensors (Basel, Switzerland) · 2022Article
- Energy Management Strategy for an Autonomous Hybrid Power Plant Destined to Supply Controllable Loads.Sensors (Basel, Switzerland) · 2022Article
- Artificial Neural Networks in MPPT Algorithms for Optimization of Photovoltaic Power Systems: A Review.Micromachines · 2021Review
- Irradiance Sensing through PV Devices: A Sensitivity Analysis.Sensors (Basel, Switzerland) · 2021Article
- Proposed ANFIS Based Approach for Fault Tracking, Detection, Clearing and Rearrangement for Photovoltaic System.Sensors (Basel, Switzerland) · 2021Article
- Towards Precise Interpretation of Oil Transformers via Novel Combined Techniques Based on DGA and Partial Discharge Sensors.Sensors (Basel, Switzerland) · 2021Article
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4 authors.
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Abstract
This paper addresses the improvement of tracking of the maximum power point upon the variations of the environmental conditions and hence improving photovoltaic efficiency. Rather than the traditional methods of maximum power point tracking, artificial intelligence is utilized to design a high-performance maximum power point tracking control system. In this paper, two artificial intelligence-based maximum power point tracking systems are proposed for grid-connected photovoltaic units. The first design is based on an optimized fuzzy logic control using genetic algorithm and particle swarm optimization for the maximum power point tracking system. In turn, the second design depends on the genetic algorithm-based artificial neural network. Each of the two artificial intelligence-based systems has its privileged response according to the solar radiation and temperature levels. Then, a novel combination of the two designs is introduced to maximize the efficiency of the maximum power point tracking system. The novelty of this paper is to employ the metaheuristic optimization technique with the well-known artificial intelligence techniques to provide a better tracking system to be used to harvest the maximum possible power from photovoltaic (PV) arrays. To affirm the efficiency of the proposed tracking systems, their simulation results are compared with some conventional tracking methods from the literature under different conditions. The findings emphasize their superiority in terms of tracking speed and output DC power, which also improve photovoltaic system efficiency.
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