Implementation of Hybrid Metaheuristic MPPT for Partial Shaded Solar PV System
Overview of the MPPT Algorithms
Algorithms Introduced: The video explores four optimization algorithms:
Particle Swarm Optimization (PSO)
C Search Optimization
Flower Pollination Algorithm (FPA)
Grey Wolf Optimization (GWO)
Understanding the Solar PV System
Panel Configuration: The system consists of three solar panels connected in series, with specific voltage and current characteristics.
Impact of Shading: Partial shading can significantly reduce the efficiency of solar panels, leading to multiple local maxima in the power-voltage curve, complicating the task of extracting maximum power.
Implementation of MPPT Algorithms
PSO Algorithm: The implementation involves initializing parameters, measuring voltage and current, and iteratively updating the duty cycle until the maximum power is achieved.
C Search Optimization: Similar to PSO, it employs a random duty cycle and updates it based on calculated power outputs, utilizing a Lev flight concept for effective optimization.
Flower Pollination Algorithm: This algorithm incorporates biotic and abiotic processes to optimize duty cycles for maximum power extraction.
Grey Wolf Optimization: GWO uses hierarchical structures to guide the search for maximum power, employing a series of mathematical equations to update positions of the agents.
Results and Conclusions
Power Extraction: The results from each algorithm demonstrate their effectiveness in maximizing power output from the solar PV system, even under shading conditions. The performance of PSO, C Search, FPA, and GWO algorithms was showcased, with each successfully achieving the maximum power point.
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