Performance Enhancement of Photovoltaic Systems Using Parrot Optimization Algorithm-Based Optimal Control Scheme

This paper presents an optimized control strategy for enhancing the low-voltage-ride-through (LVRT) capability of photovoltaic (PV) systems. The proposed method employs a proportional-integral (PI) controller, which is designed using the Parrot Optimization Algorithm (POA). The PV system is connected to the grid via a DC boost chopper and a grid-side inverter. The incremental conductance method is applied to track the maximum power of the PV system. A cascaded control strategy is implemented to control the grid-side inverter. The effectiveness of the POA-PI controller is tested under various symmetrical and asymmetrical fault conditions, demonstrating significant performance improvements. The results are compared with those obtained from a genetic algorithm-PI control system. Numerical simulations are carried out using PSCAD/EMTDC software, illustrating the robustness of the proposed approach.

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Publication Details

Published
2024-12-04
DOI
https://doi.org/10.1109/spies63782.2024.10983438
Primary Topic
Power Systems and Renewable Energy
Type
article
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article

Performance Enhancement of Photovoltaic Systems Using Parrot Optimization Algorithm-Based Optimal Control Scheme

Hany M. Hasanien, Ayedh H. Alqahtani
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Power Systems and Renewable Energy
article

Performance Enhancement of Photovoltaic Systems Using Parrot Optimization Algorithm-Based Optimal Control Scheme

Hany M. Hasanien, Ayedh H. Alqahtani
article en

Abstract

This paper presents an optimized control strategy for enhancing the low-voltage-ride-through (LVRT) capability of photovoltaic (PV) systems. The proposed method employs a proportional-integral (PI) controller, which is designed using the Parrot Optimization Algorithm (POA). The PV system is connected to the grid via a DC boost chopper and a grid-side inverter. The incremental conductance method is applied to track the maximum power of the PV system. A cascaded control strategy is implemented to control the grid-side inverter. The effectiveness of the POA-PI controller is tested under various symmetrical and asymmetrical fault conditions, demonstrating significant performance improvements. The results are compared with those obtained from a genetic algorithm-PI control system. Numerical simulations are carried out using PSCAD/EMTDC software, illustrating the robustness of the proposed approach.

Ain Shams University (EG), Public Authority for Applied Education and Training (KW)
Affordable and clean energy
Openalex Percentile: Top 61%
Power Systems and Renewable Energy
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