A Grid-Connected Solar Photovoltaic System with Predictive Control Strategies considering PSO-MPPT

Yousra IZGHECHE, Tahar BAHI, Amira LAKHDARA

Abstract


Control techniques have become an indispensable solution for electric power producers aiming to inject energy cleanly into traditional distribution networks while complying with current regulations and standards. Specifically, the connection of photovoltaic power plants to the grid is permitted only when specific quality and stability requirements are satisfied. This work contributes to this context by proposing control strategies for essential and unavailable static power converters to connect a photovoltaic system to a three-phase electrical network. The proposed approach employs the particle swarm optimization metaheuristic algorithm with a quadratic criterion-based objective function to control the boost converter for maximum power point tracking of the electric power produced by the photovoltaic generator. The objective is to compare two control strategies to identify the most effective approaches to deliver superior quality and performance. The results obtained demonstrate that the current predictive control strategy utilizing a finite control set model is preferable for selecting the optimal switching state applied to the three-phase three-level inverter, providing superior control performance compared to the alternative voltage-oriented control strategy. Voltage-oriented control and finite control set model predictive control current commands are recommended to select the optimal switching state for the three-level three-phase inverter. Finally, the overall energy conversion chain with the proposed new control configuration is subjected to testing under varying weather conditions, and the analysis of results validates the effectiveness of the adopted approach.

Keywords


Renewable Energy; MPPT, Particle Swarm Optimisation; Voltage Oriented Control; Model Predictive Control .

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References


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DOI (PDF): https://doi.org/10.20508/ijrer.v15i2.14763.g9046

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