期刊论文详细信息
卷:9
Improved MPPT Control Strategy for PV Connected to Grid Using IncCond-PSO-MPC Approach
Article
关键词: POWER POINT TRACKING;    MODEL-PREDICTIVE CONTROL;    SYSTEMS;    HYBRID;    ALGORITHMS;    OPTIMIZATION;    INTELLIGENCE;   
DOI  :  10.17775/CSEEJPES.2021.08810
来源: SCIE
【 摘 要 】

This paper proposes a new hybrid maximum power point tracking (MPPT) control strategy for grid-connected solar systems based on Incremental conductance-Particle Swarm Optimization and Model Predictive Controller (IncCond-PSO-MPC). The purpose of the suggested method is to create as much power as feasible from a PV system during environmental changes, then transfer it to the power grid. To accomplish this, a hybrid combination of incremental conductance (IncCond) and particle swarm optimization (PSO) is proposed to locate maximum power, followed by model predictive control (MPC) to track maximum power and control the boost converter to achieve high performance regardless of parameter variations. A two-level inverter, likewise, controlled by Model Predictive Control, is employed to inject the PV power generated. In this application, the MPC is based on minimizing the difference between the reference and prediction powers, which is computed to select the switching state of the inverter. The proposed system is simulated and evaluated in a variety of dynamic conditions using Matlab/Simulink. Results reveal that the proposed control mechanism is effective at tracking the maximum power point (MPP) with fewer power oscillations.

【 授权许可】

   

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