IEEE Transactions on Power Electronics · 2017 · 114 citations · 54 references
EngineeringElectrical EngineeringPower ElectronicsRenewable Energy IntegrationRenewable Energy SystemsConverter TopologiesModel Predictive ControlPower Electronics For Renewable EnergyRenewable Energy Power ConversionSolar Energy SystemsSolar Photovoltaic SystemsDynamic Performance AnalysisMaximum Power Point TrackingMaximum Power Point Tracking AlgorithmsPhotovoltaic Energy SystemsPhotovoltaic InvertersPhotovoltaic SystemsPower Conversion Control StrategiesPower Conversion For Photovoltaic Systems
The main objective of this work is to provide an overview and evaluation of discrete model-predictive control (MPC)-based maximum power point tracking (MPPT) for photovoltaic systems. A large number of MPC-based MPPT methods have been recently introduced in the literature with very promising performance; however, an in-depth investigation and comparison of these methods has not been carried out yet. Therefore, this paper has set out to provide an in-depth analysis and evaluation of MPC-based MPPT methods applied to various common power converter topologies. The performance of MPC-based MPPT is directly linked with the converter topology, and it is also affected by the accurate determination of the converter parameters; sensitivity to converter parameter variations is also investigated. The static and dynamic performance of the trackers is assessed according to the EN 50530 standard, using detailed simulation models, and validated by experimental tests. The analysis in this work aims to present useful insight for practicing engineers and academic researchers when selecting the maximum power point tracker for their application.
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