Robust Partial Feedback Linearizing Stabilization Scheme for Three-Phase Grid-Connected Photovoltaic Systems

Mahmud, M. A.; Pota, H. R.; Hossain, M. J.; Roy, N. K.

doi:10.1109/jphotov.2013.2281721

Cited by 66 publications

(29 citation statements)

References 22 publications

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“…The grid-integrated photovoltaic (PV) system is sequentially being followed as a supplement and an alternative energy source to the conventional fossil fuel generation in order to fulfill the increasing energy demand and to overcome the adverse environmental issues caused by fuel emissions [1]. PV is considered as the most promising and reliable energy source because it is clean, pollution-free, and abundantly available [2].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Feedback Linearization Based NeuroFuzzy Maximum Power Point Tracking for a Photovoltaic System

et al. 2018

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In the current smart grid scenario, the evolution of a proficient and robust maximum power point tracking (MPPT) algorithm for a PV subsystem has become imperative due to the fluctuating meteorological conditions. In this paper, an adaptive feedback linearization-based NeuroFuzzy MPPT (AFBLNF-MPPT) algorithm for a photovoltaic (PV) subsystem in a grid-integrated hybrid renewable energy system (HRES) is proposed. The performance of the stated (AFBLNF-MPPT) control strategy is approved through a comprehensive grid-tied HRES test-bed established in MATLAB/Simulink. It outperforms the incremental conductance (IC) based adaptive indirect NeuroFuzzy (IC-AIndir-NF) control scheme, IC-based adaptive direct NeuroFuzzy (IC-ADir-NF) control system, IC-based adaptive proportional-integral-derivative (IC-AdapPID) control scheme, and conventional IC algorithm for a PV subsystem in both transient as well as steady-state modes for varying temperature and irradiance profiles. The comparative analyses were carried out on the basis of performance indexes and efficiency of MPPT.

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Section: Introductionmentioning

confidence: 99%

Adaptive Feedback Linearization Based NeuroFuzzy Maximum Power Point Tracking for a Photovoltaic System

et al. 2018

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“…Relying on the assumption that the matching conditions are satisfied, a feedback linearization is practically implemented to three-phase grid-connected photovoltaic system in [27], where the boost converter is not used, and the maximum power point tracking (MPPT) is achieved by adjusting the DC-link voltage, therefore, the real PV dynamics is not considered. The shortcoming of the work presented in [26], [27] is that the closed-loop system exhibits zero dynamics, which requires stability analysis. To overcome such a drawback, another model is adopted in [28], where the grid-connected PV system is fully linearized, which means that there is no zero dynamics.…”

Section: Introductionmentioning

confidence: 99%

Experimental Validation of a Robust Continuous Nonlinear Model Predictive Control Based Grid-Interlinked Photovoltaic Inverter

Errouissi¹,

Muyeen²,

Al‐Durra³

et al. 2016

IEEE Trans. Ind. Electron.

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Abstract-The paper presents a robust continuous nonlinear model predictive control (CNMPC) for a grid-connected photovoltaic (PV) inverter system. The objective of the proposed approach is to control the power exchange between the grid and a photovoltaic system, while achieving unity power factor operation. As the continuous nonlinear MPC cannot completely remove the steady-state error in the presence of disturbances, the nonlinear disturbance observer-based control is adopted to estimate the offset caused by parametric uncertainties and external perturbation. The stability of the closed-loop system under both nonlinear predictive control and disturbance observer is ensured by convergence of the output-tracking error to the origin. The proposed control strategy is verified using a complete laboratoryscale PV test-bed system consisting of a photovoltaic emulator, a boost converter, and a grid-tied inverter. High performance with respect to DC-link voltage tracking, grid current control, disturbance rejection, and unity power factor operation has been demonstrated.

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“…[2], [10], [13]- [16]). Nevertheless, good integration of medium or large PV system in the grid may therefore require additional functionality from the inverter, such as control of reactive power.…”

Section: Introductionmentioning

confidence: 99%

Three-phase grid-connected of photovoltaic generator using nonlinear control

Yahya

Fadil

Guerrero

et al. 2014

2014 IEEE Conference on Control Applications (CCA)

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This paper proposes a nonlinear control methodology for three phase grid connected of PV generator. It consists of a PV arrays; a voltage source inverter, a grid filter and an electric grid. The controller objectives are threefold: i) ensuring the Maximum power point tracking (MPPT) in the side of PV panels, ii) guaranteeing a power factor unit in the side of the grid, iii) ensuring the global asymptotic stability of the closed loop system. Based on the nonlinear model of the whole system, the controller is carried out using a Lyapunov approach. It is formally shown, using a theoretical stability analysis and simulation results that the proposed controller meets all the objectives.

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Robust Partial Feedback Linearizing Stabilization Scheme for Three-Phase Grid-Connected Photovoltaic Systems

Cited by 66 publications

References 22 publications

Adaptive Feedback Linearization Based NeuroFuzzy Maximum Power Point Tracking for a Photovoltaic System

Adaptive Feedback Linearization Based NeuroFuzzy Maximum Power Point Tracking for a Photovoltaic System

Experimental Validation of a Robust Continuous Nonlinear Model Predictive Control Based Grid-Interlinked Photovoltaic Inverter

Three-phase grid-connected of photovoltaic generator using nonlinear control

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