Implementation of finite set model predictive current control for shunt active filter

Cherif, Ali Yahia; Hicham, Laib; Barra, Kamel

doi:10.1109/irec.2018.8362482

Cited by 3 publications

(6 citation statements)

References 12 publications

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“…Figure 7 [12] shows the system under study. The load current (i l ) was calculated as the sum of the PAF injection current ( ) and the line current ( ) for the three phases [11][12][13][14]. The voltage equation for each of the three phases can be given as [12,13]:…”

Section: Paf Modelisationmentioning

confidence: 99%

“…where, Sabc=(Sa, Sb, Sc) represent three commutation states of the three branches of the inverter. if=(ifa, ifb, ifc) represent the PAF injected current, they are provided by [14]:…”

Section: Paf Modelisationmentioning

confidence: 99%

“…Vs=(Vsa, Vsb, Vsc) are the 3-phase grid voltages ( without taking into account the passive grid filter) and Vf= (vfa, vfb, vfc)represent the inverter output voltages as given by [14]:…”

Section: Paf Modelisationmentioning

confidence: 99%

“…Then, a cost function must be defined in order to select an optimized controlling action [19][20][21]. Figure 9 illustrates a diagrammatic representation of the Predictive Control Strategy applied to the PAF, where [14]: if * (k) represents the reference harmonic current identified by the diphase method based on the extraction of harmonics with Adaline in the DQ reference frame. if(k) represent the m measured values at time k and if(k+1) represent the predicted m-state values corresponding to n switching states possible at time k+1.…”

Section: Predictive Current Control Applied To Pafmentioning

confidence: 99%

“…For the implementation in real time, predictions in two steps k+1, k+2 will be used in order to compensate the time delay within the measurement chain. Predicted harmonic currents (also called filtered currents) in the three phases have been given in [14,22] as follow:…”

Section: Predictive Current Control Applied To Pafmentioning

confidence: 99%

See 4 more Smart Citations

A New Control Stratum Applied to Two Adaptation Stages Based on Adaline-Type Neuronal Predictive Control in a Photovoltaic Solar Conversion Chain

Chtouki¹,

Wira²,

Zazi³

et al. 2020

EJEE

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In order to better adapt to the variation in solar irradiation and to improve the efficiency of the photovoltaic generator, i.e. to maximize the power delivered to the grid. Several criteria's for optimizing the efficiency of the photovoltaic system have been applied. Among them, the algorithms for tracking the optimal operating point of the photovoltaic panels that called Maximum Power Point Tracking (MPPT). In this article, a PV generator (GPV) has been connected to the power grid, as a result, direct consequence is in the deterioration of the voltage wave and thus the quality level of the energy supplied to the consumers. To overcome these problems of harmonic pollution, active power filtering is proposed as an efficient solution to improve grid power quality. This paper therefore proposes to examine the characteristics of an association between a photovoltaic generator (PVG) that aims at injecting active power into the electrical grid and a parallel active filter that has the task of eliminating disturbances present in this grid. The theory of the twophase method with Adaline harmonic extraction is applied for the extraction of the reference currents according to the DQ reference frame. Finite set mode predictive current control (FS-MPCC) applied on PAF has been proposed in order to compensate undesirable harmonic, and reactive power resulting from a non-linear load. A Global Maximum Power Point Tracking (GMPPT) algorithm based Adaline method has been suggested for extracting power from PVG. A simulation under Matlab/Simulink of the global system proves the robust performance capability of the suggested Adaline Neuro-Predictive (ANP) control to simultaneously provide harmonic current compensation, power factor correction and solar power energy injection into the grid.

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Section: Paf Modelisationmentioning

confidence: 99%

“…where, Sabc=(Sa, Sb, Sc) represent three commutation states of the three branches of the inverter. if=(ifa, ifb, ifc) represent the PAF injected current, they are provided by [14]:…”

Section: Paf Modelisationmentioning

confidence: 99%

“…Vs=(Vsa, Vsb, Vsc) are the 3-phase grid voltages ( without taking into account the passive grid filter) and Vf= (vfa, vfb, vfc)represent the inverter output voltages as given by [14]:…”

Section: Paf Modelisationmentioning

confidence: 99%