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A second-order sliding mode and fuzzy logic control to optimal energy management in wind turbine with battery storage

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Abstract

The optimal control of large-scale wind turbine has become a critical issue for the development of renewable energy systems and their integration into the power grid to provide reliable, secure and efficient electricity, despite any possible constraints such as sudden changes in wind speed. This paper deals with the modeling and control of a hybrid system integrating a permanent magnet synchronous generator (PMSG) in variable speed wind turbine (VSWT) and batteries as energy storage system (BESS). Moreover a new supervisory control system for the optimal management and robust operation of a VSWT and a BESS is described and evaluated by simulation under wind speed variation and grid demand changes. In this way, the proposed coordinated controller has three subsystems (generator side, BESS side and grid side converters). The main function of the first one is to extract the maximum wind power through controlling the rotational speed of the PMSG, for this a maximum power point tracking algorithm based on fuzzy logic control and a second-order sliding mode control (SOSMC) theory is designed. The task of the second one is to maintain the required direct current (DC) link voltage level of the PMSG through a bidirectional DC/DC converter, whereas in the last, a (SOSMC) is investigated to achieve smooth regulation of grid active and reactive powers quantities, which provides better results in terms of attenuation of the harmonics present in the grid courant compared with the conventional first-order sliding controller. Extensive simulation studies under different conditions are carried out in MATLAB/Simulink, and the results confirm the effectiveness of the new supervisory control system.

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Correspondence to Djalel Dib.

Appendix

Appendix

See Tables 4 and 5.

Table 4 PMSG parameters
Table 5 Wind turbine parameters

Nomenclature

 

\(V_{\text{sd}} ,V_{\text{sq}} ,I_{\text{sd}} ,I_{\text{sq}}\)

The direct and quadrature components of the PMSG voltages and currents, respectively

\(R_{\text{s}} ,L_{\text{d}} ,L_{\text{q}}\)

The resistance, the direct and the quadrature inductance of the PMSG, respectively

\(\psi_{m}\)

The magnetic flux

\(T_{\text{e}}\)

The electromagnetic torque

\(\omega_{\text{e}}\)

The electrical rotational speed of PMSG

\(n_{\text{p}}\)

The number of pole pairs

\(V_{\text{dg}} ,V_{\text{qg}} ,I_{\text{dg}} ,I_{\text{qg}}\)

The direct and quadrature components of the grid voltages and currents, respectively

\(V_{\text{di}} , V_{\text{qi}}\)

The inverter voltages components

\(R_{\text{g}} ,L_{\text{dg}} ,L_{\text{qg}}\)

The resistance, the direct and quadrature grid inductance, respectively

\(V_{\text{bat}}\),\(E_{0}\)

The battery rated voltage and the internal EMF, respectively

\(E_{\text{bat\, disch}} ,E_{\text{bat\,charg}}\)

The discharge and charge voltage, respectively

\(R_{i} ,Q\)

The internal resistance and the battery capacity, respectively

\(i_{t} ,i^{*}\)

The actual battery charge and the filtered current, respectively

BESS

The battery energy storage system

WTG

The wind turbine generator

MPP

The maximum power point

FLC

The fuzzy logic controller

SOSMC

The second-order sliding mode control

FOSMC

The first-order sliding controller

WECS

The wind energy conversion system

PMSG

The permanent magnet synchronous generators

MPPT

The Maximum Power Point Tracking

ESS

The energy storage system

TSR

The tip speed ratio

HCS

The hill-climb searching

MSC

The machine side converter

GSC

The grid side converter

BSC

The battery side converter

WT

The wind turbine

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Meghni, B., Dib, D. & Azar, A.T. A second-order sliding mode and fuzzy logic control to optimal energy management in wind turbine with battery storage. Neural Comput & Applic 28, 1417–1434 (2017). https://doi.org/10.1007/s00521-015-2161-z

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