An internal model control for enhanced grid-connection of direct-driven PMSG-based wind generators

Barros, Luciano Sales; Barros, Camila Mara Vital

doi:10.1016/j.epsr.2017.06.014

Cited by 50 publications

(17 citation statements)

References 15 publications

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“…In this paper, the two tasks have been performed by VSC and BC including optimization techniques, meaning FRT capability realization to improve the dynamic performance of PMSG [14]. There are many statistical and conventional techniques like Taguchi technique, response surface method (RSM) [24], artificial neural network (ANN) [12,25] and affine projection algorithm (APA) [14] where are applied for fine-tuning the PI controller employed in the regulatory system for different power system components. But, these techniques depend on the initial values, so meta-heuristic algorithms such as PSO [26] Figure 8 illustrates the steps needed to find the best solution and the three proposed techniques…”

Section: Frt Capability Realization For Pmsg With Bcmentioning

confidence: 99%

Enhancing the dynamic performance of a wind-driven PMSG implementing different optimization techniques

2020

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Quick transient and smooth stable-state output of permanent magnet synchronous generator (PMSGs) is crucial for sustained power generation and grid code fulfillment specifically the fault ride-through (FRT) capability. Optimization techniques such as gray wolf optimizer (GWO), particle swarm optimizer (PSO) and whale optimizer algorithm (WOA) are proposed to realize a fast transient response and smooth operation of the PMSG. The proposed algorithms for machineside converter are used to get the optimum power generated. Braking chopper (BC) was chosen as a solution for achieving the FRT for PMSG. The studied cases are the three-step wind speed change and symmetrical fault contingencies. In the first case, PSO gives better performance compared with conventional proportional integral, while in the second case, GWO and WOA give a better performance than PSO. GWO delivers the best output in the case of symmetrical fault compared to the WOA. MATLAB/Simulink environment is used to demonstrate the effectiveness of the proposed GWO technique including BC for improving the PMSG dynamic performance.

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Section: Frt Capability Realization For Pmsg With Bcmentioning

confidence: 99%

Enhancing the dynamic performance of a wind-driven PMSG implementing different optimization techniques

2020

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“…It is established by dual control loops, which the outer one is responsible on regulating the DC‐link voltage and other one is employed to inject the active power from the MSC into the UG at UPF as shown in Figure . Grid inverter voltages in connection points and the GSC voltages are formulated as follows:

([], \begin{matrix} V_{ia} \\ V_{ib} \\ V_{ic} \end{matrix}) = ([], R_{f}) ([], \begin{matrix} i_{fa} \\ i_{fb} \\ i_{fc} \end{matrix}) + ([], \begin{matrix} \overset{λ_{a}}{true} \\ \overset{λ_{b}}{true} \\ \overset{λ_{c}}{true} \end{matrix}) + ([], \begin{matrix} V_{ga} \\ V_{gb} \\ V_{gc} \end{matrix}),

where R f and L f are diagonal matrices,

\overset{λ_{a}}{true} = L_{f} \frac{d i_{fa}}{dt}

\overset{λ_{b}}{true} = L_{f} \frac{d i_{fb}}{dt}

, and

\overset{λ_{c}}{true} = L_{f} \frac{d i_{fc}}{dt}

. By using phase‐lag locker (PLL) to find the grid‐voltage angle so that the d‐q axis components of the GSC become

([], \begin{matrix} V_{id} \\ V_{iq} \end{matrix}) = ([], r_{f}) ([], \begin{matrix} i_{fd} \\ i_{fq} \end{matrix}) + ([], \begin{matrix} \overset{λ_{italicfd}}{true} - ω_{g} ψ_{fq} \\ \overset{λ_{italicfq}}{true} + ω_{g} ψ_{fd} \end{matrix})

…”

Section: Grid‐side Convertermentioning

confidence: 99%

Model predictive speed control of five‐phase permanent magnet synchronous generator‐based wind generation system via wind‐speed estimation

Mousa

Youssef

Mohamed

2019

Int Trans Electr Energ Syst

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Summary Accurate wind‐speed measure along with an effective control technology is an important aspect to attain optimal wind power. This paper proposes a sensorless maximum power point tracking (MPPT) algorithm that estimates the effective wind speed without an anemometer to reduce wind‐turbine installation cost and improve the overall efficiency. This algorithm depends on the aerodynamic torque power coefficient approximation to the third‐order polynomial. This paper investigates different control schemes of a 1.5‐MW grid‐tied five‐phase permanent magnet synchronous generator (PMSG) based, a variable‐speed wind‐energy conversion system (VS‐WECS). To eradicate the limitations of the proportional‐integral (PI) controller as a speed controller, model predictive controller (MPC) is implemented as a replacement of PI controller. The MPC is employed to track the rotor speed to the optimal speed. Both the PI and the MPC are designed and deliberated to satisfy the obedient performance of the speed control loop. Moreover, a comparative study of speed control schemes is performed between the conventional PI controller and the MPC. Performance of the proposed control schemes is validated using the MATLAB/SIMULINK. Simulation results show the superiority of MPC compared with the conventional PI controller and the validity of the MPC as a vital solution for drawbacks of the PI controller.

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“…The DC‐link loop adjusts capacitor voltage to a constant value. Alternatively, the grid current loop coordinates grid current to ensure injecting the real power into the UG by forcing the q ‐axis grid current component is zero . Equations of grid voltage terminals are expressed in relations to the voltage and current of the converter as

([], \begin{matrix} V_{ia} \\ V_{ib} \\ V_{ic} \end{matrix}) = ([], R_{f}) ([], \begin{matrix} i_{fa} \\ i_{normalf b} \\ i_{fc} \end{matrix}) + ([], \begin{matrix} \overset{λ_{a}}{true} \\ \overset{λ_{b}}{true} \\ \overset{λ_{c}}{true} \end{matrix}) + ([], \begin{matrix} V_{ga} \\ V_{gb} \\ V_{gc} \end{matrix}),

where R f and L f are diagonal matrices,

\overset{λ_{a}}{true} = L_{f} \frac{d i_{fa}}{dt}

\overset{λ_{b}}{true} = L_{f} \frac{d i_{fb}}{dt},

and

\overset{λ_{c}}{true} = L_{f} \frac{d i_{fc}}{dt}

.…”

Section: Wecs Control Schemesmentioning

confidence: 99%

“…Alternatively, the grid current loop coordinates grid current to ensure injecting the real power into the UG by forcing the q-axis grid current component is zero. 41 Equations of grid voltage terminals are expressed in relations to the voltage and current of the converter as…”

Section: Gsc Control Systemmentioning

confidence: 99%

Study of robust adaptive step‐sizes P&O MPPT algorithm for high‐inertia WT with direct‐driven multiphase PMSG

Mousa

Youssef

Mohamed

2019

Int Trans Electr Energ Syst

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Summary In this study, an efficient robust adaptive perturb and observe (RA‐PO) maximum power point tracking (MPPT) algorithm–based wind energy conversion system (WECS) is suggested to avoid drawbacks of conventional P&O (CPO) algorithms. It depends on observing the distance between the actual and optimal rotor speed, calculating the required adaptive ratio at each operating point, perturbing the rotor speed with an appropriate step‐size, and observing power variations until the P‐ω curve slope equals zero. Therefore, it exhibits a rapid speed tracking with low oscillations. Moreover, it offers a well‐defined relationship among the extracted mechanical power, the rotor speed, the perturbing step‐size, and the operating wind speed so wrong direction and loss of tracking problems can be avoided on high‐inertia wind turbine (WT) during rapid wind speed fluctuations. It improves the WECS efficiency from 87% to 91%. The performance of WECS is confirmed via MATLAB/SIMULINK.

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An internal model control for enhanced grid-connection of direct-driven PMSG-based wind generators

Cited by 50 publications

References 15 publications

Enhancing the dynamic performance of a wind-driven PMSG implementing different optimization techniques

Enhancing the dynamic performance of a wind-driven PMSG implementing different optimization techniques

Model predictive speed control of five‐phase permanent magnet synchronous generator‐based wind generation system via wind‐speed estimation

Study of robust adaptive step‐sizes P&O MPPT algorithm for high‐inertia WT with direct‐driven multiphase PMSG

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