Real-Time Emulation of a Grid-Connected Wind Energy Conversion System Based Double Fed Induction Generator Configuration under Random Operating Modes

Abstract

This paper presents the design, modeling, simulation and the experimental implementation of a 1.5 kW relatively low-cost wind energy conversion system (WECS) based on the double fed induction generator (DFIG) configuration. In the preliminary experiments, we test the DFIG power control under fixe speed by applying the vector control principle, then we insert the physical emulator presented in the controlled DC motor in order to simulate the static-dynamic behaviors of a real wind turbine with the use of the Tip Speed Ratio TSR based MPPT algorithm to extract the maximum available power on the emulator. The proposed structure is simulated using MATLAB Simulink environment, the obtained results are validated experimentally on our laboratory setup. We also develop an application with MATLAB AppDesigner that calculates the operating point of our system at steady state and visualize the power transfer, current, voltage and electromagnetic torque values of the DFIG and the DC motor before starting the stimulation or the experimental manipulation. The MPPT, the DC motor control and the DFIG power control algorithms are implanted in C, embedded on a dSPACE DS1104 control board. The obtained results confirm the reliability of the proposed WECS to manage all the probable operating modes, also the effectiveness of the physical simulator in the role of wind turbine emulation.

Robust Neural Control of Wind Turbine Based Doubly Fed Induction Generator and NPC Three Level Inverter

“…The aerodynamic power P tur captured by the wind turbine is given by [12][13][14][15][16][17][18][19][20][21][22]:…”

“…We present in preferred way the dynamics electrical model of the DFIG-generator in a synchronous reference frame (d, q) rotating at an angular speed of ω s . According to [14][15][16][17][18][19][20][21][22][23], the basic equations used to model the DFIG-generators in the rotating d-q reference frame are written as [24][25][26]:…”

“…The working reference for the control is that related to the rotating field so that the axis (𝑑) coincides with the direction desired flow, which can be rotor, stator, or air gap. Thus, it is possible to orient the different flows of the machine [3,[17][18][19][20][21][22][23][24][25][26][27][28][29].…”

“…As for the output layer, there is only one output, so there is only one cell. We chose only one hidden layer and 12 neurons in the hidden layer [15,17,21]. The convergence of the network in summer obtained by using the value of the parameters grouped in Table 3.…”