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The extensive use of renewable energy sources (RESs) in energy sectors plays a vital role in meeting the present energy demand. The widespread utilization of allocated resources leads to multiple usages of converters for synchronization with the power grid, introducing poor power quality. The integration of distributed energy resources produces uncertainties which are reflected in the distribution system. The major power quality problems such as voltage sag/swell, voltage unbalancing, poor power factor, harmonics distortion (THD), and power transients appear during the transition of micro-grids (MGs). In this research, a single micro-grid is designed with PVs, wind generators, and fuel cells as distributed energy resources (DERs). A nonlinear auto regressive exogenous input neural network (NARX-NN) controller has been investigated in this micro-grid in order to maintain the above power quality issues within the specific standard range (IEEE/IEC standards). The performance of the NARX-NN controller is compared with PID and fuzzy-PID controllers. The single micro-grid is extended to design a three-phase large-scale realistic micro-grid structure to test the feasibility of the proposed controller. The realistic micro-grid is verified through addition of line-impedance, communication delay, demand response, and off-nominal situations. The proposed controller is also validated by simulating different test scenarios using MATLAB/Simulink and TMS320-based processor-in-loop (PIL) for real-time implementation.

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In this paper, a low computational, robust nonlinear feedback control is proposed as independent distributed generation controller (IDGC) for doubly fed induction generator (DFIG) based wind power generation system (WPGS). WPGS integration as distributed generation (DG) to grid point of common coupling (PCC) is reflecting high power loss profile in terms of low frequency oscillations under grid operational contingencies and have high instability hazard under unbounded uncertainties like unintentional islanding operation. Thus, to improve the stability margin of DFIG-WPGS integration fast DG dynamic relations are obtained, where instantaneous activereactive power (P-Q) formulation is proposed to avoid unnecessary phase locked loop (PLL) angle (ω) estimation. The feedback path is designed with proposed finite time adaptive backstepping sliding mode control (FTABSMC) for IDGC operation according to ISA-95 standards. The FTABSMC is ensured with bounded/unbounded uncertainty handling capability by incorporating backstepping based dynamic error profile depletion and with enhanced stability margin by finite time sliding surface based error trajectory to equilibrium. Further, the adaptive sliding surface estimation is proposed in terms of dynamic uncertainty (energy fluctuation) for robust unbounded uncertainty handling. The stability improvement is established with small-signal (SS) based closed loop analysis of considered DFIG-WPGS. The uncertainty handling capability is presented thought rigorous case studies in MATLAB based simulation environment and TMS 320 digital signal processor (DSP) based processor-in-loop (PIL) validation. K E Y W O R D S backstepping control, distributed generation, phase locked loop, sliding mode control, wind power generation system 1 | INTRODUCTION To cope with increasing power demand and carbon emission (pollution towards global warming), the renewable energy resource (RES) based distributed generations (DGs) have gained importance in energy market from last few decades. 1 The wind energy (WE) is well utilized as DG for local

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