Snehamoy Dhar

This paper focuses on the distributed generation (DG) controller of a PV-based microgrid. An independent DG controller (IDGC) is designed for PV applications to improve Maximum-Power Point Tracking (MPPT). The Extreme-Learning Machine (ELM)-based MPPT method exactly estimates the controller’s reference input, such as the voltage and current at the MPP. Feedback controls employ linear PI schemes or nonlinear, intricate techniques. Here, the converter controller is an IDGC that is improved by directly measuring the converter duty cycle and PWM index in a single DG PV-based MG. It introduces a fast-learning Extreme-Learning Machine (ELM) using the Moore–Penrose pseudo-inverse technique and online sequential ridge methods for robust control reference (CR) estimation. This approach ensures the stability of the microgrid during PV uncertainties and various operational conditions. The internal DG control approach improves the stability of the microgrid during a three-phase fault at the load bus, partial shading, irradiance changes, islanding operations, and load changes. The model is designed and simulated on the MATLAB/SIMULINK platform, and some of the results are validated on a hardware-in-the-loop (HIL) platform.

This paper focuses on distributed generation (DG) controller of a PV based Micro Grid. An independent DG controller (IDGC) is designed for PV applications to improve maximum power point tracking (MPPT) in Micro Grid (MG). Extreme learning machine (ELM) based MPPT method exactly estimate the reference input of converter control. They are voltage and current at MPP. Feedback controls employ linear PI schemes or nonlinear, intricate techniques. Here the converter controller, IDGC is improved by measuring directly converter outputs like duty cycle. PWM index in a single DG PV-based MG. It introduces a fast learning Extreme Learning Machine (ELM) using Moore-Penrose pseudo-inverse and an online-sequential ridge re method for robust CR estimation. The approach ensures the stability of the microgrid during PV uncertainties. Internal DG control approach (IDGC) improves the strength of the Micro Grid during, three-phase faults at load bus, partial shading, irradiance change, islanding operation and load change. The model is designed and simulated in MATLAB/SIMULINK platform and some of the results are validated in hardware in simulation (HIL) platform.

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 active‐reactive 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.

This paper proposes a new Firefly optimized Ridge Extreme Learning Machine (RELM-FF) algorithm based maximum power point tracking (MPPT) investigation for stability study of photovoltaic (PV) interactive microgrid dynamics. The proposed MPPT study is effective by managing minimum uncertainty limits, during solar uncertainty conditions (i.e., inconsistent irradiation, partial shading, etc.), compared with conventional techniques. A two stage converter dynamics is considered for the proposed grid interactive PV system. To withstand stability during worst grid operating scenario (both PV side and grid side uncertainty), a robust nonlinear Lyapunov based finite time sliding mode (LFSM) control is proposed for PV-VSC (voltage source converter) system. As the proposed multiple distributed energy resources based microgrid is considered as weak (low short circuit ratio), and PV is considered as an active power source, the Q-V based state variables are used for the dynamic control loop. A small signal stability analysis with the two stage PV converters is presented using the proposed RELM-FF algorithm and LFSM control. The performance evaluation of the microgrid operating with the PV array is demonstrated through various case scenarios, in MATLAB/Script environment. A hardware validation with TMS320C DSK board and embedded MATLAB coder is performed to establish effectiveness of the proposed MPPT algorithm, in real time. The superiority of the proposed MPPT over the conventional techniques is validated by comparing the stability improvement performance in grid interactive PV-VSC microgrid.

A new direct power control formulation for the voltage source converter (VSC) in a grid-connected photovoltaic (PV) array is discussed in this paper. Instead of controlling the direct- and quadrature-axis currents of the VSC through the use of a phase-locked loop system (PLL), the instantaneous real- and reactive-power components are used as control variables. This approach, therefore, does not take into account the unmodelled dynamics of the PLL resulting in a robust control of the active, reactive powers while maintaining the photovoltaic (PV) array voltage at a constant value. Further, the stability of the grid-connected PV array is enhanced by designing a Lyapunov’s function-based finite-time non-linear reactive power and dc-link voltage controller, which essentially uses the terminal sliding mode approach. To prove the robustness of the proposed approach, several system disturbances like changes in solar insolation and active and reactive power references, islanding conditions, converter parametric changes, and faults on the converter and inverter buses are considered. In all these cases, the new controller is found to enhance overall system stability in comparison to the inferior performance by the proportional-integral controller