The widely used PI-controller imposes certain performance limitations when used for the grid-connected VSC systems. Model predictive controllers (MPC) can eliminate these inherent issues of PI-controller but in trade-off with an increased computational burden. Research focuses extensively on finding an intermediate solution by employing artificial intelligence (AI) techniques. This paper discusses the implementation and performance of an artificial neural network (ANN) as an inner current controller. Firstly, the PI and MPC schemes are implemented as a supervisory controller for the grid-connected VSC system. Afterwards, a feed-forward ANN structure is trained with the data set of PI and MPC schemes. The resulted ANN structures are termed ANN-PI and ANN-MPC, respectively. For a fair comparison, Levenberg-Marquardt based backpropagation algorithm is used to train both the ANN controllers with the same number of neurons and hidden layers. All four controllers are implemented in the Matlab/Simulink environment to analyze the performance under different dynamic test scenarios. Further, the performance of all the controllers is evaluated using the OPAL-RT based real-time simulator.

The standard vector control is widely used for grid-connected voltage source converters (VSCs), however, the inability to satisfactorily operate at the desired level under different dynamic scenarios and grid conditions limit its application. This paper presents an artificial neural network (ANN) based vector control for the grid-connected VSCs. The Multilayer Perceptron-Recurrent Neural Network (MP-RNN) approach is used in this work which generates the reference current for the current controller of the VSC. To verify the effectiveness of the proposed control, the MP-RNN-based vector control is implemented for a grid-connected VSC in the MATLAB/Simulink environment and the MP-RNN structure is trained by the Levenberg-Marquardt based backpropagation algorithm. Simulation results are presented and compared with the vector control with and without the proposed ANN-aided control. The results clearly show that the proposed control has a better dynamic performance in damping the oscillation introduced by the dc-link dynamics of the VSC. Further, the dynamic performance of the proposed control has been verified with a model implemented in the OPAL-RT environment considering different dynamic test cases.

Model predictive control (MPC) as a current controller has gained attention in a grid-connected power electronic converter system. The multi-objective predictive control is in greater demand when the photovoltaic (PV) sources are integrated with the utility grid since the inverter alone must ensure all of the control objectives such as grid current following, constant power factor operation and accurate maximum power point tracking (MPPT) performance. In this regard, this paper aims to implement the multi-objective Finite Set Control (FCS) - MPC for a single-stage grid-connected PV system considering the two-stage system is less cost-effective, more loss and less reliable. Moreover, the classical MPPT fails to extract the maximum power under fluctuating and shaded environmental condition. Therefore, an improved MPPT algorithm is proposed in this work which is again combined with the multi-objective FCS-MPC to ensure the extraction of the maximum power from the PV and good transient performance of the grid-side voltage and current. Two different approaches for the dc-voltage tracking are compared, one is implemented with an outer-loop proportional integral controller and the second one is implemented directly in the MPC objective function. The output findings clearly show the single-stage PV system with the proposed control can ensure a fast and accurate maximum power tracking and maintenance of stable output signal throughout all the transient conditions.

In this paper, a novel Robust-Synchronization-Loop (RSL) is proposed to track the phase and frequency of the grid voltage. The method can be widely applied to the grid-connected converters in integration of distributed generations (DGs). The detailed analytical model and the parameter tuning based on a small-signal model of the RSL are presented. It is shown that the eigenvalues associated with the RSL remain always on the left half-plane, thus, it provides better stability property with the grid-connected DG converters. In order to show the effectiveness of the proposed RSL, simulation results are provided for different scenarios of the grid conditions. The results show that the proposed method effectively tracks the phase and frequency of the grid voltage and maintains the good synchronism of the DG converters during these different small and large disturbances in the power system.

This paper presents a new anti-islanding protection (AIP) scheme for inverters in integration of distributed generation (DG) sources into the grid. The main advantage of this proposed AIP scheme is that it can be embedded into the control of DG inverters without a need of additional part in the hardware of the inverter and any change in the controller. The AIP scheme does not rely on a communication network. It detects the islanding condition based on continuous monitoring of the active power, the reactive power, and the voltage magnitude mismatch, which is shown to be an alternative to the grid impedance measurement technique. The AIP scheme isolates the inverter from the grid after the grid experiences an islanding condition for all possible scenarios of islanding. A detailed modeling of its implementation in a DG inverter is presented and the performance of the AIP scheme is verified by simulations and experiments.

This paper presents a control-loop stability analysis and parameter design of the grid-connected virtual synchronous machine (VSM) inverters that enables the VSM operate in a very weak grid condition. In order to study the stability and design the parameters, a line-frequency-averaged small-signal model of the VSM inverter has been derived. A transfer function of the control-loop has been obtained, including the coupling resulting from the inherent nature of the VSM as both active power and reactive power related to the voltage and frequency. An example of parameter design is presented by using the derived model. It is shown that the designed parameters ensure the stability and robustness of the VSM inverters connected into a weak grid with a wide range of the grid impedance variation.