Model predictive control (MPC) has become one of the well-established modern control methods for three-phase inverters with an output LC filter, where a high-quality voltage with low total harmonic distortion (THD) is needed. Although it is an intuitive controller, easy to understand and implement, it has the significant disadvantage of requiring a large number of online calculations for solving the optimization problem. On the other hand, the application of model-free approaches such as those based on artificial neural networks approaches is currently growing rapidly in the area of power electronics and drives. This paper presents a new control scheme for a two-level converter based on combining MPC and feed-forward ANN, with the aim of getting lower THD and improving the steady and dynamic performance of the system for different types of loads. First, MPC is used, as an expert, in the training phase to generate data required for training the proposed neural network. Then, once the neural network is fine-tuned, it can be successfully used online for voltage tracking purpose, without the need of using MPC. The proposed ANN-based control strategy is validated through simulation, using MATLAB/Simulink tools, taking into account different loads conditions. Moreover, the performance of the ANN-based controller is evaluated, on several samples of linear and non-linear loads under various operating conditions, and compared to that of MPC, demonstrating the excellent steady-state and dynamic performance of the proposed ANNbased control strategy.Index Terms-Three-phase inverter, model predictive control, artificial neural network, UPS systems.

In this paper, a simulation model describing the operation of a PV/wind/diesel hybrid microgrid system with battery bank storage has been proposed. Optimal sizing of the proposed system has been presented to minimize the cost of energy (COE) supplied by the system while increasing the reliability and efficiency of the system presented by the loss of power supply probability (LPSP). Novel optimization algorithms of Whale Optimization Algorithm (WOA), Water Cycle Algorithm (WCA), Moth-Flame Optimizer (MFO), and Hybrid particle swarm-gravitational search algorithm (PSOGSA) have been applied for designing the optimized microgrid. Moreover, a comprehensive comparison has been accomplished between the proposed optimization techniques. The optimal sizing of the system components has been carried out using real-time meteorological data of Abu-Monqar village located in the Western Desert of Egypt for the first time for developing this promising remote area. Statistical study for determining the capability of the optimization algorithm in finding the optimal solution has been presented. Simulation results confirmed the promising performance of the hybrid WOA over the other algorithms. INDEX TERMS Isolated microgrids, cost of energy (COE), loss of power supply probability (LPSP), optimization.

The control of inverters with output LC filter has a special importance in applications where a high quality voltage is needed. However, the controller design becomes more difficult. A model predictive control (MPC) is used for voltage control of a three-phase inverter with output LC filter. The controller uses a model of the system to predict the behaviour of the variables for a given voltage vector sequence until a certain horizon of time, then a cost function is used as a criterion for selecting the switching state that will be applied during the next sampling interval. This paper presents the effect of considering different number of prediction steps in terms of THD and the number of cycles or the settling time to reach steady state operation. The simulation results for MPC with only one prediction step and the improved MPC with two prediction steps are presented and compared, under linear and nonlinear loads, using MATLAB/Simulink tools. The simulation results show that the improved MPC improves the THD for nonlinear loads and make it constant for different resistive loads. Moreover, the settling time can be considered constant for various linear and nonlinear loads.