In this paper, shunt active power filter (SAPF) is designed to address the problem of current harmonics in the source current arising from a nonlinear load and improve the quality of electric power. That will be by compensating reactive power and harmonic currents. The PI controller responsible for DC-link energy storage tuning was developed using the Lévy flight distribution algorithm (LFA). It is a novel, previously unused optimization approach to suggest relative gain Kp and integration gain Ki gain values for the PI controller. This approach aims to get the best dynamic performance of SAPF, speed up the convergence rate, get the fastest best stability and bypass constant voltage advancement for DC-link. The model was tested and implemented in MATLAB simulation software. The result of total harmonic distortion THD showed the efficiency of this method compared with the results of traditional PI. The design of the model in the current reference frame was based on instantaneous reactive power (pq) theory.

No abstract

No abstract

This paper presented a smartness 2-D lookup table (2-DLT) control by means of adaptation gain to develop a frequency controller and facilitate the power-sharing requirements in an isolated micro-grid system. This intelligence of an expert controller adopts the scale of adaptation gain for estimating control design. Synchronous power generators are commonly used to provide power to distant and isolated regions where grid expansion is expensive due to economic and technical constraints. Load frequency control (LFC) technology challenges to guarantee the reliability and stability regarding the system. It is known that conventional control methods are unreliable due to frequency variation and sudden changes in the load or failure generation. Traditional control and criteria may not be appropriate for the new structural networks, such as micro-grid. In this work, the performance of the proposed 2-DLT controller is examined and compared to the classical proportional integral (PI) controller and artificial neural network (ANN). The simulation system is implemented and tested using MATLAB/Simulink.

No abstract