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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics
Mohammad AlShabi
University of Sharjah
Computer Science & IT Electrical & Electronics Engineering Engineering

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Estimating one-diode-PV model using autonomous groups particle swarm optimization Mohammad AlShabi; Chaouki Ghenai; Maamar Bettayeb; Fahad Faraz Ahmad
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 10, No 1: March 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v10.i1.pp166-174

Abstract

In this paper, the one-diode model of a photovoltaic PV solar cell (PVSC) is estimated for an experimental characteristic curves data by using a recently proposed version of the Particle Swarm Optimization (PSO) algorithm, which is known as the Autonomous Groups Particles Swarm Optimization (PSOAG). This meta-heuristic algorithm is used to identify the model of the PVSC. The PSOAG divides the particles into groups and then, uses different functions to tune the social and cognitive parameters of these groups. This is done to show the individuals’ diversity inside the swarm. Although, these individuals do their duties as part of the society, they are not similar in terms of intelligence and ability. By using these groups, the performance of the PSO is improved in terms of convergence rate and escaping the local minima/maxima. Six versions of PSOAG algorithms were developed in this work. Therefore, nine versions of PSOAG, including these six algorithms and three newly developed PSOAG reported previously, will be used in this research to cover more social’s behaviors. The results are compared to the original PSO and other versions of PSO like conventional and Asymmetric Time-varying Accelerated Coefficient PSOs, and the improved PSO. The result shows that the proposed methods improve the performance by up to 14% in terms of root mean squared error and maximum absolute error, and by up to 20% in term of convergence rate, when these were compared to the best results obtained from the other algorithms.
Advanced exponential sliding mode control for microgrid at autonomous and grid-connected modes A. Elnady; Mohammad AlShabi
Bulletin of Electrical Engineering and Informatics Vol 10, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i1.2718

Abstract

This paper introduces a novel control scheme for the operation of multilevel inverters forming a microgrid. The core of the suggested control scheme is an advanced (power-rate) exponential sliding mode controller. This developed controller is robust toward any variation of the system’s parameters and loads in addition to its fast and accurate performance. The presented control scheme provides advantageous characteristics to the microgrid operation in an autonomous mode (microgrid mode) and grid-connected mode. In the microgrid mode, the voltages and frequency are stable at any variable balanced and unbalanced load. In the grid-connected mode, an effective procedure for connecting the microgrid to the main grid is proposed to guarantee a seamless and fast transition to the grid-connected mode. The performance of the presented control scheme along with its proposed controller is validated by comparing its results to another linear and non-linear controllers for the same microgrid loading conditions.
Co-Authors A. Elnady Chaouki Ghenai Fahad Faraz Ahmad Maamar Bettayeb