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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI)
Chaouki Ghenai
University of Sharjah
Computer Science & IT Electrical & Electronics Engineering Engineering

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Experimental study of the impact of dust on azimuth tracking solar PV in Sharjah Mohamed A. M. Abdelsalam; Fahad Faraz Ahmad; Abdul-Kadir Hamid; Chaouki Ghenai; Oussama Rejeb; Monadhel Alchadirchy; Waleed Obaid; Mamdouh El Haj Assad
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp3671-3681

Abstract

Dust is one of the significant constraints in utilizing solar photovoltaic systems under harsh weather conditions in the desert regions due to creating a shadow that blocks solar irradiance from reaching solar cells and consequently, significantly reducing their efficiency. In this research, experimental study was performed to comprehend the nature of dust particles and their impact on the electrical power output that is generated from azimuth tracking solar PV modules under Sharjah environmental conditions in winter season. According to laboratory experiments, the power losses are linearly related to the dust accumulated density on the surface of the solar panel with a slope of 1.27% per g/m2. The conducted Outdoor studies revealed that the absolute reduction in output power increased by 8.46% after 41 continuous days with one low-intensity rainy day. The linear relationship obtained from indoor experiments was applied later to estimate the dust deposited density on the outdoor setup. The results showed that a regular cleaning process every two weeks is recommended to maintain the performance and to avoid the soiling loss. This work will help engineers in the solar PV plants to forecast the dust impact and figure out the regularity of the cleaning process in case of single axis tracking systems.
Solar/wind pumping system with forecasting in Sharjah, United Arab Emirates Waleed Obaid; Abdul-Kadir Hamid; Chaouki Ghenai
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i4.pp2752-2759

Abstract

This paper demonstrates a water pumping hybrid power system design. The proposed system was designed for water related applications in Sharjah (Latitude 25.29 °N and Longitude 55 °E), United Arab Emirates. The proposed water hybrid system has two primary renewable power systems: solar PV panels and wind turbines. The proposed hybrid system considers the changes in weather conditions (humidity, wind speed, and temperature) since wind speed affects the performance of the wind turbines and solar panels are affected by solar irradiance. The following components are involved in the proposed design: battery (to store the power from solar panels), voltage regulator circuit (for getting stable DC voltage), three-phase rectifier (to convert the reduced AC voltage to DC), three-phase transformer (for reducing the obtained AC voltage), and DC electric motor (the main output of the proposed water pumping system). The proposed water pumping system relies on neural network blocks to achieve weather forecasting by obtaining solar irradiance values from the input temperature, wind speed, and humidity in a span of five years. Both MATLAB and Simulink are used simulate the performance of the proposed system under different weather conditions by changing the values according to the measured weather conditions values over five years.
Hybrid solar/wind/diesel water pumping system in Dubai, United Arab Emirates Waleed Obaid; Abdul-Kadir Hamid; Chaouki Ghenai
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2062-2067

Abstract

This paper proposes a hybrid power system design for water pumping system in Dubai (Latitude 25.25 °N and Longitude 55 °E), United Arab Emirates using solar photovoltaic (PV) panels, wind turbines, and diesel generator. The proposed design considers the changes in weather conditions (humidity percentage, temperature in celsius, and wind speed in m/s) that directly affect solar irradiance values which alter the performance of the hybrid system. The proposed design deals with the problem of rare rainy days in Dubai between December and March and the high temperature throughout the year since that makes providing water to rural and isolated zones essential. The proposed system uses voltage regulator to maintain stable DC voltage from the solar power system, battery bank to store the voltage from solar PV panels, three-phase rectifier to convert the AC voltage from wind power system to DC, three-phase step-down transformers to reduce the AC voltage of the wind turbine and diesel generator, and DC electric motor for water pumping output. The system used neural network for solar irradiance forecasting over an interval of 10 years (from 2009 to 2019). The proposed system will be demonstrated using Simulink to show the stability and performance under different weather conditions.
Design of a thermoelectric energy source for water pumping applications: A case study in Sharjah, United Arab Emirates Waleed Obaid; Abdul-Kadir Hamid; Chaouki Ghenai; Mamdouh El Haj Assad
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i6.pp4751-4758

Abstract

There are many water pumping power systems that exist nowadays relying on conventional and renewable energy sources such as mechanical windmills, solar photovoltaic (PV) panels, wind turbines, and diesel generators. Few designs utilize thermoelectric modules for the purpose of enhancing the reliability and the performance of the system in order to provide water supply to isolated zones continuously. The use of thermoelectric (TE) modules is increasing due to their reduced prices and the possibility of using them in different applications depending on the required specifications of motors and other connected loads. This paper proposes a renewable energy system design for water pumping applications in Sharjah (Latitude 25.29°N and Longitude 55°E), United Arab Emirates. The system involves TE modules for operating the three-phase AC water pumping motor, voltage regulator, voltage boost converter, and three-phase power inverter while considering the changes of temperature values which affect the performance of the thermoelectric generator (TEG) modules. The aim is integrating TEG modules to cover the increasing demand of water in rural areas since rainy days in Sharjah are limited and the temperature is high. The performances of the proposed system will be demonstrated using Simulink simulations for the overall blocks of the proposed system.
Estimating PV models using multi-group salp swarm algorithm Mohammad Al-Shabi; Chaouki Ghenai; Maamar Bettayeb; Fahad Faraz Ahmad; Mamdouh El Haj Assad
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 10, No 2: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v10.i2.pp398-406

Abstract

In this paper, a multi-group salp swarm algorithm (MGSSA) is presented for estimating the photovoltaic (PV) solar cell models. The SSA is a metaheuristic technique that mimics the social behavior of the salp. The salps work in a group that follow a certain leader. The leader approaches the food source and the rest follows it, hence resulting in slow convergence of SSA toward the solution. For several groups, the searching mechanism is going to be improved. In this work, a recently developed algorithm based on several salp groups is implemented to estimate the single-, double-, triple-, Quadruple-, and Quintuple-diode models of a PV solar cell. Six versions of MGSSA algorithms are developed with different chain numbers; one, two, four, six, eight and half number of the salps. The results are compared to the regular particle swarm optimization (PSO) and some of its newly developed forms. The results show that MGSSA has a faster convergence rate, and shorter settling time than SSA. Similar to the inspired actual salp chain, the leader is the most important member in the chain; the rest has less significant effect on the algorithm. Therefore, it is highly recommended to increase the number of leaders and reduce the chain length. Increasing the number of leaders (number of groups) can reduce the root mean squared error (RMSE) and maximum absolute error (MAE) by 50% of its value.
Co-Authors Abdul-Kadir Hamid Fahad Faraz Ahmad Maamar Bettayeb Mamdouh El Haj Assad Mohamed A. M. Abdelsalam Mohammad Al-Shabi Monadhel Alchadirchy Oussama Rejeb Waleed Obaid