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All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Saleh Masoud Abdallah Altbawi
Universiti Teknologi Malaysia
Electrical & Electronics Engineering

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Distant temperature and humidity monitoring: prediction and measurement Farrukh Hafeez; Usman Ullah Sheikh; Attaullah Khidrani; Muhammad Akram Bhayo; Saleh Masoud Abdallah Altbawi; Touqeer Ahmed Jumani
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 3: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i3.pp1405-1413

Abstract

Sensing environmental measuring parameters has a pivotal role in our everyday lives. Most of our daily life activities depend upon environmental conditions. Accurate information about these parameters also helps in several industrial applications like ventilation rate calculation, energy prediction, stock maintenance in warehouses, and saving from harmful conditions. The emergence of machine learning can make it easy to predict such time series problems. This paper describes the design of a remotely controlled robotic car for measuring and predicting humidity and temperature. A customized app for accessing the robotic car is designed to indicate predicted and realtime measured values of humidity and temperature. A sensor installed builtin helps in the measurement. The recurrent neural network (RNN) model is used to predict humidity and temperature. For this purpose, experiments are carried out in both outdoor and indoor settings. Accuracy of 85% and 90% is achieved in an outdoor environment and indoor settings.
Improve power quality of charging station unit using African vulture optimization algorithm Saleh Masoud Abdallah Altbawi; Saifulnizam Abdul Khalid; Ahmad Safawi Mokhtar; Rayan Hamza Alsisi; Zeeshan Ahmad Arfeen; Hussain Shareef; Mehreen Kausar Azam
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5717

Abstract

In recent years, there is growth in acceptance to consume fewer fossil fuels globally and the manufacturing of electric vehicles (EVs) has become more popular. However, the increase in the number of systems connected to the grid that contain EVs with a huge power capacity leads to unstable working in the power system. To assess the stability of the electric charging station several control approaches in AC part and DC parts during charging mode and discharging modes are tested. African vulture optimization algorithm (AVOA) has been utilized to tune the system controllers (proportional integral derivative (PID)/tilt integral derivative (TID) controllers). The superiority of AVOA is confirmed by comparing the performance with the genetic algorithm (GA). Two objective functions have been used i.e. integral time absolute error (ITAE) and integral square time error (ISTE). AVOA-tuned TID controllers using ISTE were found to be the best to contain the frequency deviations. The results have shown of the AC part and DC part is within an acceptable limit recommended by IEEE standard. Further, maximum peak overshoot, undershoot, and settle time obtained by AVOA-tuned PID and TID controllers are found the best. Finally, the improvement of the performance index obtained by AVOA over its counterpart GA is confirmed.
Co-Authors Ahmad Safawi Mokhtar Attaullah Khidrani Farrukh Hafeez Hussain Shareef Mehreen Kausar Azam Muhammad Akram Bhayo Rayan Hamza Alsisi Saifulnizam Abdul Khalid Touqeer Ahmed Jumani Usman Ullah Sheikh Zeeshan Ahmad Arfeen