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All Journal International Journal of Applied Power Engineering (IJAPE) Bulletin of Electrical Engineering and Informatics
Saifulnizam Abdul Khalid
Universiti Teknologi Malaysia
Electrical & Electronics Engineering

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Optimal Placement of D-STATCOM Using Hybrid Genetic and Ant Colony Algorithm to Losses Reduction Askar Bagherinasab; Mahmoud Zadehbagheri; Saifulnizam Abdul Khalid; Majid Gandomkar; Naziha Ahmad Azli
International Journal of Applied Power Engineering (IJAPE) Vol 2, No 2: August 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (156.802 KB) | DOI: 10.11591/ijape.v2.i2.pp53-60

Abstract

In this work, a modern algorithm by hybrid genetic algorithm and ant colony algorithm is designed to placement and then simulated to determine the amount of reactive power by D-STATCOM. Also this method will be able to minimize the power system losses that contain power loss in transmission lines. Furthermore, in this design a IEEE 30-bus model depicted and three D-STATCOM are located in this system according to Economic Considerations. The optimal placement of each D-STATCOM is computed by the ant colony algorithm. In order to optimize placement for each D-STATCOM, two groups of ant are selected, which respectively located in near nest and far from the nest. Moreover, for every output simulation of D-STATCOM that is used to produce or absorb of reactive power, a genetic algorithm to minimizing the total network losses is applied. Finally, the result of this simulation shows net losses reduction about 150% that it verifies the new algorithm performance.
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 Askar Bagherinasab Hussain Shareef Mahmoud Zadehbagheri Majid Gandomkar Mehreen Kausar Azam Naziha Ahmad Azli Rayan Hamza Alsisi Saleh Masoud Abdallah Altbawi Zeeshan Ahmad Arfeen