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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS)
Ghassan Abdullah Salman
University of Diyala
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Improvement the voltage stability margin of Iraqi power system using the optimal values of FACTS devices Ghassan Abdullah Salman; Hatim G. Abood; Mayyadah Sahib Ibrahim
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i2.pp984-992

Abstract

The detection of potential voltage collapse in power systems is essential to maintain the voltage stability in heavy load demand. This paper proposes a method to detect weak buses in power systems using two stability indices: the voltage stability margin factor (dS/dY) and the voltage collapse prediction index (VCPI). Hence, the paper aims to improve the voltage stability of Iraqi transmission grid by allocating FACTS devices in the optimal locations and optimal sizes. Two types of FACTS are used in this paper which are Thyristor controlled series compensator (TCSC) and static var compensator (SVC). The objective function of the problem is fitted using particle swarm optimization (PSO). The proposed method is verified using simulation test on Diyala-132 kV network which is a part of the Iraqi power system. The results observed that improvement the voltage stability margin, the voltage profile of Diyala-132 kV is increased and the power losses is decreased.
Application of artificial intelligence techniques for LFC and AVR systems using PID controller Ghassan Abdullah Salman; Assama Sahib Jafar; Ammar Issa Ismael
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 10, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (632.611 KB) | DOI: 10.11591/ijpeds.v10.i3.pp1694-1704

Abstract

Development of electrical power systems led to search for  a new mathematical methods to find the values of PID (Proportional-Integral-Derivative) controller. The goal of the paper is to improve the performance of the overall system, through improved the frequency deviation and the voltage deviation characteristics using PID controller, so in this paper are proposed three methods of artificial intelligence techniques for designing the optimal values of PID controller of Load-Frequency-Control (LFC) and Automatic-Voltage-Regulator (AVR), the first is the Firefly Algorithm (FA), the second is the Genetic Algorithm (GA) and the third is the Particle Swarm Optimization (PSO), in addition to these three methods use the conventional (Ziegler–Nichols, Z-N). The FA, GA and PSO are used to obtain the optimal parameters of PID controller based on minimized different various indices as a fitness function, these fitness functions namely Integral-Time-Absolute-Error (ITAE) and Integral-Time-Square-Error (ITSE). Comparison between the results obtained show that FA has better performance to control of frequency deviation and terminal voltage than GA and PSO, so the results observed the FA is more effectual and reliable to determine the optimal values of PID controller.
Implementation Optimal Location and Sizing of UPFC on Iraqi Power System Grid (132 kV) Using Genetic Algorithm Ghassan Abdullah Salman; Mohammed Hasan Ali; Ali Najim Abdullah
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 9, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (621.276 KB) | DOI: 10.11591/ijpeds.v9.i4.pp1607-1615

Abstract

Electric power systems required efficient processors and intelligent methods for sustainability therefore, in this paper used Flexible AC Transmission System (FACTS) device specifically Unified Power Flow Controller (UPFC) because of its useful properties on series and shunt devices and used Genetic Algorithm (GA) to determine the optimal location and values of UPFC to achieve the following objectives: improve voltages profile, reduce power losses, treatment of power flow in overloaded transmission lines and reduce power generation. Consequently, all of these goals led to a reduction in the total cost of the power system. GA was applied to an Iraqi local power grid system (Diyala 132 kV) to find the optimal values and locations of UPFC for the purpose of achieving the objectives mentioned above using the MATLAB program. The simulation results showed the effectiveness of GA to calculate the optimum values and locations of UPFC and promising results were obtained for the Diyala power network (132 kV) with regard to the desired objectives.
Voltage stability assessment prediction using a guide strategy-based adaptive particle swarm optimisation-neural network algorithm Husham Idan Hussein; Hassan Saadallah Naji; Ghassan Abdullah Salman
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 13, No 4: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v13.i4.pp2199-2206

Abstract

In this work, the indicators of electrical power network stability and voltage stability (VS) are discussed and developed with the aim of using a power transfer stability index (PTSI) indicator as a predictor for voltage stability (VS) in electrical power networks. The power transfer stability index (PTSI) was thus used to detect abnormally weak voltages in buses within such power system networks (weak). The target data are obtained using the Newton Raphson method (NR) and include magnitude, phase angle, and active and reactive power. A new adaptive particle swarm optimization-neural network algorithm based on a guiding strategy (GSAPSO-NN) was also used to achieve the goal of the paper by improving the mixed particle updates and the weightings of the neural network to decrease the search time. All results were then compared with actual values as calculated using the PTSI NR method. The final results show only simple differences or approximately the same values using both the proposed and the classical methods. The MATLAB-PSAT package was employed to obtain most of these results and the testing of the new method was done on the IEEE14 bus system as well as the Iraqi 24-bus power system. The effectiveness validation of the new hybrid method for assessing voltage stability was thus achieved.
Co-Authors Ali Najim Abdullah Ammar Issa Ismael Assama Sahib Jafar Hassan Saadallah Naji Hatim G. Abood Husham Idan Hussein Mayyadah Sahib Ibrahim Mohammed Hasan Ali