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Assessment of voltage stability based on power transfer stability index using computational intelligence models Ahmed Majeed Ghadban; Ghassan Abdullah Salman; Husham Idan Hussein
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.pp2790-2797

Abstract

In this paper, the importance of voltage stability is explained, which is a great problem in the EPS. The estimation of VS is made a priority so as to make the power system stable and prevent it from reaching voltage collapse. The power transfer stability index (PTSI) is used as a predictor utilized in a PSN to detect the instability of voltages on weakened buses. A PSI is used to obtain a voltage assessment of the PSNs. Two hybrid algorithms are developed. The (CA-NN) and the (PSO-NN). After developing algorithms, they are compared with the actual values of PTSI NR method. The algorithms installed on the 24 bus Iraqi PS. The actual values of PTSI are the targets needed. They are obtained from the NR algorithm when the input data is Vi, δi, Pd, Qd for the algorithm. The results indicate that a weak bus that approaches voltage collapse and all results were approximately the same. There is a slight difference with the actual results and demonstrated classical methods are slower and less accurate than the hybrid algorithms. It also demonstrates the validation and effectiveness of algorithms (CA-NN, and PSO-NN) for assessing voltage-prioritizing algorithms (CA-NN). The MATLAB utilized to obtain most of the results.
Enhancement the stability of power system using optimal location of FACTS devices Ali Najim Abdullah; Ahmed Majeed Ghadhban; Hayder Salim Hameed; Husham Idan Hussein
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 2: May 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i2.pp648-655

Abstract

This paper proposes a steady-state of the Static Var Compensator (SVC) & Thyristor Controlled Series Capacitor (TCSC) set up for enhancing the damping overall performance and growing the integral clearing time (CCT) of a power network. The indispensable clearing time is carried out through increasing the time fault interval until the gadget loses stability. Increasing the CCT can be contribute to reliability of the safety gadget, decrease the protection machine ranking and cost. In order to attain most enhancement of machine stability via optimizing location, sizing and control modes of SVC and TCSC. Models and methodology for putting and designing shunt FACT’s units SVC (injected reactive strength Q) and series FACT’s devices TCSC (chose capacitive region) are examined in a 6-bus system. Performance factors are described to show validation of SVC and TCSC on extraordinary conditions. It is proven that the SVC is better than TCSC. 
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.