This paper describes the importance of FACTS devices; it presents the outcome of the study of its reflectance on the performance of power system networks. It seeks to increase and guarantee the fact and accuracy of response systems under disturbance conditions when the phase measurement units are introduced as Real-Time Measurement (RTM) stations. This paper also describes the importance of FACTS devices. The combination of FACTS devices and PMUs is presented to increase the controllability performance of power systems. This paper demonstrates how PMUs measure voltage, current and their angles. It provides, through a communication link, a Phase Angle Data Concentrator (PDC) to make an appropriate decision to correct the power system state using the FACTS device (TCSC). We utilized the Graph-Theoretic Algorithm to optimize the number and location of PMUs. The technique proposed was tested on the Iraqi National Super Grid’s 24bus network, Diyala City’s regional 10bus network and the 14bus IEEE standard test system. The MATLAB/PSAT package was utilized for the simulation of results. It is evident that our proposed algorithm and technique achieved the purpose of this paper as confirmed by the level of accuracy of the results obtained from most of the cases tested.

This study presented a new hybrid algorithm to improve the state estimation (SE) of radial distribution power systems (PSs). The proposed particle swarm optimization-neural network (PSO-NN) algorithm constructed an independent and fast monitoring system with high accuracy that can detect abnormal conditions or failures in a PS. In this study, PSO was adopted to determine the appropriate weights of the NN model. The speed and accuracy of PSO with the NN model were evaluated in the SE of power system networks (PSNs). The information obtained through SE was used to enhance the operations and customer service delivery in terms of energy consumption and power quality in PSNs. Capacitor banks were installed to reduce the losses and improve the voltage profiles. The PSO-NN algorithm was assessed on IEEE (9, 33, and 69) bus standards. Simulation results proved that the new technique can be tested on any distribution network because of its accurate and efficient SE. Results indicated that the PSO-NN algorithm had better performance than the phasor measurement units.

<p><span>This paper proposes a steady-state of the Static Var Compensator (SVC) &amp; 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. </span></p>

Background & Objective: Harmonic amplification is one of the primary issues in power system networks. The objective of this study is to manage the harmonic event and its significant effects on power quality. A new control approach that uses Artificial Intelligence (AI) is proposed and applied to a Distribution Static Synchronous Compensator (DSTATCOM). DSTATCOM is a FACTS device that can achieve highly effective reactive power compensation to reduce and/or damp the harmonic amplification in power system networks. Results & Conclusion: Simulation results are obtained using the MATLAB/Simulink package. The validity and effectiveness of using the AI approach are proven based on the DSTATCOM FACTs device with linear and nonlinear loads. Analysis results are discussed.

<span>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 V_i, δ_i, P_d, Q_d 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 </span><span>algorithms</span><span> (CA-NN). The MATLAB utilized to obtain most of the results.</span>