A smart grid could generate and distribute electricity effectively economically, securely and sustainably. It offers customers more information and choice, including the export of energy to the grid, demand-side participation and energy efficiency. However, to implement a smart grid into the Iraqi power system, various challenges should be faced, especially concerns related to understanding the contents and features of this network compared with the traditional Iraqi network. As well as the challenges and risks of implementing the smart grid itself in the modern work environment, especially with the tremendous progress in communication technologies, which has brought serious problems to the operation of the network such as cyberattacks. Also, the traditional Iraqi network suffers from various problems, including the large deficit in the generated power-to-load demand ratio, which reaches about more than a third, and the great destruction that the network has been subjected to because of the wars that the country has been exposed to during the past three decades. In this study, a clear vision was presented to researchers and engineers who are interested in applying the smart grid in Iraq on this vital topic, which will greatly help in applying this essential matter to develop the work of the Iraqi power system and improve the efficiency and services it provides.

This research achieves two goals, the first is the modelling of the static synchronous compensator (STATCOM) and design of the control circuits for current, voltage and d.c capacitor voltage (Vd.c) to improve the power factor (PF) by preparing the reactive power by STATCOM so that its work is similar to the work of a synchronous condenser, and the second goal is to use smart techniques to control the Vd.c loop. For comparison, smart technical methods such as fuzzy logic type 1 (FL-T1), fuzzy logic type 2 (FL-T2), and adaptive neuro fuzzy inference system (ANFIS) were used to regulate the Vd.c on the capacitor instead of the traditional controller proportional integral (PI). Simulation was performed in MATLAB 2021 to determine the efficiency of the suggested method or approach controllers for STATCOM. The use of the proposed method improves the signal value of both the current and the voltage and the phase difference between them, which reaches almost zero. Proved that an ANFIS technique provides best Vd.c response in different values of balance and unbalance load compared with the other methods by obtaining the minimum peak overshoot (P-ov) and minimum settling time (ST).

The research strategy focuses on the effect of connecting a STATCOM to mend critical-clearing-time (CCT) for the studied system and its transient stability. This paper targets to connect STATCOM in two situations, grouped and distributed. The first situation connects STATCOM at one placement with 100 MVAR reactive power while the second situation connects two STATCOMs at two different placements with the value 50 MVAR for each one and 60 MVAR,40 MVAR in another case. It has been found through this research that when distributing the necessary compensation capacity to more than one static synchronous compensator better than from combined them in one compensator in improving the CCT. It used MATLAB / ver.2017 for simulation of our studied system (IEEE-9 nodes).

<span lang="EN-US">Studying network stability requires determining the best critical clearing time (CCT) for the network after the fault has occurred. CCT is an essential issue for transient stability assessment (TSA) in the operation, security, and maintenance of an electrical power system. This paper proposes an algorithm to obtain CCT based on fuzzy logic (FL) under fault conditions, for a multi-machine power system. CCT was estimated using a two-step fuzzy logic algorithm: the first step is to calculate Δt, which represents the output of the FL, while maximum angle deviation (δmax) represents the input. The second step is to classify the system if it is a stable or unstable system, based on two inputs for FL, the first mechanical input power (Pm), the second average accelerations (Aav). The results of the proposed method were compared with the time domain simulation (TDS) method. The results showed the accuracy and speed of the estimation using the FL method, with an error rate not exceeding 5%, and reduced the performance time by about half the time. The proposed approach is tested on both IEEE-9 bus and IEEE-39 bus systems using simulation in MATLAB.</span>