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UPFC device is discussed in this paper along with their models and functions. Moreover, the suggested and the complementally approaches in the current research study. As a result, the methods are divided into three divisions, which are sensitivity analysis based methods, conventional optimization based methods and artificial intelligence (AI) based methods. In addition, artificial intelligence based methods plays a major role in reducing the search space region. However, to optimize the resulting benefits, the placement, sizing and parameter of UPFC device should be determined. This paper presents and discusses in depth an overall review of the last two decades’ studies, including proposed and comparative methods and strategies, approaches, objective functions, UPFC device tools utilized, limitations, contingency situations and all parameters evaluated and simulated. This paper also provides an analysis of UPFC’s various benefits and uses of power flow studies, such as, power loss mitigation, system load ability improvement, power system security, enhancement of voltage stability, cost of generation and UPFC installation and utilizing specific optimization techniques. Therefore, a more weighted overview of the proposed method is presented focused on artificial intelligence optimization methods.

The dependently of the electrical grid is critical key point to safety of the nuclear research reactor (NRR) operation. This paper provides an optimization approach relying on optimal allocation of UPFC device to obtain higher electrical power quality of such nuclear facilities. The particle swarm optimization (PSO) technique was used to address the optimal UPFC allocation problem. The suggested approach is applied to the IEEE 33-bus test system, and results reveal that the suggested PSO is more efficient in minimizing total power losses and enhancing voltage profile using only one of UPFC device. The results show the technique is good method in this case.

With rapidly growing of Renewable Energy Sources (RESs) in renewable power systems, several disturbances influence on the power systems such as; lack of system inertia that results from replacing the synchronous generators with RESs and frequency/voltage fluctuations that resulting from the intermittent nature of the RESs. Hence, the modern power systems become more susceptible to the system instability than conventional power systems. Therefore, in this study, a new application of Superconducting Magnetic Energy Storage (SMES) (i.e., auxiliary Load Frequency Control (LFC)) has been integrated with the secondary frequency control (i.e., LFC) for frequency stability enhancement of the Egyptian Power System (EPS) due to high RESs penetration. Where, the coordinated control strategy is based on the PI controller that is optimally designed by the Particle Swarm Optimization (PSO) algorithm to minimize the frequency deviations of the EPS. The EPS includes both conventional generation units (i.e., non-reheat, reheat and hydraulic power plants) with inherent nonlinearities, and RESs (i.e., wind and solar energy). System modelling and simulation results are carried out using Matlab/Simulink® software. The simulation results reveal the robustness of the proposed coordinated control strategy to preserve the system stability of the EPS with high penetration of RESs for different contingencies.

This paper presents a coordination strategy of Load Frequency Control (LFC) and digital frequency protection for an islanded microgrid (MG) considering high penetration of Renewable Energy Sources (RESs). In such MGs, the reduction in system inertia due to integration of large amount of RESs causes undesirable influence on MG frequency stability, leading to weakening of the MG. Furthermore, sudden load events, and short circuits caused large frequency fluctuations, which threaten the system security and could lead to complete blackouts as well as damages to the system equipment. Therefore, maintaining the dynamic security in MGs is one of the important challenges, which considered in this paper using a specific design and various data conversion stages of a digital over/under frequency relay (OUFR). The proposed relay will cover both under and over frequency conditions in coordination with LFC operation to protect the MG against high frequency variations. To prove the response of the proposed coordination strategy, a small MG was investigated for the simulation. The proposed coordination method has been tested considering load change, high integration of RESs. Moreover, the sensitivity analysis of the presented technique was examined by varying the penetration level of RESs and reducing the system inertia. The results reveal the effectiveness of the proposed coordination to maintain the power system frequency stability and security. In addition, the superiority of the OUFR has been approved in terms of accuracy and speed response during high disturbances.

This paper presents a Model Predictive Control (MPC) technique for frequency stabilization of renewable power systems with inherent nonlinearities. To prove the effectiveness of the proposed technique, the Egyptian Power System (EPS), which includes both conventional generation units (i.e., non-reheat, reheat and hydraulic power plants) and wind turbines is tested using Matlab/SIMULINK® software. Furthermore, the performance of the proposed MPC technique is compared with an optimal Proportional-Integral (PI) controller-based Particle Swarm Optimization (PSO) algorithm under different load profiles and system uncertainties. The simulation results emphasize the superior robustness of the proposed MPC-based LFC in comparison to the optimal PI controller.