Recently, global power demand has significantly increased. As this demand does not have a proportional impact on transmission capacity and power generation. The latest methods are used to improve power system performance. The Flexible Alternating Current Transmission System (FACTS) devices are applied to improve the existing transmission network capacity. The Unified Power Flow Controller (UPFC) has been selected in this study to control power flow in transmission networks and improve the power system operation. In this paper, the Artificial Neural Network Controller (ANN) proposed to overcome the problems of the existing UPFC controller and tested using the IEEE-14 bus system with various test cases. The results showed that the proposed ANN has improved the efficiency of UPFC successfully by increasing the active power flow, reducing reactive power, and improving the voltage profile. The performance of proposed ANN-based UPFC has also been compared with Proportional Integral (PI) based UPFC and with Fuzzy Logic Controller (FLC) based UPFC shows its effectiveness. The simulation results have shown that the proposed ANNbased UPFC proved its robustness in improving all power system parameters compared to PI-based UPFC.
The solar irradiation falling on PV-module that converted into heat hence the reducing efficiency. The dust deposition decreases efficiency and resist the amount of solar radiation interacting on surface of PV-panel. The mismatch position placed of PV string can make the mutual shading between the PV-Module, Due to this reason of shading the totally efficiency of PV system falls. To overcome all mentioned problem, in this paper the review of environmental factor and their latest minimizing techniques for optimizing performance of PV-Module is discussed. This paper merely focused on the review of cooling, Cleaning and shading effect techniques.
Recently, global power demand has significantly increased. As this demand does not have a proportional impact on transmission capacity and power generation. The latest methods are used to improve power system performance. The Flexible Alternating Current Transmission System (FACTS) devices are applied to improve the existing transmission network capacity. The Unified Power Flow Controller (UPFC) has been selected in this study to control power flow in transmission networks and improve the power system operation. In this paper, the Artificial Neural Network Controller (ANN) proposed to overcome the problems of the existing UPFC controller and tested using the IEEE-14 bus system with various test cases. The results showed that the proposed ANN has improved the efficiency of UPFC successfully by increasing the active power flow, reducing reactive power, and improving the voltage profile. The performance of proposed ANN-based UPFC has also been compared with Proportional Integral (PI) based UPFC and with Fuzzy Logic Controller (FLC) based UPFC shows its effectiveness. The simulation results have shown that the proposed ANNbased UPFC proved its robustness in improving all power system parameters compared to PI-based UPFC.
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