The Electrical power system has become vast and more complex, so it is subjected to sudden changes in load levels. Stability is an important concept which determines the stable operation of the power system. Transient stability analysis has become one of the significant studies in the power system to ensure the system stability to withstand a considerable disturbance. The effect of temporary occurrence can lead to malfunction of electronic control equipment. The application of flexible AC transmission systems (FACTS) devices in the transmission system have introduced several changes in the power system. These changes have a significant impact on the power system protection, due to differences inline impedance, line current and voltage. On the distance relaying protection system to identify essential issues that protection engineers need to consider during the stages of design and operation of the protection system. Transient analysis can be conducted using a simulation software package. One of the commercial simulation software package used by industry worldwide is Siemens Power System Simulation for Engineering (PSS/E). The object of this work is to improve the Transient stability and to clear critical fault times of the Kurdistan Region Government (KRG) network by using optimal FACTS devices in different optimal locations under fault conditions.
In this work, copper substituted cobalt ferrite nanoparticles with
chemical formula Co1-xCuxFe2O4 (x=0, 0.3, and 0.7), has been
synthesized via hydrothermal preparation method. The structure of
the prepared materials was characterized by X-ray diffraction (XRD).
The (XRD) patterns showed single phase spinel ferrite structure.
Average crystallite size (D), lattice constant (a), and crystal density
(dx) have been calculated from the most intense peak (311).
Comparative standardization also performed using smaller average
particle size (D) on the XRD patterns of as-prepared ferrite samples
in order to select most convenient hydrothermal synthesis conditions
to get ferrite materials with smallest average particl
إن المقصود باختبارات حسن المطابقة هو التحقق من فرضية العدم القائمة على تطابق مشاهدات أية عينة تحت الدراسة لتوزيع احتمالي معين وترد مثل هكذا حالات في التطبيق العملي بكثرة وفي كافة المجالات وعلى الأخص بحوث علم الوراثة والبحوث الطبية والبحوث الحياتية ,عندما اقترح كلا من Shapiro والعالم Wilk عام 1965 اختبار حسن المطابقة الحدسي مع معالم القياس
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In this work, analytical study for simulating a Fabry-Perot bistable etalon (F-P cavity) filled with a dispersive optimized nonlinear optical material (Kerr type) such as semiconductors Indium Antimonide (InSb). Because of a trade off between the etalon finesse values and driving terms, an optimization procedures have been done on the InSb etalon/CO laser parameters, using critical switching irradiance (Ic) via simulation systems of optimization procedures of optical cavity. in order to achieve the minimum switching power and faster switching time, the optimization parameters of the finesse values and driving terms on optical bistability and switching dynamics must be studied.
... Show MoreThis approach was developed to achieve an accurate, fast, economic and sensitivity to estimation of diphenhydramine Hydrochloride. The dye that produced via reaction between diphenhydramine HCl with thymol blue in acidic medium pH ≈ 4.0. The ion pair method include an optimization study to formed yellowcolored that extraction by liquid – liquid method. The product separated of complexes by using by chloroform solution measured spectrophotometry at 400 nm. The analysis data at optimum conditions showed that linearity concentration in a range of calibration curve 1.0 – 50 μg /mL, limit of detectionand limit of quantification 0.0786 and 0.2358 μg/mL respectively. The molar absorptivity and Sandell’s sensitivity were 1.8 × 10 -4 L/mo
... Show MoreThe need for quick airborne transportation is critical, especially in emergencies. Drones with suspended payloads might be used to accomplish quick airborne transportation. Due to the environment or the drone's motion, the slung load may oscillate and lead the drone to fall. The altitude and attitude controls are the backbones of the drone's stability, and they must be adequately designed. Because of their symmetrical and simple structure, quadrotor helicopters are one of the most popular drone classes. In this work, a genetic algorithm with two weighted terms fitness function is used to adjust a Proportional-Integral-Derivative (PID) controller to compensate for the altitude and attitude controllers in a quadrotor drone
... Show MorePotential data interpretation is significant for subsurface structure characterization. The current study is an attempt to explore the magnetic low lying between Najaf and Diwaniyah Cities, In central Iraq. It aims to understand the subsurface structures that may result from this anomaly and submit a better subsurface structural image of the region. The study area is situated in the transition zone, known as the Abu Jir Fault Zone. This tectonic boundary is an inherited basement weak zone extending towards the NW-SE direction. Gravity and magnetic data processing and enhancement techniques; Total Horizontal Gradient, Tilt Angle, Fast Sigmoid Edge Detection, Improved Logistic, and Theta Map filters highlight source boundaries and the
... Show MoreThis paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett
... Show MoreSome of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems. Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic. Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance. In this study, two different sets of select
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