International Journal of Smart Electrical Engineering
Year:2014 | Volume:3 | Issue:4|Papers Count:7

This paper describes an advantageous method for using the capacitor banks in the distribution network, optimally. The aim is to determine the count, location and capacitor values in order to minimize the annual cost resulting from energy losses and capacitor bank’s installation cost. Besides, in the case of having nonlinear loads in the network, by installing capacitors in appropriate locations, the possibility of occurring a resonance at harmonic frequencies originating from nonlinear loads, could be reduced. Therefore, in capacitor placement, power quality constraints, including the maximum harmonic deviation value, are taken into account. The case study is a nonlinear problem that a new algorithm based on the gravitational optimal detector and fuzzy system has been used to solve it. In comparison with other intelligent search methods, the proposed algorithm has appropriate precision and convergence rate. The proposed method has been performed on a 69-buss network and a part of the distribution network of city YAZD, and the results confirmed the performance and efficiency of the proposed algorithm.

Electric arc furnace (EAF) is one of the largest loads in electric power systems. It is highly time varying and nonlinear. Its reactive power variations cause voltage fluctuations in nearby system which is known as flicker. On the other hand the nonlinear voltage-current characteristic causes strong voltage and current harmonics in EAF. To this end Flexible AC Transmission Systems (FACTS) technologies are used to mitigate the flicker and harmonics caused by EAF. The mostly used FACTS device in EAFs is Static VAr compensator (SVC) which can reduce the flicker and harmonics to some levels. Delays relevant to reactive power measurement and thyristor ignition reduce compensation capabilities of SVC. In order to prevent these delays, one can use faster compensation devices. Static Synchronous Compensator (STATCOM) may be considered as a high performance candidate for this purpose due to its fast and flexible response. In this article the performance of STATCOM is compared to SVC in EAFs plants. For this purpose the system is simulated with SVC and STATCOM in PSCAD/EMTDC using the practical EAF data records. Data records are the instantaneous EAF voltage and current recorded from EAFs in Mobarakeh steel company in Esfahan/Iran.

The Frequency Response Analysis (FRA) test has been recognized as one of the sensitive tools available for detecting electrical and mechanical faults inside power transformers. However, there is still no universally systematic interpretation technique for these tests. Many research efforts have employed different statistical criteria in order to aid the interpretative capability of the FRA, but it is showed that the methods used so far, are based on parametric statistics which need a set of assumptions about the normality, randomness and statistical independence of FRA data. Therefore, this paper aims to propose some nonparametric statistical methods which are based on explicitly weaker assumptions than such classical parametric methods. The proposed statistical methods are applied to the experimental FRA measurements obtained from two test objects: a three phase, two winding distribution transformer (35/0.4 kV, 100 kVA) to study the winding inter-turn fault as an electrical fault, and a two winding transformer (1.2 MVA, 10 kV) for the study of radial deformation as a mechanical fault. It was found through this research work that the used methods namely, Wilcoxon signed rank test and Friedman test which are proposed for the first time, can effectively reflect the differences between compared FRA data and diagnose the fault.

In this paper, a new circuit is proposed for step-up Z-source inverter based on QZSI (quasi-Z-source inverter). The proposed topology inherits all advantages of the conventional topology. The proposed topology in comparison with conventional topology reduces the ST (Shoot-through) duty cycle by over 25% at the same voltage boost factor. Theoretical analysis of the proposed qZSI in the ST and non-ST operating modes is described. Then in order to show the performance of the proposed ZSI, the simulation results on PSCAD software are used.

The paper presents a mathematical base modeling combined to Modified-Winding -Function-Approach (MWFA) for eccentricity fault detection of a round-rotor synchronous machine. For this aim, a 6-pole machine is considered, and the machine inductances are computed by MWFA in healthy and also under eccentricity fault. A numerical discrete-time method has been proposed to machine modeling in voltage-fed case, and an exact analytical method is proposed to calculate the machine's currents and torque. A method is introduced for both static and dynamic eccentricity fault diagnosis, which is proposed for first time. A mathematical base method is introduced for machine modeling, and new results are obtained to a novel method addressing for eccentricity fault diagnosis. The method is validated by Finite-Element-Method (FEM) so accuracy of the proposed method is proofed.

In this paper, a consistent pattern with the optimal coordinated design of PSS and SSSC controller to improve the damping of low frequency oscillations is shown. In this design, sensing and signal transmission time delays are considered as effectiveness parameters. The design problem has been considered an optimization problem and biogeography-based optimization (BBO) algorithm is used for searching the optimal controller parameters. The proposed controller is employed for a single machine and two-machine power systems. The results are displayed in different load conditions to present the efficiency of the proposed method. The proposed controller provides sufficient damping for power system oscillations, in different operating conditions and disturbances. Results analysis shows that the use of biogeography-based optimization algorithm has a higher efficiency in damping oscillations of the power system, compared with the PSO algorithm, and increases the dynamic stability more.

In this paper, a novel neuro-fuzzy based method combined with a feature selection technique is proposed for online dynamic voltage stability status prediction of power system. This technique uses synchronized phasors measured by phasor measurement units (PMUs) in a wide-area measurement system. In order to minimize the number of neuro-fuzzy inputs, training time and complication of neuro-fuzzy system, the Pearson feature selection technique is exploited to select set of input variables that have the strongest correlation with the output. Study on the network features such as phase angle and voltage amplitude has shown that among two interesting features, phase angle has maximum information about the performance of the network and solely can be used for training purposes. This is extra advantage of the proposed method that minimum data is needed to predict dynamic voltage stability status The efficiency of the proposed dynamic voltage stability prediction method is verified by simulation results of New England 39-bus and IEEE 68-bus test systems. Simulation results show that the proposed algorithm is accurate, computationally very fast and reliable. Moreover, it requires minimum data and so it is desirable for Wide Area Monitoring System (WAMS).