JOURNAL OF ELECTRICAL ENGINEERING DEPARTMENT, TRANSACTION ON ELECTRICAL TECHNOLOGY (ELECTRONICS AND POWER)
Year:2009 | Volume:1 | Issue:1|Papers Count:8

Torsional torques on turbine-generator shaft which are yields of disturbances in power systems, can reduce the useful lifetime of shaft. In this paper, these oscillations will be damped and controlled by novel Power System Stabilizers (PSSs). Complex PSS which is used in this paper will act on the excitation system in generator set and also on the controller of in High Voltage Direct Current (HVDC) system. This PSS uses three terms (generator angle deviation, frequency oscillation and capacitor voltage deviation in HVDC system) of the study system which includes two ties AC and DC. This is the reason that this PSS is named novel one against the conventional PSSs. In order to adjust the PSS parameters to damp the oscillations, genetic algorithm is used. To improve the application of this PSS, fuzzy logic control methods are also used which has notable effect on controlling the oscillations in study system. The simulation results show the effectiveness of designed PSS in controlling the torsional torques in turbine-generator shaft.

One method for on-line fault detection in synchronous generator is stator current harmonics analysis. In this paper, the flexible neural network with reconstruction structure during learning has been used to evaluate the stator current harmonics in different loads.Generator modeling, finite element method and state space model make training set of flexible neural network. Many points from generator capability curve are used to complete this set. Flexible neural network that is used in this paper is a perception network with single hidden layer, flexible hidden layer neuron and back propagation algorithms. Results are show that the trained flexible neural network can identify stator current harmonics for desired load from the capability curve. The error is less than 10% in compared to the values obtained directly from the CFE-SS algorithms. The parameters of modeled generator are 43950 (KVA), 11 (kV), 3000 (rpm), 50 (HZ), (PF=0.5).

The stability of frequency and voltage is one of the basic principles in the power systems. One of the latest control measures for power system frequency control and stability is load shedding. A fast and optimal adaptive load shedding method using Artificial Neural Networks (ANN) is presented in this paper. In this paper, the total power generation and the total existing load in power system were selected as the ANN inputs. This method has been tested on the New England test system. The simulation results show the ability of this frequency control algorithm for optimal solving problem related to conventional method.

Permanent Magnet Synchronous Machines (PMSM) are increasingly used because of their advantages over other machines, which include compactness, high efficiency, and well developed drives.. The substitution of the position sensors by advanced algorithms embedded in the controls hardware and software has been investigated for the last couple of decades. This Paper presents the modeling, analysis, design and experimental validation of a robust sensor less control method for PMSM based on Extended Kalman Filter. The position/speed sensor less control scheme along with the power electronic circuitry is modeled. The performance of the proposed control is assessed and verified for different types of dynamic and static torque loads.

In this paper, intifially an introduction is presented about Electric Power market in deregulated system and load shedding by interior-point method in these systems. Then, predictor-corrector of IPM is considered and by consideration of the IEEE 6 busbar network, distribution of load by using software (PSAT) will be considered. Then, with introduction of bilateral contracts in organized renewal system, the proposed method is applied to make optimal load shedding in the IEEE 30 busbar network. In this direction, the effective factors on changes of load- shedding model are analyzed completely. Some of factors are price changes, congestion lines (result from emitting of one or more lines) and maximum load-shedding limit in each bus bar.

Motion estimation and compensation are main stages in hybrid video coding standards. Due to structural simplicity the block-matching motion estimation is the most used method in digital video technology. In recent years the mesh-based motion estimation is considered by the researchers because of its more complex motion models and lack of blocking artifacts. However, mesh-based motion estimation suffers from error propagation and weak performance in noisy and brightness varying conditions. In this paper motion adaptive interpolation functions are proposed for the mesh-based motion estimation to overcome these problems. The simulation results show the better robustness of the proposed scheme against noise and brightness variations, not only regarding to mesh-based but also block-matching motion estimation techniques.

Motion estimation and compensation are main stages in hybrid video coding standards. Due to structural simplicity the block-matching motion estimation is the most used method in digital video technology. In recent years the mesh-based motion estimation is considered by the researchers because of its more complex motion models and lack of blocking artifacts. However, mesh-based motion estimation suffers from error propagation and weak performance in noisy and brightness varying conditions. In this paper motion adaptive interpolation functions are proposed for the mesh-based motion estimation to overcome these problems. The simulation results show the better robustness of the proposed scheme against noise and brightness variations, not only regarding to mesh-based but also block-matching motion estimation techniques.