The Modares Journal of Electrical Engineering
Volume:12 Issue: 4, 2013

Due to the high penetration of wind farms in the networks, they can have a significant role in the control of power systems. In this paper, wind farms (WFs) are used to improve the static security margins of the power system. Generation rescheduling is one of the remedies to improve the static security margins of the power system. In this paper, the generation rescheduling is presented based on wind farms. To assess the security of the power system, the net active and reactive (generation minus demand) powers of all buses are selected as features. The numbers of the features are reduced based on one of the famous methods of the feature extraction methods named Principle Component Analysis (PCA). The feature extraction method is used to save all features effects on the security of the power system. In this paper, to find the most optimum way to improve the static security margins, two optimization problems are introduced for the two strategies presented. The proposed method is implemented on the IEEE 39-bus network and the results show its effectiveness on the static security margin. It should be mentioned that the proposed method can deal with correlated random variables. Nataf transformation is used to build more accurate and more realistic database to train the classifier to assess the static security margins of the power system. The real data of Iran's grid are used to validate the Nataf transformation

The Direct Torque Control (DTC) of Interior Permanent Magnet Synchronous Motor (IPMSM) offers simple structure and fast torque response. The conventional Switching Table-based DTC (ST-DTC) presents some disadvantages like high torque and flux ripple and also variable switching frequency. This paper investigates the improved ST-DTC strategies to reduce both torque and flux ripple in DTC of IPMSM with emphasis on structure simplicity and fast dynamics. New switching table with only two active vectors for each sector is introduced and the torque control hysteresis band is replaced by duty cycle calculation unit. For flux ripple reduction, conventional hysteresis-based controller is replaced by simple dithering technique. The duty cycle calculation unit is implemented to operate on each selected vector with the aim of torque ripple RMS minimization. The increase of switching frequency in ST-DTC because of delay in torque and flux estimation process, actually, is not possible; even when hysteresis bands are sufficiently diminished. This paper incorporates the combination of duty cycle modulated DTC and dithering technique to enlarge switching frequency. It therefore provides smoother waveform concurrently for the motor torque and the flux. In the proposed method waveform comparison structure for duty cycle calculation is used; hence, the merits of classical ST-DTC, such as fast dynamic and simple structure, are mostly preserved

This paper develops new results on the use of model predictive control to regulate the attitude of a ground station antenna. Two degree of freedom AZ-EL pedestal is considered as ground station antenna. Permanent Magnet Synchronous Motors are taken into consideration as the best choice for satisfaction of control objectives as actuators. The design is based on a two cascade controller consist of MPC and a simple feedback linearization, respectively. The proposed approach provides more smooth tracking and lower energy consumption with respect to analogous works. The model predictive controller employs integral action, resulting in zero steady-state error and load torque disturbance rejection. Realistic disturbances caused by wind and load is considered and applied to an industry-sized pedestal. The reference data of azimuth and elevation angles are chosen from a real tracking mission. The comparison of simulation results by typical PI controller, verify the effectiveness of the proposed method.

This paper presents a probabilistic confidence-interval based method for optimal placement of shunt capacitors in distribution networks by considering probabilistic characteristics of loads. The main objective function are reducing loss and improving the voltage profile. Backward forward sweep method has been employed to obtain the power flow results in distribution system. In addition, Integer Harmony Search Algorithm has been used to solve the optimization problem. The probabilistic aspects of problem have been solved using point estimation (PE) method. The novelty of this paper is introducing a confidence interval index using Gram-Charlier expansion. This index shows the risk of system to violate its security constraints when loads are considered as stochastic random variables. Using this index, planners can find the optimal sitting and sizing of capacitors in distribution systems based on their desired level of risk. Verification of the proposed method has been tested on 33-bus radial distribution system. Results demonstrate the effectiveness and merits of the proposed method.

Microgrids are small-scale, low voltage (LV) power networks which employ renewable distribution energy resources (DERs) with power electronic interfaces (PEIs). Microgrids as single controlled units and active distribution networks require flexible control systems to ensure reliable and secure operation in different modes. These various operations of microgrid cause variations in voltage and frequency especially in island mode. In this paper, a new control method with two optimization algorithms (genetic algorithm (GA) & imperialist competitive algorithm (ICA)) are proposed to eliminate both voltage and frequency disturbances. Also, a new concept of conventional droop control in format of fast droop controller (FDC) is designed to guaranty the microgrid system reliability with cooperation of a modern frequency controller. Simulation results show the truth behavior of proposed approach in comparison with previous methods

Since it is essential to deliver smoothed sinusoidal voltage to the customers, diagnosing power quality (PQ) events has played important role in power delivery and conversion. This diagnostic scheme should be accurate to classify PQ events from other events in power system. Also it should be fast enough to rapidly mitigate PQ events. In this paper, an algorithm based on Core Vector Machine (CVM) has been introduced to classify power quality events. Feature selection method has also been applied to increase the accuracy of the classifier’s algorithm. Some features have been selected among several others extracted by wavelet transform. In addition, eight different classes are simulated due to the corresponding equations used in previous studies. Evaluating the performance of the algorithm, different indices have been used to assess the operation of the classifier’s algorithm. Simulations results show the robust capability of the proposed algorithm to classify the PQ events