COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING)
Year:2012 | Volume:3 | Issue:2|Papers Count:7

The paper aims to investigate the advantages of using adaptive bit rate in the communication link of a LEO satellite. While doing the study, it is assumed that there is a communication subsystem on-board responsible for gathering the information sent by a number of ground user terminals. The subsystem which operates based on Store-and-Forward (SAF) Scenario, contains two communication links, one for receiving data from user terminals (store case), and the other for forwarding the stored data to an Earth station (forward case). In fact, the current work aims to improve the volume of the data forwarded to Earth station. To this end, the Forward case bit rate is varied adaptively, and then by analyzing the power budget in a practical condition, the improvement achieved is evaluated. The results specifically obtained for a sample LEO satellite shows that utilizing adaptive bit rate instead of fixed bit rate can increase the daily data exchange up to about 100%.

Carpet patterns are in two categories: machine-printed and hand-painted. There are a few articles on automatic reading of machine-printed patterns, but due to the difficulties in reading of machine-printed patterns, there is not any published work yet. This article provides a new method for automatic reading of hand-painted carpet patterns which consists of the following steps: initial pixel-based color reduction, knot-based color reduction, segmentation by region growing and final color reduction. The proposed method is tailored for the application in hand and, therefore yields a good result. For 80 segments of different patterns, the algorithm has an approximate of 95% accuracy. In other words, the color of 95% of pattern knots are found accurately. It is tried to develop a method with proper accuracy and speed. Therefore, the proposed method is not completely automatic and the number of colors is required to be given by the user.

In this paper, a stator-flux-reference frame control method is proposed in order to control the speed and torque of an Interior Permanent Magnet Synchronous Machine (IPMSM) in different loads condition. Direct Torque Control method (DTC) based on Space Vector Modulation (SVM) is used for control of IPMSM. In the proposed control method, conventional PI controller is used for controlling the stator flux, and torque of the motor. Also, a fuzzy controller is considered to improve the dynamic performance of DTC technique for speed control. In comparison to the conventional reference flux controller methods, this method, in addition, improves the torque profile of the motor drive. Moreover, it reduces copper losses. Simulation results for a 240V, 120A, 2500rpm, IPMSM confirm the appropriate performances of the method.

Power quality monitoring is the first step in the identification of power quality disturbances and reducing them in order to improve the performance of the power system. The aim of this paper is to propose the architecture of a new intelligent strategy for online and offline power quality monitoring system based on multi-agent systems. In this study, a multi-agent system for solving some problems in power quality monitoring, including computational complexity, low accuracy, change in the data pattern, non-adaptive structure of detection system to changing conditions is proposed. In the proposed strategy, the agent characteristics, such as automatic and dynamic performance, intelligent, learning, reasoning ability, objectively and interoperability of agents are used. This paper is presented in two stages. In the one stage, to indicate problems in power quality monitoring, different methods of feature extraction, feature selection and classification for automatic recognition of power quality disturbances have been analyzed. Optimal selection of input feature vector of distinguish system is applied using different methods of data mining. Also, three well-known classifiers are considered. In another stage of the paper, to solve some challenges, the design of investigated structures in the form of a multi-agent system is expressed. The results of the experiments in this paper demonstrate the superiority of agents and multi-agent systems for online and offline power quality monitoring.

Today power system works with a lower stability boundary due to increasing energy consumption. Increase of extensive blackouts in different points of the world in recent years clarifies that the power system stability should be improved. Using FACTS devices has a great role for improving power system stability. In this regard, locating UPFC in order to boost stability is getting important in power system studies. This paper develops a new optimal UPFC placement method by using adaptive PSO (APSO) algorithm in Isfahan-Khozestan transmission network for improving static and transient stability. For UPFC placement, system voltage, loading and transmission line congestion, total power system losses, installation and operation cost constraints are considered. UPFC control system with supplementary control signal is modeled in details. All power system components, excitation system and load frequency control loops for all generators of Isfahan-Khozestan network in DIgSILENT software have been simulated. Simulation results show the remarkable effect of the proposed method for improving static and transient stability in under study system.

In this paper, a method to track the maximum power of solar panels based on fuzzy logic is presented. The proposed method is based on the relationship between radiation intensity and the voltage of maximum power operating point. With this relationship, at any time by measuring the light intensity, voltage can be calculated at the maximum power point by using fuzzy approximation function. In order to verify the proposed method, simulation results are presented.