JOURNAL OF IRANIAN ASSOCIATION OF ELECTRICAL AND ELECTRONICS ENGINEERS
Year:2007 | Volume:4 | Issue:1|Papers Count:7

This paper investigates the Multi-band OFDM (MBOFDM) based physical (PHY) layer proposal for IEEE 802.15.3a working group on short-range high data-rate Ultra-wide-Band (UWB) communications. An overview of the MB-OFDM PHY layer architecture with its various parameters is presented and the optimal choice of critical parameters is discussed. Next, we derive the theoretical un-coded Bit Error Rate (BER) of MB-OFDM over the Rayleigh fading channel. Performance results over realistic IEEE UWB channel models are analyzed and compared to a pulsed-OFDM based approach. Although pulsed-OFDM was presented in the literature as an enhancement to the MB-OFDM approach, simulation results showed that with same redundancy-factor, both systems give almost similar BER performance.

Restructuring of electric industry has seriously affected the operation and planning process of electric power systems, Due to the unbundling process and new market requirements, a set of new challenges and goals have been introduced in the field of transmission planning. Moreover, the uncertainty level of input data to planning process has been increased significantly. In this paper first, the transmission expansion planning problem in the new environment is defined. Next, a new algorithm for transmission expansion planning in the restructured electric power system with market efficiency and probabilistic reliability criteria is proposed which is capable of handling uncertainties in input data using scenario , planning technique. The proposed algorithm has been implemented on IEEE 14-bus test system and the results have been discussed.

Face expression recognition is useful for designing new interactive devices offering the possibility of new ways for human to interact with computer systems. In this paper we develop a facial expressions analysis and synthesis system. The analysis part of the system is based on the facial features extracted from facial feature points (FFP) in frontal image sequences. Selected facial feature points were automatically tracked using an improved cross-correlation based motion tracking algorithm, and extracted feature vectors from the position of FFPs in the first and the last frames, were used to classify expressions and Action Units (AU), using Probabilistic Neural Networks (PNN).Comparing with similar analysis works, we improved analysis system recognition rate by using improved motion tracking system and some new facial features. The synthesis part of the system uses a deformable patch object model that models facial features (eyes, eyebrows and mouth) by small polygons. The coordinates of the vertices of these polygons can be changed based on the FFP positions in the original image. The synthesis part of the system can be used as an on-line personalized facial animator by tracking some FFPs in the original image, or as a generic facial expressions animator by applying some parameters for each AU code (off-line animation). The proposed deformable model has a simple structure and uses a few set of control points comparing to the similar face models.

This paper presents a framework for long term transmission expansion planning in power pool competitive electricity markets. In the proposed approach, maximization of network users' benefits with satisfying of security constraints is considered for determination of transmission expansion strategy. The proposed model is a complicated non-linear mixed-integer optimization problem. A hybrid genetic-based algorithm and Quadratic Programming (QP) is used for optimization procedure. The discrete decision-making variables of the expansion plan are optimized by genetic algorithm, while QP optimizes the continuous ones. For illustration of the approach capabilities, many test results on IEEE-RTS is presented.

Context-dependent modeling is a widely used technique for better phone modeling in continuous speech recognition. While different types of context dependent models have been used, triphones have been known as the most effective ones. In this paper, a Maximum a Posteriori (MAP) estimation approach has been used to estimate the parameters of the untied triphone model set used in data-driven clustering. The use of better prior parameters derived from two sets of more reliably trained biphone models has helped in this process. The result is better parameter tying where the tied-state triphone system built in this manner outperforms a similar system in which ordinary Maximum Likelihood (ML) approach was used to estimate the untied triphone system parameters. The technique may also be useful in other tying schemes used in context-dependent modeling.

This paper presents actual cases of steady reactive power oscillation of Distributed Generations (DGs) during parallel operation with the main grid. The cause of the problem was found to be the adverse effects of excitation system voltage regulation. It is shown, through preliminary investigation and detailed simulation studies, that how the excitation control system can be modified to overcome this problem. Onsite test results verify the analysis results and effectiveness of the remedial actions. Finally, general practical recommendations are offered for excitation control of synchronous generator-based DG, such that it performs properly, both in grid connected and islanding conditions.

This paper suggests a method for designing PSS to damp multi-machine power system oscillations. The method is based on robust control theory. First, the conventional method for designing robust controller in LMI framework is illustrated. Then, the suggested method is given, in which, a PID output feedback controller is tuned using the LMI approach. Mostly, the classical methods are used to tune a PSS, but in this paper a robust approach is investigated to guarantee the robustness of the given PSS. The performance of the controller is tested on a sample power system. Simulation results show the effectiveness, robustness, and good performance of the suggested controller.