Iranian Journal of science and Technology (B: Engineering)
Volume:32 Issue: 3, june 2008

This paper presents a new structure to overcome some of the difficulties in axial-flux permanent magnet surface-mounted generators. In the new structure with a non-ferromagnetic holder، the centrifugal force acting on permanent magnets is counteracted. Hence، an increase in the rotation speed and the output power of the generator is feasible. The new design is inexpensive and easy to construct. Thus، by development of the proposed structure، it is possible to construct high-speed، low-cost axial-flux permanent magnet generators.

To design a safe substation grounding grid، it is necessary to compute the split factor for earth fault current and also current distribution in other possible paths. In this paper، a novel، simple and accurate method is developed for determination of this factor. In the proposed algorithm grounding grid impedance of adjacent substations، dissimilar tower footing resistances، different parallel circuits، more than one earth wires and different spans in transmission lines can be considered. In addition، the formulation for the earth faults through line towers is presented. Finally، the results are compared with the addressed cases that are comparable and show good agreement and accuracy.

This paper presents a valued-based approach to select system enhancement alternatives based on the proposed system well-being analysis technique. The technique is used to rank the various system enhancement alternatives for an existing HVDC system. The system health states are classified according to three operating states namely، healthy، marginal and at risk. The reliability health indices with various improvement options are calculated for the HVDC transmission. The reliability health indices are then recalculated by including the outages of the generation. The options are then ranked according to their reliability benefits and their costs.

Power system restructuring and deregulation introduces new functions، the so-called open access to transmission network، for transmission system providers. Transmission system operators are dealing with facilitating more room for electric power transfer. The transmission expansion problem (TEP) is a crucial issue، especially as it can help competition under a new scheme of power system reform. There is a very limited capability in controlling this natural tendency of power flows، while transmission expansion is a major task to meet the growth of demand. There has been some research in this field، however، in this paper a hybridization of a meta heuristic technique associated with a conventional method is employed. Real genetic algorithm and goal attainment are combined in order to develop a constrained multi-objective optimization for TEP. By considering the load shedding of demand as well as capital cost of installation (CCI) for new transmission lines، a cost function is proposed in this paper. Case studies and results analysis on “Garver System” and IEEE 24-bus test system show the effectiveness of the proposed methodology.

Although for many years scientists and engineers have been faced with the problem of optimizing discrete functions، no general analytical method has been proposed for multidimensional discrete optimization. All the methods that have already been reported in the literature are algorithmic. In one dimensional discrete optimization، no general analytical method has yet been proposed to find all the local minima and maxima of multimodal one dimensional discrete functions either. In this paper، for the first time، a general analytical method has been proposed for solving multidimensional and multimodal discrete optimization problems. Here، first we will introduce the method and present its mathematical proof، and then confirm its validity through some examples and computer simulations.

Application of the network equivalent concept for external system representation for power system transient analysis is well known. However، the challenge to utilize an equivalent network، approximated by a rational function، is to guarantee the passivity of the corresponding model. In this regard، special techniques are required to enforce the passivity of the equivalent model through a post processing approach that minimizes its impact on the original model characteristics. In this paper، the passivity is enforced by expressing the problem in terms of a convex optimization problem that guarantees the global optimal solution. The convex optimization problem is efficiently solved by recently developed numerical interior–point methods. This passivity enforcement is also global which indicates that the passivity enforcement in one region does not lead to passivity violation in other regions.

This paper presents a novel approach for human-machine interface using visual-based communication. Scene analysis، object recognition and tracking، together with gesture detection and classification، are employed to design and implement a system for real time interaction. A new paradigm is proposed for efficient selection of hand gestures that can be used in other gesture-based environments aiming at interactive multimedia. An inexpensive web camera and readily available tools (such as an ordi nary pen) have been used in this approach to render the system cost effective and suit able for general and home-based multimedia applications. Focus is placed on real time applications with a fast decision function for gesture classification، and a model-based approach for orientation detection. Experimental results demonstrate the efficacy of the proposed approach when tested using different performance criteria.

The inability of experts to articulate the knowledge required to solve a problem is، arguably، the greatest challenge to building an expert system. The problem is made worse in situations where the response of the expert must be so rapid that there is not even a chance of a plausible post hoc reconstruction of the decision processes involved. For this reason، construction of the knowledge base by example is the only approach available. Examples can be used in two ways. They may be used as input to an induction program whose task is to find an abstraction of a control strategy from the data. Examples may also be used to induce the expert to discern differences between cases، thereby allowing the knowledge acquisition system to construct rules semi-automatically. The work presented in this paper demonstrates the feasibility of both approaches. In particular، it shows that the RDR methodology can be extended to domains where the expertise involved is necessarily subcognitive. This is demonstrated by the application of a combination of ripple-down rules and machine learning to the task of acquiring piloting skills for an aircraft in a flight simulator.