COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING)
Year:2013 | Volume:4 | Issue:3|Papers Count:4

High penetration of distributed generations and the increasing demand for using electric vehicles provide a lot of issues for the utilities. If these two effective elements of the future power system are used in an unscheduled manner, it may lead to the loss increment in distribution networks, dramatically. In this paper, the simultaneous allocation of distributed generations (DGs) and electric vehicles (EVs) parking lots has been studied in a radial distribution network. A distribution network which is upgrading and equipped with DGs is considered and these resources’ optimal placement is achieved in interaction with the EV parking lots in order to minimize the power distribution network loss. The proposed method considers not only the loss minimization but also the reliability of the parking lot from the investor’s point of view. The output of this model is the daily electricity demand of parking lot. The proposed method includes two levels. At the first level of the proposed algorithm, the parking lot investor makes decision and selects three candidate buses for each parking based on three main criteria. After making decision by the parking lot investor, the candidate buses are introduced to the distribution network operator. At the second stage, the distribution network operator allocates the DGs and EV parking lots based on the candidate buses of investor in order to achieve the minimum loss of the distribution network. Finally, the effectiveness of the proposed method is evaluated by allocating of DGs and EV parking lots simultaneously on the standard distribution test system.

This paper presents an intelligent power management strategy for hybrid wind/ fuel cell/ energy storage power generation system. The dynamic models of wind turbine, fuel cell and energy storage have been used for simulation of hybrid power system. In order to design power flow control strategy, a fuzzy logic control has been implemented to manage the power between power sources. The optimal operation of the hybrid power system is a main goal of designing power management strategy. The hybrid power system is simulated in MATLAB/ SIMIULINK environment and different operating conditions have been considered to evaluate the response of power management strategy.

Content-based image retrieval, CBIR, is an interesting problem of pattern recognition. This paper is devoted to the presentation an approach to reduce the semantic gap between low level visual features and high level semantics by parameter adaptation in feature extraction sub-block. In the proposed method, GSA is used. In texture feature extraction, the parameters of a 6-tap parametrized orthogonal mother wavelet and in color feature extraction, the quantization levels are adapted to reach maximum precision of the image retrieval system. Experimental results and comparison with the conventional CBIR system are reported on a database of 1000 images. Results confirm the efficiency of the proposed adapted image retrieval system.

This paper presents the application of recently introduced water cycle algorithm (WCA) to optimize the parameters of exact and approximate induction motor from the nameplate data. Considering that induction motors are widely used in industrial applications, these parameters have a significant effect on the accuracy and efficiency of the motors and, ultimately, the overall system performance. Therefore, it is essential to develop algorithms for the parameter estimation of the induction motor. The fundamental concepts and ideas which underlie the proposed method is inspired from nature and based on the observation of water cycle process and how rivers and streams flow to the sea in the real world. The objective function is defined as the minimization of the real values of the relative error between the measured and estimated torques of the machine in different slip points. The proposed WCA approach has been applied on two different sample motors. Results of the proposed method have been compared with other previously applied Meta heuristic methods on the problem, which show the feasibility and the fast convergence of the proposed approach.