International Journal of Smart Electrical Engineering
Volume:3 Issue: 2, Spring 2014

This paper presents a comparison study between the multilayer perceptron (MLP) and radial basis function (RBF) neural networks with supervised learning and back propagation algorithm to track hand gestures. Both networks have two output classes which are hand and face. Skin is detected by a regional based algorithm in the image, and then networks are applied on video sequences frame by frame in different background (simple and complex) with different illumination of environment to detect face, hand and its gesture. The number of training and testing samples in networks are equal and the set of binary images obtained from skin detection method is used to train the networks. Hand gestures are 6 cases which are tracked and they were not recognized. Both left and right hands has been trained to the network. Network features are based on the image transforms and they should not relate to deformation, size and rotation of hand. Since some of the features are in common with each other so a new method is applied to reduced calculation of input vector. Result shows that MLP has high accuracy and higher speed in tracking hand gesture in different background with minimum average error but it has a lower speed in training and convergence compare to the RBF in its final average error.

The interline power flow controller (IPFC) is a concept of the FACTS controller for series compensation which can inject a voltage with controllable magnitude and phase angle among multi lines. This paper proposes a novel IPFC-Based Damping Neuro-control scheme using PSO for damping oscillations in a power system to improve power system stability. The addition of a supplementary controller to the IPFC main control can provide effective damping to the low frequency oscillation on the heavily loaded tie lines of interconnected power systems. However, the conventional controller designed based on a linearized model cannot provide satisfactory performance over a wide range of operation point and under large disturbances.

This study based on investigation for integration wind power into conventional power system with its impact on fossil fuel generators and their generation management. Wind power as environmental friendly energy source can reduce the operational cost of the system due to considering no cost for energizing the generator in comparing with fossil fuel generators. However due to unpredictable nature of the wind power, it is quite difficult to determine how much wind power should be integrated to ensure both power system security and operational cost reduction. In this study by compering both economic and security requirements using GA and PSO for smart calculation in wind power generation into the conventional system, a proper economic load dispatch program has been applied. Three different approaches (pessimistic, Optimistic and Linear) has been studied and compered to evaluate the system security and reliability with economic benefits. Due to considering no fuel cost for wind power generators, it is more beneficial to produce electrical power by this type of power resource but with more reliability for the system. At the end by compering PSO and GA results and numerical analysis on IEEE-30 bus test system with six generator, exactitude and accuracy of the proposed approaches presented.

One of the big concerns of big cities is facing with the increase of fossil fuel vehicles in the roads. The cars intensify greenhouse gas emission in civic centers. One approach to reduce the emission is replacing the cars by Plug-In Electric Vehicles (PEVs). In spite of reducing the emission, PEVs have some adverse effect on electric distribution networks. Technical challenges such as load and loss factors are some of the considerable problems. In this paper, in order to overcome the problems, the effect of integration of different energy networks is introduced. Two scenarios are proposed. In first scenario, a parking lot is just supplied by just electric distribution network. In second scenario, the parking lot is supplied by electricity and gas networks. Finally, the significant effect of multi carrier energy networks to supply the vehicles is confirmed.

In this paper, the electrical consumption of Hamedan University is derived of the bills, Then with defining of fuzzy Bus Thermal Coefficient objective function for heating, the amount of available heat selling to university consumer that is produced by Biomass CHP plant is calculated. With the capacity determination of Biomass CHP plant to provide Thermal and electrical energy of university and calculation of photovoltaic systems to supplling electrical energy, each technical calculation is presented . Then, Economic Calculation of each projects will be addressed separately. The Economic optimization in designing and operation of electrical systems is usually done through a review of investment criteria, that in this study, are include: Net present value (NPV), Internal Rate of Return (IRR) and Return period (PP) that with regard to the economic evaluation methods, the economic evaluation of project is doing. The economic calculations shows that the use of biomass CHP plant is adequate but using of photovoltaic system is not adequate.

Leakage of oil from pipelines and oil tankers into seas and oceans is ecologically important and can have significant social and economic impacts on the environment. An early detection of deliberate or accidental oil spills can reduce serious hazards that may threaten coastal residents and help identify pollutants. Iran has been surrounded by seas from the north and the south and they provide us with valuable natural resources, in general, and oil reserves in particular. Besides, the seas are where oil is mined and oil tankers pass. Therefore, protecting the seas against oil contamination is essential. Due to the vastness of seas and the need for early detection of contamination source, modern methods must be employed to prevent excessive environmental damage. Unfortunately, a few studies have been conducted on it to date. In the present study, a number of robots controlled by the Fuzzy Particle Swarm Optimization (FPSO) algorithm were used to discover the source of contamination. In this paper a z coefficient was added to FPSO algorithm derived from fuzzy logic and contamination condition. This z coefficient informed the velocity of particles in a PSO model. We showed that using a fuzzy logic can improve the treatment of standard PSO algorithm in detecting oil contamination.

In recent years, there has been a fast growth in wind energy conversion system (WECS). There are two general types of wind turbines in WECS: fixed speed wind turbines and varying speed wind turbines.Permanent magnet synchronous generator (PMSG) is one of the most attractive generators for the varying speed turbine WECS.In this paper, a fuzzy controller is proposed to control the current source inverter (CSI) in a wind energy conversion system (WECS) based on permanent magnet synchronous generator (PMSG). The fuzzy controller guarantees the unity power factor operation of CSI. In order to drive CSI the space vector switching (SVM) is utilized. In addition, the WECS has a buck converter which regulates the DC current so that the maximum power point tracking is achieved. The proposed system is implemented in MATLAB/SIMULINK, and the results are provided and compered with the traditional PI controller based systems. The results show that the proposed system is faster than traditional PI controller based systems.

Simultaneous routing and resource allocation has been considered in wireless networks for its performance improvement. In this paper we propose a cross-layer optimization framework for worst-case queue length minimization in some type of FDMA based wireless networks, in which the the data routing and the power allocation problem are jointly optimized with Fuzzy distributed H∞ control strategy . with the presented formulation based on the minimization of the queuing length in each node, the routing and resource allocation problem is formulated as a decentralized fuzzy H∞optimal control problem for a wireless mesh network. the presented control strategy determines the transmit power in FDMA systems in which each node has fixed set of powers to be allocated to its outgoing links. Using the proposed control strategy a robust routing performance will be achieved in the presence of unknown network delays in network modeling. also with using fuzzy decision rules in the proposed H∞ controller strategy, we try to improve the network performance criteria and avoid packet loss in the network.