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Analysis on the Basis of Volterra Series Signal–To–Noise Ratio of Nonlinear Device in the Conditions of the Stochastic Resonance Effect
Okcana Kharchenko,
Vladislav Tyutyunnik
Issue:
Volume 3, Issue 3, June 2015
Pages:
25-29
Received:
29 March 2015
Accepted:
11 April 2015
Published:
27 April 2015
Abstract: In this paper, the stochastic resonance effect is considered. It is shown that the stochastic resonance effect appears in the conditions of operating on the nonlinear system of additive mixture of desired signal and noise. The numerical simulation of the output signal when exposed to the input of the system of additive mixture harmonic signal and noise with a uniform distribution is given. Analytical relational expressions for signal-to-noise ratio on the output of the nonlinear system are got. The analysis of signal-to-noise ratio is conducted on the output of the nonlinear system depending on the parameters of the input signal and noise. In this paper we have shown the stochastic resonance effect occurs mainly at low frequencies.
Abstract: In this paper, the stochastic resonance effect is considered. It is shown that the stochastic resonance effect appears in the conditions of operating on the nonlinear system of additive mixture of desired signal and noise. The numerical simulation of the output signal when exposed to the input of the system of additive mixture harmonic signal and n...
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Design and Simulation of TCR-TSC in Electric Arc Furnace for Power Quality Improvement at Steel Making Plant (No-1 Iron and Steel Mill, Pyin Oo Lwin, Myanmar)
Thet Mon Aye,
Soe Win Naing
Issue:
Volume 3, Issue 3, June 2015
Pages:
30-35
Received:
3 April 2015
Accepted:
11 April 2015
Published:
13 May 2015
Abstract: Electric Arc Furnaces (EAFs) are unbalanced nonlinear and time varying loads, which can cause many problems in the power system quality. As the use of arc furnace loads increases in industry, the important of the power quality problems also increase. So, in order to optimize the usage of electric power in EAFs, it is necessary to minimize the effect of arc furnace loads on power quality in power systems as much as possible. Therefore, in this paper, design and simulation of an electric plant supplying an arc furnace is considered. Then by considering the high changes of reactive power and voltage flicker of nonlinear furnace load, a thyristor controlled reactor compensation with thyristor switched capacitor (TCR-TSC) are designed and simulated. Finally, simulation results verify the accuracy of the load modeling and show the effectiveness of the proposed TCR-TSC model for reactive power compensating of the EAF. The installation site for this proposed system is No (1) Iron and Steel Mill (Pyin- Oo- Lwin). And data is taken from this Steel Mill. Simulation results will be provided by using MATLAB/ Simulink.
Abstract: Electric Arc Furnaces (EAFs) are unbalanced nonlinear and time varying loads, which can cause many problems in the power system quality. As the use of arc furnace loads increases in industry, the important of the power quality problems also increase. So, in order to optimize the usage of electric power in EAFs, it is necessary to minimize the effec...
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Effects of Distributed Generation on System Power Losses and Voltage Profiles (Belin Distribution System)
Chaw Su Hlaing,
Pyone Lai Swe
Issue:
Volume 3, Issue 3, June 2015
Pages:
36-41
Received:
11 April 2015
Accepted:
24 April 2015
Published:
15 May 2015
Abstract: In present times, the use of DG systems in large amounts in different power distribution systems has become very popular and is growing on with fast speed. Although it is considered that DG reduces losses and improves system voltage profile, this paper shows that this is usually true. The paper presents voltage stability index based approach which utilizes combine sensitivity factor analogy to optimally locate and size a multi-type DG in 48-bus Belin distribution test system with the aim of reducing power losses and improving the voltage profile. The multi-type DG can operate as; type 1 DG (DG generating real power only), and type 2 DG (DG generating both real and reactive power). It further shows that the system losses are reduced and the voltage profile improved with the location of type 2 DG than with the location of type 1 DG. It reaches a point where any further increase in number of DGs in the network results for minimizing power losses and voltage profiles improvement.
Abstract: In present times, the use of DG systems in large amounts in different power distribution systems has become very popular and is growing on with fast speed. Although it is considered that DG reduces losses and improves system voltage profile, this paper shows that this is usually true. The paper presents voltage stability index based approach which ...
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Short-term Electrical Energy Consumption Forecasting Using GMDH-type Neural Network
Tsado Jacob,
Usman Abraham Usman,
Saka Bemdoo,
Ajagun Abimbola Susan
Issue:
Volume 3, Issue 3, June 2015
Pages:
42-47
Received:
20 April 2015
Accepted:
29 April 2015
Published:
19 May 2015
Abstract: Electric load forecasting plays an important role in the planning and operation of the power system for high productivity in any institution of learning. A short-term electrical energy forecast for Gidan Kwano campus, Federal University of Technology Minna, Nigeria was carried out using GMDH-type neural network and the result was compared to that of regression analysis. GMDH-type neural network was used to train and test weekly energy consumed in the campus from September 2010 to December 2014. The neural network was trained using quadratic neural function. Root mean square error (RMSE) and mean absolute percentage error (MAPE) were used as performance indices to test the accuracy of the forecast. The neural network model gave a root mean square error (RMSE) of 0.1189, a mean absolute percentage error (MAPE) of 0.0922 and a correlation (R) value of 0.8995 while the regression analysis method gave a standard error of 10968.1 and a correlation (R) value of 0.1137. Results obtained show the efficacy of the GMDH-type neural network model in forecasting over the regression analysis method.
Abstract: Electric load forecasting plays an important role in the planning and operation of the power system for high productivity in any institution of learning. A short-term electrical energy forecast for Gidan Kwano campus, Federal University of Technology Minna, Nigeria was carried out using GMDH-type neural network and the result was compared to that o...
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A Wideband Directional Microstrip Slot Antenna for On-Body Applications
Mehdi Hamidkhani,
Behdad Arandian
Issue:
Volume 3, Issue 3, June 2015
Pages:
48-51
Received:
29 April 2015
Accepted:
13 May 2015
Published:
28 May 2015
Abstract: Antennas are one of the main components of every wireless telecommunication system. With wideband antennas for on-body applications, there are some additional features that should be considered including radiation and physical size. In this paper, we presented a wideband omnidirectional slot antenna with a reflector element improvised under the feed line in order to minimize the impact of body on the antenna. Curiously, this reflector element allows for directionality of the antenna. In the following sections of the paper we will show that less power can penetrate body tissues in the presence of reflector elements; thus, wideband directional antennas are influenced less by human body than omindirectional antenna.
Abstract: Antennas are one of the main components of every wireless telecommunication system. With wideband antennas for on-body applications, there are some additional features that should be considered including radiation and physical size. In this paper, we presented a wideband omnidirectional slot antenna with a reflector element improvised under the fee...
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Power System Stabilizer Design Using Compressed Rule Base of Fuzzy Logic Controller
Issue:
Volume 3, Issue 3, June 2015
Pages:
52-64
Received:
9 June 2015
Accepted:
18 June 2015
Published:
2 July 2015
Abstract: In this paper, the fuzzy logic controller (FLC) based power system stabilizer (PSS) with compressed / reduced rule is presented. The FLC rule base is generally based on empirical control rules. In this method, the fuzzy system with a large number of fuzzy rules is compressed to a fuzzy system with a reduced number of rules by removing the redundant and inconsistent rules from the rule base which doesn’t affect the performance of the fuzzy logic controller. The FLC based PSS has two input signals as speed deviation and derivative of speed deviation with an appropriate number of linguistic variables. The number of compressed rules in the rule base through the proposed dominant rule algorithm is reduced to a number as low in the number of selected linguistic variables to represent input and output signals. The application of the FLC with compressed rules as a power system stabilizer (CR-FPSS) is investigated by simulation studies on a single-machine infinite-bus system (SMIB). The superior performance of this compressed rule based fuzzy PSS (CR-FPSS) as compared to conventional PSS and proves the better efficiency of this new CR-FPSS. The reduced CPU computational time and storage space as compared to the fuzzy power system stabilizer (FPSS), proves its applicability in control.
Abstract: In this paper, the fuzzy logic controller (FLC) based power system stabilizer (PSS) with compressed / reduced rule is presented. The FLC rule base is generally based on empirical control rules. In this method, the fuzzy system with a large number of fuzzy rules is compressed to a fuzzy system with a reduced number of rules by removing the redundant...
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