Robust optimization based optimal chiller loading under cooling demand uncertainty

Fuzzy-based heat and power hub models for cost-emission operation of an industrial consumer using compromise programming

A framework to expedite joint energy-reserve payment cost minimization using a custom-designed method based on Mixed Integer Genetic Algorithm

A new wind power prediction method based on ridgelet transforms, hybrid feature selection and closed-loop forecasting

Short-term wind power forecasting based on support vector machine with improved dragonfly algorithm

In this paper short term power forecast of wind and solar power is proposed to evaluate the available output power of each production component. In this model, lead acid batteries used in proposed hybrid power system based on wind-solar power system. So, before the predicting of power output, a simple mathematical approach to simulate the lead–acid battery behaviors in stand-alone hybrid wind-solar power generation systems will be introduced. Then, the proposed forecast problem will be evaluated which is taken as constraint status through state of charge (SOC) of the batteries. The proposed forecast model includes a feature selection filter and hybrid forecast engine based on neural network (NN) and an intelligent evolutionary algorithm. This method not only could maintain the SOC of batteries in suitable range, but also could decrease the on-or-off switching number of wind turbines and PV modules. Effectiveness of the proposed method has been applied over real world engineering data. Obtained numerical analysis, demonstrate the validity of proposed method.

A new prediction model of battery and wind-solar output in hybrid power system

‬ We have described a compact antenna based on fractal and metamaterial loads techniques. The microstrip patch antenna is assumed as a basic antenna and then the effect of fractal structures is implemented. The fractal patch is considered as a right-handed element and then by adding a left-handed element, the antenna miniaturization is achieved by using the metamaterial loads technique. The equivalent circuit is also used to describe the element effect on miniaturization and parametric models clarify them. The proposed antenna is modified for wireless applications and experimental results confirm our simulation results. In addition, we show that the proposed antenna is suitable for reconfigurable. By joining the unit cells together with various arrangements and changing the effective length, the various inductances can be obtained. Finally, by adding reconfigurable characteristic to the proposed antenna, the gain and radiation pattern can be controlled as shows in this paper. The patch antenna has low bandwidth and gain and so we have developed the patch antenna with defected ground to improve the bandwidth and the Frequency Selective Surface (FSS) is used to achieve higher gain and bandwidth. The final antenna is covering 2.4, 3.5 and 5.5 GHz with higher gain than the patch antenna.

Compact and miniaturized microstrip antenna based on fractal and metamaterial loads with reconfigurable qualification

The metamaterial and fractal techniques are two main methods for antenna miniaturization and in this paper, we have modeled an especial shape of the antenna based on loop formation with metamaterial load for this aim. The metamaterial layer is made by multi parallel rings and the result shows that the final antenna size reduced drastically while the frequency shifts from 7 to 4 GHz. The antenna has Omni-directional pattern with the gain of 3.5 dBi, so the size is reduced around 40%for 4.5 GHz and another resonance is made at 2.5 GHz with a return lossless than −6 dB with more than 60% frequency shift. The reflection and transmission have been utilized for showing the left hand characteristic based on two port periodic simulations in HFSS full wave software. We show that how the metamaterial load can provide the circular polarization (CP) by controlling the current distribution. We also presented that by making slots we obtained the better Axial Ratio (AR) and miniaturized the antenna with reconfigurable qualification. As a result of fact, we show that by using metasurface we able to miniaturized the antenna and simultaneously achieved the circular polarization.

Miniaturization of microstrip loop antenna for wireless applications based on metamaterial metasurface

The compact microstrip antennas with the dual-band characteristic and reconfigurable qualification have been noticed and investigated in this paper. We have developed the slot microstrip antenna with Sierpinski carpet and Minkowski formations and then the metamaterial loads are placed on this antenna in the slot area. The reflection/transmission method has considered to obtain the permittivity and permeability of the split ring resonator (SRR) as a metamaterial. Finally, we show that by using some junction in the metamaterial layer, we can obtain reconfigurable characteristic. Both antennas have dual-band characteristic where the first antenna has two resonances at 3.2 and 4.5 GHz and in the second antenna by altering the metamaterial layer both resonances are occurring at 3.5 and 5.8 GHz. We show that the antenna has two resonance frequencies that matched with the metamaterial Double Negative (DNG) characteristic. Both antennas are printed on FR-4 also we compared measurement and simulation results together. Aforementioned antennas cover the main wireless, WiMAX and LTE bands with sufficient gain and high efficiency (more than 80% typically) with a bi-directional radiation pattern for the indoor application. Here, the metamaterial is used for controlling the resonances and Sierpinski carpet is developed for matching.

Microstrip Sierpinski fractal carpet for slot antenna with metamaterial loads for dual-band wireless application

4 Abstract: Modulation recognition is the main part of Smart Telecom receptors and to detect the type of signal, eliminating the interference, noise and measuring the spectrum is very useful and important. The received signals due to a variety of reasons including fading and multi-alignment phenomena and …. Are not very safe and must initially be separated and process of separation and noise eliminating to be done. For this purpose, signal separation is very important and separation of considered signal from the received signals has a great importance in the signal processing ; That one of its best applications is the elimination of telecommunication signal interference, noise elimination from the received signals and speech signals or image or information separation from solitary data and etc … Due to the extensive applications and its enormous importance, rapidly new and efficient algorithms were introduced in order to process and design them. Despite the exiting independence condition, the issue of initial resources derivation from the several signal production sources independent from each other is possible that we knew it by the name of blind signal separation. The main idea in all signal separation algorithms is the same and is the finding a criterion for measurement of a density function's non-Gaussian. This criterion must be simple and meanwhile be resistant to the solitary data and noises. In this paper blind signal separation is investigated using the method of Convolution Mixture in the intelligent telecommunication systems (Coming) and finally will be investigated via MATLAB.

/pdf/blind-signal-separation-ica-using-the-method-of-convolution-2mw198m2zt.pdf

Gohar Varamini

Papers

A new prediction model of battery and wind-solar output in hybrid power system

Compact and miniaturized microstrip antenna based on fractal and metamaterial loads with reconfigurable qualification

Miniaturization of microstrip loop antenna for wireless applications based on metamaterial metasurface

Microstrip Sierpinski fractal carpet for slot antenna with metamaterial loads for dual-band wireless application

Blind Signal Separation (ICA) Using the Method of Convolution Mixture in the Intelligent Telecommunication Systems (COMINT) Using MATLAB