Showing 17 results for Ahmadi
Ali Ghaffari, Mohammad Reza Homaeinezhad, Yashar Ahmadi, Mostafa Rahnavard,
Volume 5, Issue 2 (June 2009)
Abstract
In this study, a mathematical model is developed based on algebraic equations which is capable of generating artificially normal events of electrocardiogram (ECG) signals such as P-wave, QRS complex, and T-wave. This model can also be implemented for the simulation of abnormal phenomena of electrocardiographic signals such as ST-segment episodes (i.e. depression, elevation, and sloped ascending or descending) and repolarization abnormalities such as T-Wave Alternans (TWA). Event parameters such as amplitude, duration, and incidence time in the conventional ECG leads can be a good reflective of heart electrical activity in specific directions. The presented model can also be used for the simulation of ECG signals on torso plane or limb leads. To meet this end, the amplitude of events in each of the 15-lead ECG waveforms of 80 normal subjects at MIT-BIH Database (www.physionet.org) are derived and recorded. Various statistical analyses such as amplitude mean value, variance and confidence intervals calculations, Anderson-Darling normality test, and Bayesian estimation of events amplitude are then conducted. Heart Rate Variability (HRV) model has also been incorporated to this model with HF/LF and VLF/LF waves power ratios. Eventually, in order to demonstrate the suitable flexibility of the presented model in simulation of ECG signals, fascicular ventricular tachycardia (left septal ventricular tachycardia), rate dependent conduction block (Aberration), and acute Q-wave infarctions of inferior and anterior-lateral walls are finally simulated. The open-source simulation code of above abnormalities will be freely available.
Sh. Gorgizadeh, A. Akbari Foroud, M. Amirahmadi,
Volume 8, Issue 2 (June 2012)
Abstract
This paper proposes a method for determining the price bidding strategies of
market participants consisting of Generation Companies (GENCOs) and Distribution
Companies (DISCOs) in a day-ahead electricity market, while taking into consideration the
load forecast uncertainty and demand response programs. The proposed algorithm tries to
find a Pareto optimal point for a risk neutral participant in the market. Because of the
complexity of the problem a stochastic method is used. In the proposed method, two
approaches are used simultaneously. First approach is Fuzzy Genetic Algorithm for finding
the best bidding strategies of market players, and another one is Mont-Carlo Method that
models the uncertainty of load in price determining algorithm. It is demonstrated that with
considering transmission flow constraints in the problem, load uncertainty can considerably
influences the profits of companies and so using the second part of the proposed algorithm
will be useful in such situation. It is also illustrated when there are no transmission flow
constraints, the effect of load uncertainty can be modeled without using a stochastic model.
The algorithm is finally tested on an 8 bus system.
A. H. Hadjahmadi, M. M. Homayounpour, S. M. Ahadi,
Volume 8, Issue 2 (June 2012)
Abstract
Nowadays, the Fuzzy C-Means method has become one of the most popular
clustering methods based on minimization of a criterion function. However, the
performance of this clustering algorithm may be significantly degraded in the presence of
noise. This paper presents a robust clustering algorithm called Bilateral Weighted Fuzzy CMeans
(BWFCM). We used a new objective function that uses some kinds of weights for
reducing the effect of noises in clustering. Experimental results using, two artificial
datasets, five real datasets, viz., Iris, Cancer, Wine, Glass and a speech corpus used in a
GMM-based speaker identification task show that compared to three well-known clustering
algorithms, namely, the Fuzzy Possibilistic C-Means, Credibilistic Fuzzy C-Means and
Density Weighted Fuzzy C-Means, our approach is less sensitive to outliers and noises and
has an acceptable computational complexity.
S. Ahmadi, A. Vahedi,
Volume 11, Issue 3 (September 2015)
Abstract
In this paper a multiobjective optimal design method of interior permanent magnet synchronous motor ( IPMSM) for traction applications so as to maximize average torque and to minimize torque ripple has been presented. Based on train motion equations and physical properties of train, desired specifications such as steady state speed, rated output power, acceleration time and rated speed of traction motor are related to each other. By considering the same output power, steady state speed, rated voltage, rated current and different acceleration time for a specified train, multiobjective optimal design has been performed by Broyden–Fletcher–Goldfarb–Shanno (BFGS) method and finite element method (FEM) has been chosen as an analysis tool. BFGS method is one of Quasi Newton methods and is counted in classic approaches. Classic optimization methods are appropriate when FEM is applied as an analysis tool and objective function isn’t expressed in closed form in terms of optimization variables.
A. Hamidi, A. Ahmadi, S. Karimi,
Volume 14, Issue 1 (March 2018)
Abstract
In AC-DC power conversion, active front end rectifiers offer several advantages over diode rectifiers such as bidirectional power flow capability, sinusoidal input currents and controllable power factor. A digital finite control set model predictive controller based on fixed-point computations of an active front end rectifier with unity displacement of input voltage and current to improve dynamic response has been presented in this paper. Here by using a predictive cost function and fixed-point computations, the optimal switching state to be applied in the next sampling is selected. The low-cost architecture is implemented on a FPGA platform. Designed architecture is constructed based on fixed-point arithmetic with minimal functional units. The control algorithm, which is used in this architecture, is Finite-Set Model Predictive Control (FS-MPC). Compared with other controllers, this controller provides a much better dynamic performance. Finally, in order to evaluate the accuracy of the fixed-point computations several cases for various loading conditions and word lengths are verified.
M. Esmaeilzadeh, I. Ahmadi, N. Ramezani,
Volume 14, Issue 2 (June 2018)
Abstract
Distributed generation (DG) has been widely used in distribution network to reduce the energy losses, improve voltage profile and system reliability, etc. The location and capacity of DG units can influence on probability of protection mal-operation in distribution networks. In this paper, a novel model for DG planning is proposed to find the optimum DG location and sizing in radial distribution networks. The main purpose of the suggested model is to minimize the total cost including DG investment and operation costs. The operation costs include the cost of energy loss, the cost of protection coordination and also the mal-operation cost. The proposed DG planning model is implemented in MATLAB programming environment integrated with DIgSILENT software. The simulation results conducted on the standard 38-bus radial distribution network confirm the necessity of incorporating the protection coordination limits in the DG planning problem. Additionally, a sensitivity analysis has been carried out to illustrate the significance of considering these limits.
H. Ahmadi, A. Rajaei, M. Nayeripour, M. Ghani,
Volume 14, Issue 4 (December 2018)
Abstract
Considering the increasing usage of the clean and renewable energies, wind energy has been saliently improved throughout the world as one of the most desired energies. Besides, most power houses and wind turbines work based on the doubly-fed induction generator (DFIG). Based on the structure and the how-ness of DFIG connection to the grid, two cases may decrease the performance of the DFIG. These two cases are known as a fault and a low-voltage in the grid. In the present paper, a hybrid method is proposed based on the multi-objective algorithm of krill and the fuzzy controller to improve the low-voltage ride through (LVRT) and the fault ride through (FRT). In this method, first by using the optimal quantities algorithm, the PI controllers’ coefficients and two variables which are equal to the demagnetize current have been calculated for different conditions of fault and low voltage. Then, these coefficients were given to the fuzzy controller. This controller diagnosed the grid condition based on the stator voltage and then it applied the proper coefficients to the control system regarding the diagnosed condition. To test the proposed method, a DFIG is implemented by taking the best advantages of the proposed method; additionally, the system performance has been tested in fault and low voltage conditions.
P. Ahmadi, I. Gholampour,
Volume 15, Issue 2 (June 2019)
Abstract
Analyzing motion patterns in traffic videos can be employed directly to generate high-level descriptions of their content. For traffic videos captured from intersections, usually, we can easily provide additional information about traffic phases. Such information can be obtained directly from the traffic lights or through traffic lights controllers. In this paper, we focus on incorporating additional information to analyze the traffic videos more efficiently. Using side information on traffic phases, the semantic of motion patterns from traffic intersection scenes can be learned more effectively. The learning is performed based on optical flow features extracted from training video clips, and applying them to supervised topic models such as MedLDA and MedSTC. Based on such models, any video clip can be represented based on the learned patterns. Such representations can be further exploited in scene analysis, rule mining, abnormal event detection, etc. Our experiments show that employing side information in intersection video analysis leads to improvement in discovering scene pattern. Moreover, supervised topic models achieve about 4% improvement in abnormal event detection, compared to the unsupervised ones, in terms of area under ROC.
M. Ahmadi Jirdehi, V. Sohrabi-Tabar,
Volume 17, Issue 3 (September 2021)
Abstract
Control center of modern power system utilizes state estimation as an important function. In such structures, voltage phasor of buses is known as state variables that should be determined during operation. To specify the optimal operation of all components, an accurate estimation is required. Hence, various mathematical and heuristic methods can be applied for the mentioned goal. In this paper, an advanced power system state estimator is presented based on the adaptive neuro-fuzzy interface system. Indeed, this estimator uses advantages of both artificial neural networks and fuzzy method simultaneously. To analyze the operation of estimator, various scenarios are proposed including impact of load uncertainty and probability of false data injection as the important issues in the electrical energy networks. In this regard, the capability of false data detection and correction are also evaluated. Moreover, the operation of presented estimator is compared with artificial neural networks and weighted least square estimators. The results show that the adaptive neuro-fuzzy estimator overcomes the main drawbacks of the conventional methods such as accuracy and complexity as well as it is able to detect and correct the false data more precisely. Simulations are carried out on IEEE 14-bus and 30-bus test systems to demonstrate the effectiveness of the approach.
T. Agheb, I. Ahmadi, A. Zakariazadeh,
Volume 17, Issue 3 (September 2021)
Abstract
Optimal placement and sizing of distributed renewable energy resources (DER) in distribution networks can remarkably influence voltage profile improvement, amending of congestions, increasing the reliability and emission reduction. However, there is a challenge with renewable resources due to the intermittent nature of their output power. This paper presents a new viewpoint at the uncertainties associated with output powers of wind turbines and load demands by considering the correlation between them. In the proposed method, considering the simultaneous occurrence of real load demands and wind generation data, they are clustered by use of the k-means method. At first, the wind generation data are clustered in some levels, and then the associated load data of each generation level are clustered in several levels. The number of load levels in each generation level may differ from each other. By doing so the unrealistic generation-load scenarios are omitted from the process of wind turbine sizing and placement. Then, the optimum sizing and placement of distributed generation units aiming at loss reduction are carried out using the obtained generation-load scenarios. Integer-based Particle Swarm Optimization (IPSO) is used to solve the problem. The simulation result, which is carried out using MATLAB 2016 software, shows that the proposed approach causes to reduce annual energy losses more than the one in other methods. Moreover, the computational burden of the problem is decreased due to ignore some unrealistic scenarios of wind and load combinations.
M. Ahmadinia, J. Sadeh,
Volume 17, Issue 4 (December 2021)
Abstract
In this paper, an accurate fault location scheme based on phasor measurement unit (PMU) is proposed for shunt-compensated transmission lines. It is assumed that the voltage and current phasors on both sides of the shunt-compensated line have been provided by PMUs. In the proposed method, the faulted section is determined by presenting the absolute difference of positive- (or negative-) sequence current angles index, firstly. After determining faulted section, the voltage phasor at the shunt-compensator terminal is estimated via the sound section. The faulted section can be assumed as a perfect transmission line that synchronized voltage and current phasors at one end and voltage phasor at the other end are available. Secondly, a new fault location algorithm is presented to locate the precise fault point in the faulted section. In this algorithm, the location of the fault and the fault resistance are calculated simultaneously by solving an optimization problem, utilizing the heuristic Particle Swarm Optimization (PSO) method. The simulation results in MATLAB/SIMULINK platform demonstrate the high performance of the proposed method in finding the fault location in shunt-compensated transmission lines. The proposed scheme has high accuracy for both symmetrical and asymmetrical fault types and high fault resistance.
S. A. Mozdawar, A. Akbari Foroud, M. Amirahmadi,
Volume 18, Issue 1 (March 2022)
Abstract
This paper scrutinizes the impact of different renewable energy sources (RES) development policies on competitiveness within multiple electricity markets (MEMs). Also, the variation in market power indices by increasing the integration of the markets undergoing symmetric and asymmetric RES development policies is investigated. To do so, several stochastic mixed-integer non-linear programming objective functions are used in the agent-based simulation framework to model the power plants’ behavior and markets. The case study shows in the low RES penetrated markets, one can say the more integration level of the markets, the lower potential of exercising market power. The reciprocal judgment is true for a high RES penetrated market. Also, large asymmetry in RES development between markets within MEMs may bring about market power problem for a high RES penetrated market. Unlike the asymmetric RES development policies, adopting homogeneous policies in RES development within MEMs reduces the market power potential in all markets and this potential decreases with the increase in the integration of the markets.
Y. Fattahyan, N. Ramezani, I. Ahmadi,
Volume 18, Issue 3 (September 2022)
Abstract
Using doubly-fed induction generator (DFIG) based onshore wind farms in power systems may lead to mal-operation of the second zone (Z2) of distance protection due to the uncertain number of available wind turbines on the one hand and the function of DFIGs control system to maintain the bus voltage on the other hand. In such cases, variable injected current by the wind farm causes distance relay fall in trouble to distinguish whether the fault point is in the Z2 operating area or not. In the current study, an adaptive settings scheme is proposed to determine the Z2 setting value of distance relays for such cases. The proposed method is based on the adaptive approach and the settings group facility of the commercial relays. The proposed method applies the k-means clustering approach to decrease the number of setting values calculated by the adaptive approach to the number of applicable settings group in the distance relay and uses the Particle Swarm Optimization (PSO) algorithms to achieve the optimum setting values. The high accuracy of the proposed method in comparison with other methods, suggested in the literatures, is shown by applying them to the IEEE 14-bus grid.
Hassan Alizadeh Shyrayeh, Iraj Ahmadi, Mohammad Mirzaie, Masoud Ahmadi Gorji,
Volume 18, Issue 4 (December 2022)
Abstract
The progressive application of non-linear loads in distribution systems (DS) increases current harmonics flow in DS's apparatuses, especially distribution transformers (DTs). Since DTs' operating temperature rises due to the harmonics flow, their loading should be reduced such that the hot spot temperature (HST) is preserved under its permissible value. This means that DTs' available capacity is influenced by load harmonic content. In this paper, a novel formulation for DTs' failure rate in the presence of harmonics is presented as a function of load harmonic contents. Using the suggested equivalent failure rate, DTs' available capacity in harmonic polluted DS is mathematically formulated. Additionally, the presence of the harmonic increases the HST, leading to DTs' aging acceleration. Therefore, the impact of harmonic components on DTs' aging is arithmetically modeled. To evaluate the efficacy of the suggested reliability model, it is applied to three distinct DTs having respectively industrial, commercial, and residential loads. The obtained results indicate that the available capacity of DTs with the same rated capacity would be different regarding to their load harmonic contents. On the other hand, it is comprehended from the achieved results that the aging acceleration factor (Faa) of the DTs increases owing to their load harmonic contents.
A. Rezapour, Z. Ahmadian,
Volume 19, Issue 1 (March 2023)
Abstract
Shamir’s secret sharing scheme is one of the substantial threshold primitives, based on which many security protocols are constructed such as group authentication schemes. Notwithstanding the unconditional security of Shamir's secret sharing scheme, protocols that are designed based on this scheme do not necessarily inherit this property. In this work, we evaluate the security of a lightweight group authentication scheme, introduced for IoT networks in IEEE IoT Journal in 2020, and prove its weakness against the linear subspace attack, which is a recently-proposed cryptanalytical method for secret sharing-based schemes. Then, we propose an efficient and attack-resistant group authentication protocol for IoT networks.
A. Hamidi, S. Karimi, A. Ahmadi,
Volume 19, Issue 2 (June 2023)
Abstract
One of the problems in digital control of power converters is calculation time in each sampling instant which effect on cost and complexity of digital controller. In this paper, a formula is introduced for calculating the number of clock cycles in each sample then interaction between sampling frequency and implementation cost (number of functional units and word length) of FPGA-based digital controller of DC-AC converter (three-phase four-legs inverter) is verified. The digital architecture is built on finite set model predictive control, and implemented on the FPGA board based on fixed-point calculations. We consider two digital architectures for design the controller in this study. One with four functional units and another with six functional units. This study aims to develop a mathematical equation for the number of clock cycles in each time instant to select the best switching state in the control algorithm, which affects the sampling frequency and clock frequency. Based on the obtained results, the number of functional units, word-length, and the number of switches determine the maximum clock cycles. By knowing maximum clock cycles the maximum sampling frequency is determined. In structure with four functional units, the maximum sampling frequency is 71 kHz for WL=8 bits and 17.7 kHz for WL=32 bits, and in structure, with six functional units, the maximum sampling frequencies are 97.6 and 24.4 kHz for WL=8 and WL=32 bits, respectively. In architecture with more functional units, we have greater sampling frequency with more accuracy and cost. The results obtained from this paper can be a reference for digital controller design.
Atefeh Sohrabi, Hamideh Dashti, Javad Ahmadi-Shokouh,
Volume 19, Issue 4 (December 2023)
Abstract
In this article, an active electrically small Horn antenna for very high frequency (VHF) and ultra-high frequency (UHF) frequencies is presented. The proposed horn antenna has a height of 5 cm and a diameter of 4.28 cm which can cover 6-12 GHz without a special active circuit with the VSWR of less than 2. A Non-foster Active Adaptation Circuit is used to reduce the antenna input frequency from 164 MHz to 880 MHz. Good matching is visible between the simulation results and the measurement of the antenna reflection coefficient with the active matching circuit. The proposed structure has more than 137 % bandwidth. With the proposed active antenna, the problem of non-portability of VHF and UHF Horn antenna antennas has been solved. Finally, by analyzing the time domain, the stability of the circuit is examined, and the results of the stability test show that the system, including the antenna and the circuit, is stable. The antenna and the matching circuits are simulated by CST microwave studio and advanced design system, respectively.
