جستجوی مقالات مرتبط با کلیدواژه « Self » در نشریات گروه « برق »

This paper develops a new possibilistic-scenario model for a wind power plant to determine its optimal self-scheduling (SS) in the presence of high-impact low-probability events uncertainty. Nowadays, in the context of the power system, examining the effects of extreme weather events in the category of high-impact low-probability (HILP) events has become one of the most important issues for researchers all around the world. There are so many reports of HILP events which acknowledge that these incidents can directly affect the power plants and cause them to fail. Generally, the self-scheduling of generating units in the pre-extreme weather conditions would be different from normal conditions. In such manners, this paper tries to address the self-scheduling problem of a wind power plant in pre-extreme weather conditions. For this purpose, there are numerous uncertainty sources in the SS problem that could affect the final results which include electricity prices, wind power production and contingency-based lack of production in the face of HILP events. In this regard, this paper proposes an efficient hybrid probabilistic-possibilistic assessment tool for dealing with these uncertainties. Additionally, CVaR evaluation was used as the intrinsic risk management tool of both probabilistic and possibilistic parameters in the SS problem

Usually, in monitoring schemes the nominal value of the process parameter is assumed known. However, this assumption is violated owing to costly sampling and lack of data particularly in healthcare systems. On the other hand, applying a fixed control limit for the risk-adjusted Bernoulli chart causes to a variable in-control average run length performance for patient populations with dissimilar risk score distributions in monitoring clinical and surgical performance. To solve these problems, a self-starting scheme is proposed based on a parametric bootstrap method and dynamic probability control limits for the risk-adjusted Bernoulli cumulative sum control charts. The advantage of the proposed control charts lies in the use of probability control limits when any assumptions about the patients’ risk distributions and process parameter. Simulation studies show that both proposed schemes have good performance under various shifts.

In this paper, a new approach is proposed for voltage and current harmonics compensation in grid-connected microgrids (MGs). If sensitive loads are connected to the point of common coupling (PCC), compensation is carried out in order to reduce PCC voltage harmonics. In absence of sensitive loads at PCC, current harmonics compensation scenario is selected in order to avoid excessive injection of harmonics by the main grid. In both scenarios, compensation is performed by the interface converters of distributed generation (DG) units. Also, to decrease the asymmetry among phase impedances of MG, a novel structure is proposed to generate virtual impedance. At fundamental frequency, the proposed structure for the virtual impedance improves the control of the fundamental component of power, and at harmonic frequencies, it acts to adaptively improve nonlinear load sharing among DG units. In the structures of the proposed harmonics compensator and the proposed virtual impedance, a self-tuning filter (STF) is used for separating the fundamental component from the harmonic components. This STF decreases the number of phase locked loops (PLLs). Simulation results in MATLAB/SIMULINK environment show the efficiency of the proposed approach in improving load sharing and decreasing voltage and current harmonics.

In this paper we address the issue of recognizing Farsi handwritten words. Two types of gradient features are extracted from a sliding vertical stripe which sweeps across a word image. These are directional and intensity gradient features. The feature vector extracted from each stripe is then coded using the Self Organizing Map (SOM). In this method each word is modeled using the discrete Hidden Markov Model (HMM). To evaluate the performance of the proposed method, FARSA dataset has been used. The experimental results show that the proposed system, applying directional gradient features, has achieved the recognition rate of 69.07% and outperformed all other existing methods.

Many industrial processes are Multi-Input Multi-Output (MIMO) that has more than one controlled variable. Therefore, without considering the impact of these factors it is not possible to achieve the desired performance. In this paper, two methods, adaptive controller and self-tuning fuzzy PID controller is used to control the quadruple-tank process. Although the both presented methods are able to eliminate disturbance effect and reach steady-state with acceptable performance, the fuzzy controller is preferred to the adaptive controller due to the lower computational effort. Moreover, the fuzzy controller does not need the transfer function of the system, while it has a simple design procedure and simple arithmetic. Superiority of the proposed method is automatic adjustment of multivariable fuzzy controller parameters to achieve desirable performance.

In this paper, a method using an evolutionary algorithm to automatically set-up the color-feature model of an omnidirectional vision system will be introduced. The mentioned method, in addition to avoiding the issue of over-reliance on lighting conditions when the soccer robot is performing image processing, can also very e ectively speed up the parameter setup procedure of the robot vision system. Hence, when the robot is moving in the soccer eld, it can nish target object detection and self-localization in real time. In order to verify the e ectiveness of the mentioned method, tests have been conducted under di erent bad lighting conditions, and the experimental results show that the soccer robot can always set up the parameters of the vision system. It can also set up the color-feature model that is applicable to the operational environment at that moment and detect target objects such as goals and the eld. Meanwhile, through relative location between detected target objects and the robot, self-localization and path planning can be nished.

The aim of this paper is optimal operation of a divided-wall column (DWC) based on self-optimizing control (SOC). By now, the proposed SOC methods have been based on linearization of the process. The novelty of this paper is to overcome this shortcoming of the local optimality of SOC. Theoretically, changes in optimal sensitivity matrix from nominal design, due to changes in operating condition, make SOC deviate from steady state optimality. These deviations from optimal operation, in already available SOC structures, have to be counteracted by optimization layer in the control structure hierarchy which involves solving a large nonlinear optimization problem online. The proposed method in this paper solves this problem with modeling optimal sensitivity matrix with Takagi-Sugeno fuzzy inference. This fuzzy inference system is tuned offline. The proposed method is dynamically validated and compared with conventional SOC. The results showed that conventional SOC had high value of loss and deviated from optimal operation. However, in the same operating condition, the proposed method with the aid of Takagi-Sugeno fuzzy inference system, which involves online calculation of weighted average of some linear function, imposed small loss, made DWC track optimal trajectory and removed the need for online solving large nonlinear optimization problem.

Self-affine maps were successfully used for edge detection, image segmentation, and contour extraction. They belong to the general category of patch-based methods. Particularly, each self-affine map is defined by one pair of patches in the image domain. By minimizing the difference between these patches, the optimal translation vector of the self-affine map is obtained. Almost all image processing methods, developed by using self-affine maps, take advantage of either the attracting or repelling behaviors which have been, only, experimentally investigated. In this paper, we analytically study the properties of self-affine maps and prove their attracting and repelling behaviors. Furthermore, the new corner/edge pointing behavior is also proposed for contractive self-affine maps. We show that the conventional cost function of self-affine maps may cause critical uncertainty due to providing multiple equivalent optimal translation vectors. Thus, a new cost function is suggested to effectively tackle this problem. Forevaluation, it is used with the selfaffine snake (SAS) for contour extraction. Experimental results demonstrated that the enhanced SAS provides better performance compared to a number of different active contour methods in terms of both solution quality and CPU time.

In this study, workability and mechanical properties of fiber reinforced self-compacting lightweight concretes (FRSCLC) were investigated. Concrete samples were produced with steel fiber include low and high carbon were added. Fluidity of FRSCLC has been conducted by two categories of flow ability property and viscosity of fresh concrete. Mechanical performance of the concrete mixes was determined with short and long-term tests, which include compressive and flexural strength at 3, 7, 28 and 365 days. The test results showed that adding fibers to self-compacting lightweight concrete mixtures decreased workability. On the other hand, compressive strength was lower enhanced compare to the results of flexural strength. As a result, compressive and flexure strengths of SCLWC’s increased up to 30% and 43% adding fiber at 28 days, respectively.

Random Early Detection (RED) is one of the most commonly used Active Queue Management (AQM) algorithms that is recommended by IETF for deployment in the network. Although RED provides low average queuing delay and high throughput at the same time, but effectiveness of RED is highly sensitive to the RED parameters setting. As network condition varies largely, setting RED's parameters with fixed values is not an efficient solution. We propose a new method to dynamically tuning RED's parameters. For this purpose, we compute the rate of which the queue is occupied and consider it as a congestion metric that will be forecasted when the queue is overloaded. This meter is used to dynamically setting RED parameters. The simulation results show the effectiveness of the proposed method. According to the results, we achieve a significantly higher utilization and less packet loss comparing to original RED algorithm in dynamic conditions of the network.

In this article, our aim is to quantify the impact of three reference architectural styles, i.e. Aspect-peer-to-peer, Aggregator-escalator-peer, and Chain-of-configurators on the maintainability attribute in self-healing systems. To do so, we used metrics of coupling and cohesion. To show the effectiveness of our method, we applied it to the Wireless Body Area Network (WBAN) as a case study. Our findings showed the Chain-of-configurators architectural style, in comparison with two other styles, had the least (best) coupling and the most (best) cohesion. In fact, it was the best style from the maintainability point of view.

Ubiquitous power-law as a fingerprint of Self-Organized Criticality (SOC) is used for describing catastrophic events in different fields. In this paper, by investigating the prerequisites of SOC, we show that SOC-like dynamics drive correlation among disturbances in Iran bulk power system. Existence of power-law region in the probability distribution is discussed for empirical data using Maximum likelihood estimat­ion. To verify the results, long time correlation is evaluated in terms of Hurst exponents by means of statistical analysis of time series including Rescaled Range (R/S) and Scaled Windowed Variance (SWV) analysis. Also, Sensitivity analysisshowed that for correct inference in existence of SOC in power systems, all disturbances should berecorded to be used in statistical analyses. Greater thresholds for recording disturbances lead to underestimate the Hurst exponent.

An innovative TiO2/iron oxide/Ag nanoparticles with crystal size of about 25 nm was synthesized on polyester fabric to achieve different multi-features including super-paramagnetism, antibacterial and enhanced self-cleaning properties. Treatment temperature was varied at boil and 130°C, creating TiO2/magnetite/silver and TiO2/hematite/silver nanoparticles, respectively. The alkaline hydrolysis of polyester surface was accompanied by the nanoparticles synthesis, which forms more active surface for nanoparticles adsorption. The co-operation of iron oxide and silver nanoparticles on TiO2 surface synergistically improved the self-cleaning efficiency of titanium dioxide nanoparticles by separation of electron-hole pairs, three and four times for fabrics treated with TiO2/Fe3O4/silver and TiO2/α-Fe2O3/silver nanoparticles, respectively comparing with their corresponding control samples. Moreover, both TiO2/iron oxide/Ag nanoparticles treated samples indicated antibacterial efficiency of ≥99.99% against Staphylococcus aureus bacteria. Findings suggested that the developed magneto, bio and photo activities could be idealized depending on the end use of the treated fabrics through incorporation of different iron oxides in the prepared nanoparticles; magnetite providing the highest saturation magnetization and hematite the best self-cleaning towards degradation of Methylene Blue under sunlight irradiation.

In the present paper, we use a gold electrode modified by 2-(3, 4-dihydroxy phenyl) benzothiazole self-assembled monolayer (DHT-SAM) for the determination of epinephrine (EP) and uric acid (UA). Initially, DHT-SAM was characterized by different techniques. CV was used to investigate the redox properties of the modified electrode at various scan rates. The apparent charge transfer rate constant, ks and transfer coefficient (α) were calculated. Next, electro oxidation of epinephrine (EP) and uric acid (UA) on a gold electrode modified by a self-assembled monolayer of DHT mediated was investigated. At the optimum pH of 7.0, the oxidation of EP occurs at a potential about 200 mV less positive than that of an unmodified gold electrode. The values of transfer coefficients (α = 0.35), catalytic rate constant (k = 4.4 × 104 M-1s-1) and diffusion coefficient (D = 1.03 × 10-6cm2s-1) were calculated for EP, using electrochemical approaches. Differential pulse voltammetry (DPV) exhibited a linear dynamic range over the concentration range of 0.5–400.0 µM and a detection limit (3s) of 0.11 µM for EP in pH= 7. Finally, simultaneous determination of EP and UA at the modified electrode was described and used for the determination of EP in EP ampoule.

Because of the remarkable market share of Generation Companies (GENCOs) in the restructured electricity market, GENCOs competition for supplying electric of power may occur under oligopolistic environment. In such condition, for the sake of maximum profit each GENCO should provide optimal bids. This paper focuses on the short-run bidding behavior of GENCOs under an oligopolistic power market, while the interaction among GENCOs is studied by game theory. In case of non-cooperative GENCOs competition, game theory proposed Nash equilibrium as an optimal bidding strategy for each GENCO. On the other hand, GENCOs can make alliances with each other in order to propose their coordinated bids, the so called coalition condition. It can be argued that, the coalition's optimal bidding strategy will be calculated via cooperative game theory. Then the obtained profit from such coalition will be allocated among its members based upon Shapley value. In this paper it is assumed that GENCOs submit their bidding blocks in an economic model of supply function equilibrium (SFE). In order to modeling optimal bidding strategy problem of each GENCO, the bi-level programming method is employed in this research. In the upper level, the profit of GENCOs were maximized and in the lower level, the Independent System Operator (ISO) with the aim of minimizing consumers’ payment subjected to secured operation of power system, will clear the market. The proposed methodology is implemented on a 30-bus IEEE test system; considering both non-cooperative and cooperative competitions, while GENCOs optimal bidding strategies is calculated. Numerical results show that the efficient alliance has impressive impact on GENCOs profits.