نشریه عصر برق
پیاپی 11 (زمستان 1397)

Nowadays, in the power industry, the reduction of power outage and stability of the system due to disturbances is one of the important issues for network operators. Operation of power system depends on the nature of all elements in network. One of the factors that help maintain synchronism during fault is inertia of synchronous generators. This inertia will prevent the acceleration and loss of synchronization. Nowadays penetration of wind farms is increasing and asynchronous generators have lower inertia compared with synchronous generators, so the transient stability decreases in the network. This paper reviews the effect of system inertia reduction on transient stability in the presence of asynchronous generators in the power grid using the energy function. As a simulation, the asynchronous generator is modeled as an equivalent conventional synchronous generator with negligible inertia. The evaluation is done on a sample network for calculating critical energy and critical clearing time (CCT) using three methods which are called the closest unstable equilibrium point (UEP), controlling unstable equilibrium point, and the potential energy boundary surface (PEBS). Reduction of line reactance is proposed by using FACTS devices to compensate the inertia reduction of the system in the presence of an asynchronous generator and the compensation amount in the transmission lines will be calculated.

Underwater imagery is one of the research areas of interest for marine exploration, such as environmental assessment, mineral detection and underwater living organisms analysis. For this research, clear, high-quality images of underwater objects are necessary. Underwater images, however, have always had visual, opaque, or excessive glare due to the lack of uniform and low light, which in turn results in the loss of detail in underwater images. On the other hand, the greater the depth of water, the more intense the light will diminish, which will result in the absorption of a series of wavelength by the water. This paper reviews, categorizes and compares the methods for enhancing underwater images. The results of this research show that color correction methods show better performance among other methods.

Microgrids are considered as a platform for the use of distributed energy resources (DERs). The traditional AC distribution systems result in the emergence of AC grids. In order to reduce costs and losses and increase reliability, recently, DC distribution systems and subsequently DC microgrids have been considered. In this paper, the quality of DC voltages during the islanded mode is studied. In this mode, DERs are usually controlled by droop characteristics. In the use of the droop characteristics, the micro grid voltage deviation occurs from a nominal value. For voltage restoration, low band width communications as a part of secondary control are used. This control level, provides voltage restoration with one of two centralized and distributed approaches. In this paper, the voltage restoration with these two approaches is studied and analyzed, and then a comparison is presented. It is shown that for the centralized approach, the point of common coupling has desirable voltage quality and for the distributed approach, DERs buses have desirable voltage quality. For verification, the time domain simulation of a DC microgrid is used.

The field of medical image processing includes a wide range of applications from automated screening of diabetic retinopathy based on retinal images to MRI segmentation for tumor recognition. Various machine learning classification and clustering approaches have been studied in literature with the purpose of improving the accuracy of the screening methods. Some studies used manually feature extraction of fundus images by image processing experts. In recent years, a new approach for image classification and diagnosis without using any manual feature extraction is proposed based on convolutional neural network (CNN). The CNNs are based on deep learning concept have more convolutional and hidden layers and are more powerful envolving the high dimension inputs such as medical images. In medical imaging and diagnosis, training a deep CNN from scratch is difficult because it requires a large amount of labeled training data and the training procedure is a time consuming task to ensure proper convergence. Therefore, a very common method to train CNNs for medical diagnosis is fine-tuning a pre-trained CNN. Some of these powerful pre-trained CNNs are the GoogleNet, CifarNet and AlexNet which have been trained on the ImageNet as a a large databas

In this paper we use new neural network for modeling and fault detection of KAHAK wind turbine. We use real data from KAHAK wind farm that installed in Qazvin province. Our new neural network is a neural network that we optimizing the cost function of that with genetic algorithm. We use MATLAB software for simulation and result of article shown in figures and tables.

Process of quality of service (Qos) evaluation and optimization for mobile telecommunication networks is consisted of daily collection of key performance indicators (KPI) reports, determination and fixing of defects, and network testing to ensure the omission of the defects. Drive test is common approach of testing which is time-consuming and expensive due to necessity for experts and equipment. To overcome these limitations, this paper proposes a new software-based testing method using OPTIMA software. Performance of the proposed method together with drive test approach have been studied and evaluated for the 70 BTS sites of Kerman GSM network as the statistical society. The results demonstrate that the proposed method provides performance similar to that of drive test for defect fixing. However, this software method not only removes the dependency to experts and equipment, but also reduces the testing time about one-third compared to the drive test.

In this paper, simulation the behavior of a single neuron, and the implementation of the hardware of a biochemical neuron according to the Hodgkin-Huxley model is investigated, that is closely resembles the real neuron, and its implementation is very difficult, But with the help of re-configuration and implementation on parallel, the FPGAbased hardware design of the optimized neuronal system was performed. For this purpose, we have been using a variety of hardware ideas for the implementation of single-neurons to design the best type of complete neuron based on high speed, compactness, high precision and expandability. Some of the ideas in design and implementation include doing limited digital calculations, simplifying mathematical functions, and converting floating-point operations to fixed-point, which have the optimization and reduction of consumable hardware, have the maximum parallelism and the precision of the production of the output signals. The model presented in this paper is very important for many scientists in the field of cognitive neuroscience.

In this article; an islanded distribution network, which is connected with Distributed Generation (DG), is investigated. A distribution network that be able of operating in both grid connected or islanded condition, will improve reliability and power quality of the customers. In this case, the DG will be maximized to supply and feed the distribution network loads, even in islanded mode. Therefore, for the operation of the islanded distribution network, the frequency and voltage of the network should be kept within their optimal range. During the islanding mode voltage and frequency are very sensitive in distribution network connected with DG and the system frequency is determined by the power balance in the islanded system. This research adopt an Under Frequency Load Shedding (UFLS) scheme in response based and event based methods to improve the system stability and security by enhancing the frequency and voltage response of the system on occurrence of contingency in distribution network. Proposed method is performed based on frequency and Rate of Change of Frequency (RoCoF) for islanded distribution network. Developed UFLS scheme provide a fast decision to prevent the frequency decline in the system. Hence, after calculating the amount of load needed to be shed; this method will shed the required load in one-step to find a better response. The proposed method functionality has been investigated and an acceptable stability for the voltage and frequency of the network has been obtained.