International Journal of Smart Electrical Engineering
Volume:1 Issue: 3, Summer 2012

Distributed Generations (DGs) are utilized to supply the active and reactive power in the transmission and distribution systems. These types of power sources have many benefits such as power quality enhancement, voltage deviation reduction, power loss reduction, load shedding reduction, reliability improvement, etc. In order to reach the above benefits, the optimal placement and sizing of DG is significant. In this regard, this paper gets use of the Bacteria Foraging Algorithm (BFA) and Binary Genetic Algorithm (BGA) to investigate the DG placement with the purpose of power loss and voltage deviation reduction. The proposed method is applied on the 33-bus and 69-bus IEEE test systems and the optimal place and size of DGs from the power losses and voltage deviation minimization are assessed. Also, the performance of the above two algorithms are compared with each other.

In today’s restructured environment, congestion management plays an essential role in power system operation. Different methods are presented and discussed in this respect for congestion management in short-term and long-term intervals. It is attempted in the present paper to investigate the impact mechanism of FACTS devices and demand response programs together with generation re-dispatch as some facilities from transmission, consumption and generation sides on short-term congestion management of electricity market. For this purpose, Thyristor controlled Series Capacitor (TCSC) representing series FACTS devices and Direct Load Control (DLC) program representing demand response programs in day-ahead power pool market are mathematically modeled and results will be numerically studied and analyzed on the 14-bus IEEE test system.

This paper presents a fault location technique for transmission lines with minimum current measurement. This algorithm investigates proper current ratios for fault location problem based on thevenin theory in faulty power networks and calculation of short circuit currents in each branch. These current ratios are extracted regarding lowest sensitivity on thevenin impedance variations of the network structure. Proposed algorithm compares current ratios from offline calculations with corresponding values achieved from measurements with a look-up table system. Best solution based on Dynamic Time Warping (DTW) algorithm is introduced as an output (location of the fault) which includes the line and the distance. Among many current ratios to form look-up table system, the minimum number of them will be extracted by a multi-objective optimization technique using Bees Algorithm (BA). This extraction is based on lowest possible number of buses for instruments installation and required current measurements, estimation accuracy and sensitivity degree from thevenin impedances changes. Accuracy of proposed algorithm is evaluated in a widely used multi-machine network of Western Systems Coordinating Council (WSCC).

With the development of deregulated power systems and increase of prices in some hours of day and increase fuel price, demand response programs were noticed more by customers. demand response consists of a series of activities that governments or utilities design to change the amount or time of electric energy consumption, to achieve better social welfare or some times for maximizing the benefits of utilities or consumers. In this paper we try to evaluate the effect of DR programs especially EDRP on Nodal Marginal Pricing spikes reduction of Restructured Power Systems while occurs events. In order to reach to this target, EDRP program (Emergency Demand Response Program), as common demand response program, is considered. Effects of EDRP program on Nodal Marginal Pricing spikes and operation cost reduction of Restructured Power Systems are investigated using EDRP and economic load model, AC-OPF Formulation and nodal marginal price evaluation techniques. The IEEE 9 bus Test System is used to implement comparisons of impacts with and without EDRP activity on nodal marginal pricing spikes and operation cost reduction. According to obtained results, EDRP using lead to volatility decrease in local marginal price (LMP). It can be said that solving problems such as congestion in transmission lines, power system reliability decrease and volatility decrease in local marginal price at load network peak hours, is impossible without customer interfering in power market. In other hand Consumer participation, makes the power markets more competition and enhance its performance.

Traffic prediction systems can play an essential role in intelligent transportation systems (ITS). Prediction and patterns comprehensibility of traffic characteristic parameters such as average speed, flow, and travel time could be beneficiary both in advanced traveler information systems (ATIS) and in ITS traffic control systems. However, due to their complex nonlinear patterns, these systems are burdensome. In this paper, we have applied some supervised data mining techniques (i.e. Classification Tree, Random Forest, Naïve Bayesian and CN2) to predict the next state of Traffic by a categorical traffic variable (level of service (LOS)) in different short-time intervals and also produce simple and easy handling if-then rules to reveal road facility characteristic. The analytical results show prediction accuracy of 80% on average by using methods

A sensor network is made up of a large number of sensors with limited energy. Sensors collect environmental data then send them to the sink. Energy efficiency and thereby increasing the lifetime of sensor networks is important. Direct transfer of the data from each node to the central station will increase energy consumption. Previous research has shown that the organization of nodes in clusters and selection the appropriate cluster head increases the network lifetime. In this study, clustering, determine to cluster heads and the sink movement on the predefined paths has been done with fuzzy method. There are two inputs for the fuzzy model; residual energy of the node and distance from the sink. The output is priority of cluster heads. Sink moves base on the highest priorities on the predefined paths. Then by using genetic algorithm, the number of clusters, shape type and area is optimized. Fitness function is based on network lifetime.

Since most common form of cervical cancer starts with pre-cancerous changes, a flawless detection of these changes becomes an important issue to prevent and treat the cervix cancer. There are 2 ways to stop this disease from developing. One way is to find and treat pre-cancers before they become true cancers, and the other is to prevent the pre-cancers in the first place. The presented approach uses precancerous images which are taken from a digital colposcope, and a set of texture and color features is extracted which includes low and high grade SIL (Squamous Interepithelial Lesion ) .After extracting, features are fed to a classifier, which could be KNN,RBF,MLP and Neuro-Fuzzy network and after training effective features are selected using UTA algorithm for each classifier individually. Finally, results come in a comparison table, show that the landa fourteenth, theta-x and together with Neuro-fuzzy classifier have the best overall performance. This approach has an acceptable and simple early diagnosis of cervix cancer and may have found clinical application

In this paper, by means of fuzzy approaches, an accurate method is introduced for edging of color photographs. The difference between our method with other similar methods is the use of a morphological operation to think or thick the obtained edges. In this proposed method, a 3×3 window is dragged on the photo. For each block, 12 point sets will be defined, each including two non-overlapping point sets. Then, a fuzzy membership function will be designed for each point sets according to data of contrast. At last, the range of membership contrast degree for the points of second point sets will be assessed. A comparison of membership degree of second point sets with a pre-defined threshold indicates whether central point of window is bordered or non-bordered. The method was performed on some reference images and the results were compared with common edging methods. The results show that proposed method has a high capability to edge photographs