Smart Grid Wide-Area Transmission System Visualization

The installation of vast quantities of additional new sensing and communication equipment, in conjunction with building the computing infrastructure to store and manage data gathered by this equipment, has been the fi rst step in the creation of what is generically referred to as the "smart grid" for the electric transmission system. With this enormous capital investment in equipment having been made, attention is now focused on developing methods to analyze and visualize this large data set. The most direct use of this large set of new data will be in data visualization. This paper presents a survey of some visualization techniques that have been deployed by the electric power industry for visualizing data over the past several years. These techniques include pie charts, animation, contouring, time-varying graphs, geographic-based displays, image blending, and data aggregation techniques. The paper then emphasizes a newer concept of using word-sized graphics called sparklines as an extremely eff ective method of showing large amounts of timevarying data.

High Performance of a TOA-TDOA Hybrid GSM Location System for Intelligent Transportation Systems

This paper illustrates the performance of a mobile positioning technique applicable to a GSM network.An experimental system of a network-based GSM positioning for ITS has been proposed, and the hybrid TOA-TDOA method based on GSM signaling has been analyzed and used. The performance of the proposed system is showed through simulations in urban and suburban environments. The accuracy for 67% mobile stations is 70 m in urban and 120 m in suburban. The accuracy, coverage and network load of positioning system are also analyzed.

Application of artificial intelligent systems for real power transfer allocation

The application of various artificial intelligent(AI) techniques,namely artificial neural network(ANN),adaptive neuro fuzzy interface system(ANFIS),genetic algorithm optimized least square support vector machine(GA-LSSVM) and multivariable regression(MVR) models was presented to identify the real power transfer between generators and loads.These AI techniques adopt supervised learning,which first uses modified nodal equation(MNE) method to determine real power contribution from each generator to loads.Then the results of MNE method and load flow information are utilized to estimate the power transfer using AI techniques.The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of various AI methods compared to that of the MNE method.

Gaussian Mixture Statistics Model Based on Automatic Inspection System Used in ITS

The ITS is becoming more and more important in the economic development of China. But most of the ITS used in Chinese major cities need the human to perform the supervision task. As a result, it consumes too much human resources, and also can not achieve the satisfied supervision performance. Thus, in this paper, we will propose an automatic inspection system based on the Gaussian mixture statistics model to alleviate this kind of problem. The proposed method will utilize a Gaussian Mixture model to model the background, and then use the EM algorithm to update the model＇s coefficients frame by frame to make the model adapt to the changing environment. After successful modeling, we can extract out the foreground blocks from background blocks, and finally trigger the automatic alarming system by calculating the number of foreground blocks. From the experiment results, our proposed method can achieve considerable good results.