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"This handbook offers the whole knowledge of high voltage substations from their design and construction to the maintenance and the ongoing management, the entire asset life-cycle. The content of the book covers a range of substation topologies: Air-Insulated, Gas-Insulated and Mixed Technology Switchgear Substations together with the essential secondary systems. Additionally specialized substations such as ultra high voltage (UHV), offshore substations for wind power plants and the use of gas insulated lines are included.The book includes topics, providing information for increased reliability and availability, asset management, environmental management aspects, and the adoption of appropriate technological advances in equipment and systems in substations.The book was written by more than 30 experts from around the world and assembled through the Cigré study committee on Substations. This guarantees that the book contains information that is based on the global exchange and dissemination of unbiased information for technical and non-technical audiences.Although there are other works containing references to Substations, this book is designed to provide a complete overview of the topic in one book, providing a valuable reference for anyone interested in the topic. "

"This book consists of the identification, characterization, and modeling of electromagnetic interferences in substations for the deployment of wireless sensor networks. The authors present in chapter 3 the measurement setup to record sequences of impulsive noise samples in the ISM band of interest. The setup can measure substation impulsive noise, in wide band, with enough samples per time window and enough precision to allow a statistical study of the noise. During the measurement campaign, the authors recorded around 120 noise sequences in different substations and for four ranges of equipment voltage, which are 25 kV, 230 kV, 315 kV and 735 kV. A characterization process is proposed, by which physical characteristics of partial discharge can be measured in terms of first- and second-order statistics. From the measurement campaign, the authors infer the characteristics of substation impulsive noise as a function of the substation equipment voltage, and can provide representative parameters for the four voltage ranges and for several existing impulsive noise models."

"The electric power is something that is very important and widely used in supporting human life, but the power is also very dangerous to human safety itself. Low voltage 220 V is part of the electric power distribution system. On this channel it is possible short circuit due to installation errors. Disturbances in this system becomes a possibility of being harmful to humans, because the electric current can make men swoon even death. So that people can avoid the danger that occurs, then the system installation households should be connected to the ground through a prisoner whose price is relatively low. Of the prisoners is to be investigated in the installation of existing homes in the city of Medan."

"ABSTRAKPenelitian ini merupakan pengembangan dari metode klasifikasi dengan jaringan syaraf tiruan (JST) yang telah dilaporkan dalam Iiteratur. Pengembangan yang diusulkan dalam penetilian ini adalah mengklasifkasi sinyal M-PSK termodulasi pada sisi penerima dengan mencari nilai entropi dari masing masing band output dekomposisi wavelet untuk mengidentifikasi sinyal temuodulasi yang diterima oleh penerima Serta melewatkannya pada sistem jaringan syaraf timan untuk mengelompokkan dan pengklasitikasian sinyal yang diterima tersebut dalam kelompok M-PSK dimaksud.Dari hasil pengujian sistem ini, dapat dilihat bahwa jenis modulasi yang paling mudah dikenali adalah BPSK dan yang paling sulit adalah 32-PSK. Untuk pengaruh kanal, kanal frekuensi selektif fading memberikan pengaruh yang paling besar untuk M-PSK dengan M yang semakin besar. Untuk tipe wavelet yang berbeda, tipe wavelet Haar yang memberikan tingkat pengenalan yang paling baik dibandingkan daubechies dan Biorlhogonal. Sedangkan Tingkat Keakuratan 100 % untuk M=2, 93,33% untuk M=4, 86.67% untuk M=8, 70% untuk M=16, 36,67 % untuk M=32 dan 76,67% untuk M=64.

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ABSTRACTThere is a need for a reliable method of classifying signal modulation types without prior knowledge of the signal characteristics. This paper proposes training artificial neural networks with the entropies of wavelet packets to separate binary from M-ary phase shift keyed signals and describes the experimental results of that training and testing.As the information explosion places additional demands on our communications technology, the desire to encode more information within the same bandwidth drives the development of more sophisticated modulation schemes. Each new modulation type has introduced new problems for electrical and communications engineers to solve in order to make the information placed on a signal at the transmitter understandable at the receiver.The research goal was to develop a set of features characterizing a signal, which could then be used to train an artificial neural network. The resulting network could, in tum, be used to classify M-PSK signals. The result of experiment shown that the value of recognition are 100%, 93,33%, 86,67%, 70%, 36,67%, 76,67% for M=2,4, 8, 16, Ni=32 and M=64 respectively.

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