Serap Karagol

Generation of Equivalent-Circuit Models From Simulation Data of a Thermal System

In this paper, we develop a methodology to obtain medium-order electrical equivalent circuits (ECs) of the thermal behavior of electronic systems. The method combines several elements: 1) the use of detailed finite-element (FE) simulations of steady-state thermal behavior; 2) graph partitioning of FE meshes to decompose the geometry at intermediate levels of detail; and 3) physically guided estimation of the parameters of the EC. To obtain richer training datasets, we also develop a method to include fictitious heat sources inside the FE model. This approach yields modular medium-order models for extensive and complicated geometries, such as a power-electronic chip. Moreover, representing the thermal behavior with an EC enables coupled simulations of electrothermal behavior, which are important in power electronics. We test our algorithms on a multimaterial pole of a dc motor and electronic chip. Excellent agreement in modeling both steady-state and transient behaviors was obtained.

Novel Smart Grid and SCADA system interdependency networks for future's clean, sustainable and green energy

A novel approach of interdependency modeling of Smart Grid and Supervisory Control and Data Acquisition (SCADA) networks is introduced. Methodological approach for vulnerability reduction considering both structural and functional vulnerability is introduced in this paper. The analysis of cyber-attacks on Smart Grid and SCADA network is discussed. Paper discusses importance and need of clean, sustainable and green energy for the future. Paper also analyzes interdependent Smart Grid and SCADA network under severe emergency situations. The contribution of this paper provides novel network with integrated infrastructures for active and survivable network operation. Thus novel Smart Grid and SCADA interdependency network will act as futures clean, sustainable and Green energy model.

Power differential method based islanding detection in PV systems

Safety operation/measures are of great concern and among them islanding phenomena takes an important role for reliable energy. Therefore, the utility grid requires anti-islanding protection for a safe and reliable operation. For this purpose, a different and fast method is proposed for islanding detection in PV systems. The suggested method is based on instantaneous power calculation at the point of common coupling and able to detect islanding condition within a few sampling interval. No further calculation is needed to detect islanding problem for grid connected PV systems.

A novel transformer protection method based on Hilbert Huang Transform and artificial neural network

This paper presents the application of Hilbert-Huang Transform (HHT) and artificial neural network (ANN) for fault detection on transformers. The combined procedure, Emprical mode decomposition (EMD) and Hilbert transform, is called the Hilbert-Huang Transform (HHT). The ANN is designed and trained using feed forward propagation algorithm. The input features of the ANN are extracted from the frequency and aplitude of IMFs by applying the Hilbert transform. Simulation results of the proposed method for fault detection on tranformers proveto be effective.

GreenCloud simulation QoSbox in cloud computing

Cloud computing was introduced as a new technology when local resources could not any more fullfil access requirements along with the increase of network bandwidth and variety of services breaks constraints of physical placement and deliver diversities of services in its virtualized hardware and software type. GreenCloud simulator as an extension of the Network Simulator (NS-2) cloud computing simulators, execute an energy-aware cloud computing scenario with data center virtualized components (switches, routers, links, etc.). This paper converses a cloud architecture that delivers virtualized network as per demand from cloud user, with the explanation of QoSbox-based GreenCloud simulation that to demonstrate the performance and behavior of the nework performance in cloud computing environment.

A Novel Self Localization Approach for Sensors

This paper presents a modification of 3N Time of Arrival (TOA) and a reliable Time Difference of Arrival (TDOA) based localization algorithms. TDOA is formulated using the parametric equations of the hyperbolas whose intersections are candidate locations for the nodes to be localized. The TDOA algorithm is guaranteed to find all possible relevant solutions, even when implemented on a computational node with limited capability. Monte- Carlo simulations were used to assess the performance for both algorithms.

Maximum overlap discrete wavelet based transformer differential protection

In this paper, a wavelet based power transformer protection algorithm, which is one of the most important components of power system, is proposed. Traditionally, power transformers (rated power greater than 1.5MVA) are protected by differential protection scheme. Its function supported by discrete Fourier transform is fundamentally based on comparison of primary and secondary currents of the transformer and dedicated to discriminate internal faults and magnetizing inrush phenomena. In this way, the relay (differential protection relay) is ensured to be more reliable and selective. Nevertheless, the concept of transformer protection has been keeping up-to-date and several numerical protection algorithms have been suggested for this purpose. In this work, maximal overlap discrete wavelet transform (MODWT) based transformer differential protection technique is proposed. The features vectors obtained by MODWT are then processed by artificial neural network (ANN) to classify the normal, magnetizing, and internal fault conditions. The obtained results are also compared to traditional discrete wavelet transform (DWT) and interpreted using performance curves.

Transmission of audio signal from linear block coded AWGN channel using different modulation techniques and wavelet transform families

Mobile communication has become an important part of our daily lives for voice communication and data sharing and access over the Internet. Mobile communication is an open network, so maintaining the privacy and reliability of data has always been anxiety. The reliability of the data against channel noise can be achieved by various error correction codes. The purpose of the channel coding process is to reduce the effect of some disruptive elements that the information is influenced in the transmission phase as much as possible, that is to ensure that the data is delivered to the receiver with minimum error. In the first1 part of this work, Linear Block Coding Method is used to transmit the audio data recorded in .wav format for 5 seconds in MATLAB environment with minimum error. Four different types of modulation were used as the modulation method and the best performance was obtained by using Binary Phase Shift Keying (BPSK). The Bit Error Rate (BER) performance curve was drawn and the difference between the original and the received signal was observed. According to the BER performance curve, as the signal to noise ratio increases, less false data is received at the receiver. In the second part of the study, four wavelet transforms at different levels were applied to the audio signal, and the performances of these families were compared.

A hyperbolic location algorithm for various distributions of a Wireless Sensor Network

Intersection of hyperbolic curves defined by the Time Difference of Arrival (TDOA) is often used in Wireless Sensor Networks (WSNs) to estimate the location of sensors. This paper proposes a new algorithm of this type. The hyperbolic parametric equation and the rotation matrix are used to estimate the location of the target node and rotation, translation and intersection operations are applied. MATLAB simulations on Uniform, Beta, Weibull and Gamma distributed networks showed the optimum combinations of distribution, constant range and anchor percentage.

Assessment of short/long term electric field strength measurements for a pilot district

The level of electromagnetic radiation (EMR) exposure increases day by day as natural consequences of technological developments. In recent years, the increasing use of cellular systems has made it necessary to measure and evaluate EMR originating from base stations. In this study, broadband and band selective electric field strength (E) measurements were taken at four different times in order to evaluate the change of short term E in Atakum district of Samsun, Turkey. The measurements were collected from 46 different locations using PMM 8053 and SRM 3006 EMR meter in band from 100 kHz to 3 GHz, and the maximum E (Emax) and the average E (Eavg) were recorded. The highest values have been noticed in these measurement 9.45 V/m and 17.53 V/m for Eavg and Emax respectively. Apart from these measurements, 24 hour long term E measurements were taken at a location where the highest value was observed and analyzed to observe the change of Es during a day. At the end of the study an empirical model that helps calculating the total E of medium with 95% was proposed.