Özcan Kalenderli

Determination of source voltage from audible corona noise by neural networks

In this study, a different application of the signal recognition is presented for classification of source voltage level, which leads to produce corona noise in an experimental set-up, using recorded sound data of corona (electrical discharge) and utilizing probabilistic neural network (PNN). By applying different levels of 50 Hz ac high-voltage, the corona sound data are acquired experimentally from a test set-up intentionally producing corona sound. After successfully recording the sound data, they have been used in training and test sets of the probabilistic neural network. In this context, we can indicate the main objective for our study; to develop a model to determine exact source voltage level by only analyzing the recorded corona sound data. During the application of algorithmic method, linear prediction coefficients are used. It is shown that reasonable results can be obtained by following the proposed method.

DC breakdown voltage characteristics of small air gaps with insulating barriers in non-uniform field

In this study, the influence of insulating barriers on the breakdown voltage of air in non-uniform field is experimentally and theoretically investigated. Tests were conducted in order to determine the positive and negative DC breakdown voltage of small air gaps (up to 50 mm) formed by energized rod and grounded plane electrodes with an insulating barrier between them. The dielectric behaviour of the barriers is also examined by using various disc type insulating barriers with three different materials such as rubber, colored and transparent PVC (polyvinyl chloride) with diameters of 37.5, 75 and 150 mm. In addition, the experiments are simulated with FEMM 4.0 (Finite Element Method Magnetics) analysis program by computer. A comparison was made between the test results and the computer application. As a result, the breakdown voltage varies due to the size of the barriers, the maximum flashover voltages were observed when the barriers were positioned at the nearest point to the rod electrode and the small sized barriers become effective only in very small air gaps. The test results are in accordance with the application and the breakdown voltage of the negative polarity is always higher than the positive polarity tests.

Multi-resolution wavelet analysis for chopped impulse voltage measurements and feature extraction

In this study, an application of the wavelet transform based on the multi-resolution analysis (MRA) is aimed for evaluation of amplitude and time parameters of the chopped impulse voltage. In terms of getting data set, three types of the chopped lightning impulse voltages with different chopping times are considered and MRA is applied to these data as different case studies. Hence, some characteristic properties are extracted from the impulse waveforms at some special frequency values. In this sense, frequency component of 33 MHz is found with the maximum peak value for each case before the chopping time and their appearing times for three cases are determined using the time-frequency analysis. Hence the difference between the chopping time and occurring time of the maximum peak values at 33 MHz is calculated easily. Also, some physical interpretations of the frequency component of 33 MHz are defined through the circuit parameters of the measurement system. In usual application, the MRA can be presented as a powerful technique to extract the noise effects, which come from different sources, in the high voltage measurements.

Preliminary partial discharge measurements with a computer aided partial discharge detection system

Partial discharges (PDs) can be destructive to electrical insulation as they may degrade the material in time. Consequently, studies have been made to develop efficient systems for PD measurements and monitoring. Due to the complexity of PDs as well as factors that can affect PD characteristics, the research on PD measurement is still active. In this study a set off preliminary laboratory measurements of discharges, produced in laboratory environment with various test objects, were performed to evaluate understanding of the theory related to partial discharge and the relationship to early detection of insulation deterioration. Beside these, the common problems with recent computer aided partial discharge detection systems were tried to be identified such as detect level selection, exact PD inception voltage (PDIV) and PD extinction voltage (PDEV).

Single end travelling wave fault location on transmission systems using wavelet analysis

Power system performance is affected by transient phenomena such as different faults on power cables and transmission lines. Detection/location of the faults has great importance in order to be able to clear the fault as soon as possible and provide more reliable service to power customers. When a fault location scheme is utilized for this purpose, which uses the velocity of the propagation as a parameter during analysis, changing parameters of the transmission medium introduces large errors in determination of fault locations. The reason for the introduced error is that the travelling distance is calculated by using the travelling time and the velocity of the propagation. However, in order to have accurate fault localization, the successful analysis should not use the velocity of propagation in computer based relaying. Another important thing is that single end measurement has advantages over double end measurements. In this context, a new scheme has been developed which describes the use of wavelet analysis for identification and location of line faults without using the velocity of propagation and utilizing only one end recording. Extensive simulation work has been performed in order to confirm the effectiveness of the proposed scheme based on wavelet analysis. The obtained results indicate that the proposed scheme is effective and able to locate the points of faults with reasonable accuracy. This scheme can also be further used for the travelling wave protection on power cables for the fast and accurate fault clearance.

Noise reduction on partial discharge data with wavelet analysis and appropriate thresholding

One of the major challenges of partial discharge (PD) measurements is separation of PD signals from different type of noises resulting from measurement circuit or surrounding environment. White noise is the most common noise component that couples the PD data in practice. De-noising with wavelet shrinkage method is capable of separating the noise component to some extent, but thresholding is a key factor which is directly related to distortion of PD waveform and quality of de-noising process. Although there are applications in literature for PD noise separation, selection of thresholding rule and thresholding function, which affects the evaluation of PD characteristics, is still challenging. In this paper, by using the simulative noisy PD pulses, different thresholding rules and thresholding functions with various combinations have been studied in order to achieve the best thresholding scheme by way of observing the Signal to Noise Ratio (SNR), Mean Square Error (MSE) and Magnitude Error (ME). Results show that level dependent thresholding rule together with combined thresholding function gives the best result for de-noising white noise coupled to the PD signal.

An improved particle swarm optimization method to optimal reactive power flow problems

This study proposes an improved particle swarm optimization method to find optimal power flow by using the power transmission loss as an objective function. In the literature, PSO is a well - known intelligent search method to handle the solution of optimal power flow problem. A novel scheme which is called Improved PSO (IPSO) is defined by modifying the initialization step of PSO algorithm and choosing the load bus voltages, generator active and reactive powers, line flow capacities as penalty functions in the objective function. PSO and IPSO-based optimal power flow solutions are compared with each other on IEEE 118 and 300 bus systems. According to the test results, the power loss obtained by IPSO-based solution has less power loss than PSO-based solution. This proposed method can be used to obtain faster desirable solutions and better power loss results for the optimal power flow problem in case of power loss minimization.

Grid connection and power quality optimization of wind power plants

This paper covers the integration of the wind turbines with the national grids which includes the quality of the power generated at the wind plants, the impact to the power systems and the details of connection systems. The system has been considered in detail together with PSS-E (Power System Simulation for Engineering) software program. The scope of the study consists of two parts: technical and economical. 30 MW Wind Power Plant consisting of 13 pieces of 2.3 MW asynchronous WTG of type 690 V, 50 Hz is investigated due to the grid compliance of WPP according to Turkish Grid Code for Wind Turbines (Annex 18) in technical part. Firstly, the reactive capability of the wind power plant and comparison of it with the requirements of the Grid Code is determined. Secondly, the low voltage right through (LVRT) capability of the wind park is assessed. Finally, the system frequency and voltage test shall be applied. In the economic section, by changing some of technical parameters, cost-benefit analysis of the economic impact will be made in order to get use of maximum wind potential that could be obtained.

Optimum grounding grid design by using genetic algorithms

Grounding systems are necessary for safety of people to be exposed to dangerous voltages during any fault and for equipment by keeping their proper operation. In design of grounding grids, it is important to minimize the cost of grounding grid by considering tolerable touch voltage and step voltage values defined in regulations. For this purpose it is necessary use an optimization tool in order to have an effective design. In this paper, a method for designing grounding grids by using a genetic algorithm is presented. The aim is to minimize the cost function of the grounding grid, while the design parameters are kept according to limits defined by IEEE-Std-80. For the design of the grounding system, which comprises of 100 m × 100 m square grounding grid and ensures tolerable touch and step voltages at reasonable costs, Genetic Algorithm (GA) has been utilized. This design has been made with uniform soil model, and grid parameters which are effective at touch and step voltages have been determined via GA method. Furthermore, burying depths and rod lengths have been compared in order to keep the costs at minimum level. During the studies Matlab has been used for the genetic algorithm application. Different parameters have been studied in order to see the effectiveness of the proposed method and designed grid has been compared with real grounding grids, validating the proposed solution.

Insulator contour optimization using intelligent systems & soft computational methods

The purpose of this study is to give basic concepts of insulator contour optimization by using intelligent systems and soft computational methods. In this sense, artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are used as an optimization method. First training and validation data were collected from electric field distribution of an insulator by using finite element method analysis. Data contains coordinates and electrical field values of the middle point and the top point of the insulator. Then the data sets were used as inputs for ANN and ANFIS to train the algorithms. After the training process, any desired output that the top radius of the insulator was calculated for given input data using both methods. Finally results were compared from each other. The methods successfully are used for insulator contour optimization.