Venizelos Efthymiou

Evaluation of Partial Discharge Denoising using the Wavelet Packets Transform as a Preprocessing Step for Classification

The identification of partial discharges in high voltage equipment has emerged as one of the most effective condition monitoring methods for assessing the integrity of the equipment under test. The fact that the application of PD monitoring methods is being applied online makes the measurements suffer from noise, inevitable at the measurement point, and reduces the sensitivity of the measurements. Signal processing methods to post process the measurements have been utilised, resulting not only in rejection of the noise and improvement of the sensitivity, but also in improved classification of the PD. A powerful noise rejection technique, the wavelet packets transform (WPT) has been extensively employed for the effective extraction of PD signals from noise. This technique is particularly useful in denoising signals which have transient characteristics. It expands the signal into different bases that are chosen adaptively according to a cost function, transforming the signal into a set of wavelet coefficients. The choice of a cost function has a significant effect on the compact representation of the signal. In this paper after the theory of wavelet packets is first briefly presented, and the denoising performance of the various wavelet packets parameters, such as the wavelet function, the thresholding type, and the cost function to be used is studied through the use of data acquired in a laboratory experimental environment for four types of discharges; namely the corona discharge in air, the internal discharge in oil, the floating discharge in oil and the surface discharge in air. The Symmlet wavelet has been compared with the Daubechies wavelet, both with 8 vanishing moments, the hard thresholding rule has been compared with the soft thresholding rule, and three cost functions have been compared as to their suitability for best basis expansion. Using some predefined criteria to assess their denoising performance the Symmlet 8 has been found to outperform the Daubechies 8 wavelet, the hard thresholding rule to yield better performance than the soft thresholding rule and the Shannon entropy cost function to perform better that the log energy and the norm energy cost functions.

Classification of Partial Discharge Signals using Probabilistic Neural Network

Partial Discharge (PD) classification in power cables and high voltage equipment is essential in evaluating the severity of the damage in the insulation. In this paper, the Probabilistic Neural Network (PNN) method is used to classify the PDs. After the algorithm has been trained it uses the input vector, which contains the features that would be used for classification, to calculate the probability density function (pdf) of each class and together with the assignment of a cost for a misclassification the decision that minimizes the expected risk is taken. The maximum likelihood training is employed here. The success of this particular method for classification is asserted. This method has the advantage over Multilayer Neural Network that it gives rapid training speed, guaranteed convergence to a Bayes classifier if enough training examples are provided (i.e. it approaches Bayes optimality), incremental training which is fast (i.e. additionally provided training examples can be incorporated without difficulties) and robustness to noisy examples. The results obtained here (99.3%, 84.3% and 85.5% for the corona, the floating in oil and the internal discharges respectively) are very encouraging for the use of PNN in PD classification.

Thevenin equivalent circuit for the study of high photovoltaic penetration in distribution grids

The electricity grid is unidirectional operating in a passive way and consequently it is not yet ready to accept high penetration of renewable energy sources (RES). Further research is required to assess the impact of distributed Photovoltaic (PV) generation on power quality and establish the necessary measures for the restructuring of the electricity grid to ensure its optimum operation. In this paper, appropriate models are developed in order to assess the effects of PV generation. Thevenins theorem is used to develop the equivalent circuit representing the exact distribution grid behaviour. The Thevenin equivalent circuit in combination with a verified PV system model are employed to study the power quality response of the distribution grid in the presence of PV via simulation and the results are compared to actual measurements yielding good agreement.

Effective dynamic tariffs for price-based Demand Side Management with grid-connected PV systems

In isolated electricity networks the penetration of renewable energy sources offers, among others, the advantage of distributed electricity. At the same time, as penetration levels increase, controls and regulations need to be imposed in order to alleviate rising grid integration issues. Some of these can be prevented through the use of dynamic tariffs enabling Demand Side Management. In this work, a new tool for the optimization of dynamic tariffs is developed. This is based on statistical analysis of the consumption profiles and optimization procedures, aiming to derive the most appropriate Time-of-Use (ToU) tariffs. The consumption profile analysis performed on three hundred prosumers in Cyprus showed strong correlation between the measured and the average consumption profiles while the self-consumption rate of existing prosumers is averaged to 30%. The developed dynamic ToU blocks in comparison with the load curve exhibit a mean absolute percentage error and root mean square error of 6.22% and 12.32%, respectively.

Forecasting and Observability: Critical Technologies for System Operations with High PV Penetration

Pierre-Jean Alet (CSEM, PV-center, Pierre-Jean.ALET@csem.ch), Venizelos Efthymiou (University of Cyprus, FOSS Research Centre for Sustainable Energy, efthymiou.venizelos@ucy.ac.cy), Giorgio Graditi (ENEA Portici Research Centre, giorgio.graditi@enea.it). Norbert Henze (Fraunhofer Institute for Wind Energy and Energy System Technology, norbert.henze@iwes.fraunhofer.de), Mari Juel (SINTEF Materials and Chemistry, Sustainable Energy Technology, Mari.Juel@sintef.no), David Moser (EURAC Research, Institute for renewable energy, david.moser@eurac.edu), Franko Nemac (ApE Agencija za prestrukturiranje energetike, franko.nemac@ape.si), Marco Pierro (EURAC Research, Institute for renewable energy, Marco.Pierro@eurac.edu), Evangelos Rikos (Center for Renewable Energy Resources and Saving CRES, vrikos@cres.gr), Stathis Tselepis (Center for Renewable Energy Resources and Saving CRES, stselep@cres.gr), Guangya Yang (Technical University of Denmark, Department of Electrical Engineering, gyy@elektro.dtu.dk)

The impact of simulation studies on the distribution grid operation and planning in Cyprus

Simulation tools offer a wide range of prospective advantages that give utilities and system operators the ability to improve power quality and operational costs. The use of such tools can make the analysis/study of complex power networks simpler, giving valuable answers about the power quality behaviour of electricity networks in the presence of intermittent renewable energy generation and can help in reducing undesirable energy losses. In this work, steady-state simulations are performed by undertaking measurement investigations and model development in order to assess the impact of such studies on system planning and operation. By using DigSILENT PowerFactory, typical feeders of Nicosia district, Cyprus are realized into circuit form and simulated while considering demand and renewable energy production time series measurement data. The aim of the paper is to reveal the operational benefit of using design and analysis tools for proactive or corrective actions. From the simulations, it has been shown that network reconfiguration tasks lead to the reduction of power losses which can inevitably create an economic benefit for electricity utilities. In addition, simulation tools can help utilities meet challenging voltage regulation requirements/issues. One example of eliminating voltage violations through transformer tap optimization is also provided.

New voltage regulation scheme for photovoltaic systems based on Thevenin's Theorem

The distribution grid structure is expected to change in the upcoming years with the further penetration of renewable energy sources (RES). Most of the energy needs will be covered by local distributed generators (DG) responsible also for maintaining good levels of power quality and grid stability. As a consequence, measures for regulating the voltage within acceptable levels will be required as well as storage to allow proper utilization of produced energy and to ensure that the distribution grid operates in an uninterruptable and healthy way. In this work, a new voltage regulation scheme inspired by Thevenins Theorem is developed and presented. The well-known dynamic power factor method is modified accordingly to provide a variable lower limit, which is defined by the Thevenin equivalent impedance (TEI) measured at the point of common coupling with the electricity grid. The new voltage regulation scheme is incorporated into the control circuit of a verified Photovoltaic (PV) system model for its further evaluation via computer simulations.