Pawel Sowa

Impact of static electric field on prooxidant‐antioxidant balance in rats

Purpose – The purpose of this paper is to estimate the influence of long‐term, whole‐body exposure of rats to strong, static electric field with physical parameters generated nearby high voltage direct current (HVDC) transmission lines on the intensity of reactive oxygen species generation analyzed indirectly, basing on the measurement of malone dialdehyde level, as well as on the activity of enzymatic antioxidant defence system.Design/methodology/approach – In rats exposed to static electric field with intensity of 16, 25 and 35 kV/m, respectively, or sham‐exposed eight hours daily for 56 days, in the obtained plasma, erythrocytes lysates and liver homogenates the activity of some antioxidant enzymes as well as the concentration of malone dialdehyde were determined with use of spectrophotometric and kinetic methods.Findings – It was observed that long‐term exposure of rats to static electric field causes only temporary compensatory changes in the concentration of malone dialdehyde and transient changes i...

Neural networks on transformer fault detection evaluating the relevance of the input space parameters

Following a number of studies that have employed different forms of neural network models to perform dissolved gas-in-oil analysis (DGA) of transformer bushings, this manuscript focuses on evaluating the relevance of the parameters that form part of the model input space. Using a multilayer neural network initially populated with all the 10 input parameters (10V-Model), a matrix containing causal information about the possible relevance of each input parameter is obtained. The information from this matrix is proven to be valid through the construction and testing of another two, separate, multilayer networks. One networks input space is populated with the 5 most relevant parameters (MRV-Model), while the other is populated with the 5 least relevant parameters (LRV-Model). The obtained classification accuracy values are as follows: 100% for the 10V-Model, 98.5% for the MRV-Model, and 53.0% for the LRV-Model.

Serum levels of selected adipocytokines in benign and malignant parotid gland tumor patients

Objectives The aim of this study was to evaluate serum levels of adiponectin, leptin, visfatin and IL‐6 in patients with pleomorphic adenoma, Warthin’s tumor and acinic cell carcinoma of the parotid gland. Materials and methods Venous blood samples were collected from 30 patients with pleomorphic adenoma, 21 patients with Warthin’s tumor and 8 patients with acinic cell carcinoma. Serum adiponectin, leptin, visfatin, IL‐6 and CRP concentrations were determined. Results Our results revealed significantly lower adiponectin serum levels in patients with malignant tumors compared to benign tumor individuals. Moreover, in benign cases the level was significantly higher compared to controls. Furthermore, serum leptin concentrations of benign tumor patients were higher compared to controls. Those differences, however, were observed only in males. The serum visfatin level was elevated in all tumor subjects compared to healthy individuals, whereas the serum IL‐6 concentration was similar. Conclusions We anticipate that adiponectin may play a potential protective role in salivary gland tumors. Also leptin and visfatin seem to play an important role in salivary gland tumor pathology, although in males and females leptin may act or be regulated in a different manner. The influence of visfatin on salivary gland tumors is probably independent of IL‐6 production.

Changes in Serum Ceruloplasmin Levels Based on Immunomodulatory Treatments and Melatonin Supplementation in Multiple Sclerosis Patients

Background The cause of multiple sclerosis (MS) is currently unknown, but it is thought that oxidative damage and iron metabolism mechanisms are involved. The aim of this study was to examine ceruloplasmin concentration in MS patients based on various immunomodifying therapies and to test the effect of antioxidative melatonin on ceruloplasmin levels. Material/Methods This prospective study included 102 MS patients and 15 healthy controls. Patients were divided into groups according to different immunomodifying therapies: interferons beta 1a, interferons beta 1b, glatiramer acetate, mitoxantrone, and immunomodifying pre-treatment (A, B, G, Mx, and P groups, respectively), and the relapse R group. MS patients were supplemented with melatonin for 3 months. Serum ceruloplasmin concentrations, EDSS, brain MRI, serum C-reactive protein level, and white blood cell count were examined. Results The results indicated significantly increased levels of ceruloplasmin in MS patients. No differences in ceruloplasmin concentrations between the relapse group and controls were observed. In A and G groups, ceruloplasmin levels before and after melatonin were similar to levels in controls. In group B, ceruloplasmin concentration was significantly higher vs. control and relapse groups. After melatonin administration in group B, ceruloplasmin levels decreased. Ceruloplasmin concentrations in the Mx group were significantly higher compared to controls. Conclusions We found for the first time that ceruloplasmin concentration in MS patients varies depending on different immunomodulatory treatment and decrease after 3 months of melatonin administration. Ceruloplasmin could be a valuable serum marker for the chronic demyelinating process participating in oxidative stress mechanisms, as well as a neurodegenerative marker, but not a marker of acute-phase MS.

Components reliability parameters by mid-term deficit of electric energy

Reliability plays important role in rational management of transmission network. It concerns both the current activity of energy enterprise and forecasting of development of network, which cooperates with different kind of power stations and different customers. The required level of reliability results from agreements with customers. Mid-term deficit of power and electric energy occur mainly in winter and summer period. Usually maximum demand takes a stand in winter period and lowest temperatures in year, however in summer request for power and energy is definitely lower but potential of base of power station falls simultaneously. In this period numerous planned disconnections of lines and transformers occur. In addition maximum temperatures as well as numerous storms also and hurricanes are observed. In remaining periods i.e. in autumn or spring the probability of power or energy deficit is small, although can occur because of emergency reasons. The reasons of mid-term deficits can be located in the sector of energetic or outside it. Collected data from period 2005–2008 show on the reality of threat for whole energy system and it smallest part. In the paper the reasons of deficits of energy are analyzed. The reliability parameters of basic network components: transmission lines, transformers and bus systems; which are given from sufficient statistics of disconnections; are presented. Received indices shows the level of reliability and gives information about future period of utilization of elements. The methods of liquidation and moderation of deficit - especially in regional network in the area of commune are presented.

Adaptive decision-taking of protection systems in networks with dispersed power generating sources

Incorporating renewable energy sources into the power system is connected with a number of new challenges, i.e. for the power system protections. Thus, several problems have been identified in addition to the factors which occur in such systems without the connected i.e. wind farms. Taking the presence of wind farms into account, the selectivity and the speed of decisions of distance protection will probably be very limited. One of the possible solutions will be creating protection systems which use data from the selected area of the power system network to increase the correctness of decision-taking by adapting settings of protection functions to the changing conditions. This paper will discuss the proposal of such a solution as well its simulation results.

A neural network approach to adaptive protective systems problem in the complex power generating units

Practical successes have been achieved with neural network models in a variety of domains, including energy‐related industry. The large, complex design space of electrical power systems (EPS) is only minimally explored in current practice. The satisfactory results that nevertheless have been obtained testify that neural networks are a robust modeling technology; at the same time, however, the lack of a systematic design approach implies that the best neural network models generally remain undiscovered for most applications. This paper presents an approach to an adaptive protective systems problem in the complex power generating units. First, we demonstrate the complex interdependencies between various parameters of EPS protection systems. We then present an approach, based on protection and adaptation criteria, for designing a neural network based adaptive protection system. © 2000 John Wiley & Sons, Inc.

A New Simple Method for Assessing Security of Low-Voltage Power Networks Development Variants

This paper presents a new and simple expert method for assessment of potential development variants of LV power networks. The network security, dispatching personnel and power consumers were taken into consideration. The uniqueness of the method is its ease of use. Each variant was evaluated using 20 indicators. These indicators are defined clearly and concern the narrow-themed aspects of security of the power network operation. Analyses performed with the use of the authors’ method may also include the presence of generating units. Streszczenie. W artykule przedstawiono nową, prostą metodę eksperckiej oceny potencjalnych wariantów rozwoju sieci niskiego napięcia z punktu widzenia bezpieczeństwa pracy sieci, służb ruchowych i odbiorców. Cechą szczególną opracowanej metody jest łatwość jej stosowania. Każdy wariant sieci jest oceniany przy użyciu ponad 20 wskaźników. Wskaźniki te są jednoznacznie zdefiniowane i dotyczą wąskotematycznych aspektów bezpieczeństwa pracy sieci. Analizy prowadzone z wykorzystaniem tej metody mogą również uwzględniać obecność źródeł wytwórczych. (Nowa, prosta metoda oceny bezpieczeństwa wariantów rozwoju sieci niskiego napięcia).

Expert evaluation method of the SAIDI normative reliability index

The paper presents a new method developed to estimate the level of standard of reliability index SAIDI expected in the future for new power network conditions determined for making changes to the network configuration (including changes in the functionality of the components of the network). This involved defining a set of split times that make up the long and very long unplanned outage electrical energy consumers. The usefulness of this method is shown in assessing the impact of several variants of automation low-voltage power network (of varying scope to implement new functionality determined by adopted set of installed equipment, and a set of potentially performed tasks) on the level SAIDI. The developed method can be successfully used as a criterion for the decision making process of shaping the future power grid systems.

Prediction of Power System Post-Contingency Vulnerability Status by Mining Synchronized Phasor Measurements

Abstract Real-time vulnerability assessment (VA) is one of the essential tasks of the so called Smart Grid, since it has the function of detecting the necessity of performing global control actions. In view of this, the present paper will introduce a novel data-mining-based approach to map post-contingency Dynamic Vulnerability Regions (DVRs), taking into account three short-term instability phenomena. Based on probabilistic models of relevant inputs (e.g. nodal loads and occurrence of contingencies), the approach applies Monte Carlo (MC) simulation to recreate a wide variety of possible post-contingency dynamic data of some electric variables, which could be directly available from PMUs in a real system (e.g. voltage phasors or frequencies). From this information, a pattern decomposition method, based on empirical orthogonal functions (EOF), is used to approximately pinpoint the DVR spatial locations. The identified DVRs are then used to ascertain the actual dynamic state relative position with respect to their boundaries, which is accomplished by using a support vector classifier (SVC). The proposal is tested on the IEEE New England 39-bus test system. Results show the feasibility of the approach in finding hidden patterns in dynamic electric signals as well as in numerically mapping power system DVRs.