A. Halinka

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.

Distance Protections in the Power System Lines with Connected Wind Farms

In recent years there has been an intensive effort to increase the participation of renewable sources of electricity in the fuel and energy balance of many countries. In particular, this relates to the power of wind farms (WF) attached to the power system at both the distribution network (the level of MV and 110 kV) and the HV transmission network (220 kV and 400 kV)1. The number and the level of power (from a dozen to about 100 MW) of wind farms attached to the power system are growing steadily, increasing the participation and the role of such sources in the overall energy balance. Incorporating renewable energy sources into the power system entails a number of new challenges for the power system protections in that it will have an impact on distance protections which use the impedance criteria as the basis for decision-making. The prevalence of distance protections in the distribution networks of 110 kV and transmission networks necessitates an analysis of their functioning in the new conditions. This study will be considering selected factors which influence the proper functioning of distance protections in the distribution networks with the wind farms connected to the power system.

ANN-Based Fault-Type and Location Identification System for Autonomous Preventive-Restoration Control of Complex Electrical Power System Plants

In modern electrical power systems (EPS) an increasing importance of generating nodes, such as: pump storage plants or combined power plants including gas-turbine as well as steam-turbine generators, is observed. Such objects posess composed but highly redundant structure offering a significant opertion flexibility e.g. the adjacent start-up system use in a fault case in the dedicated start-up system, or two generating sets co-operation with one step-up transformer. The essential features of these objects are: very good power regulation abilities, short start-up time and internal structure modification possibility. The above features determine the growing importance of such objects in the EPS operation control process, aiming at the optimal operation mode as well as fast and effective restoration after a system fault occurrence, which may be ensured by the adaptive protection and control system (APCS) - sufficiently reliable both in normal operating conditions and in a fault case. One of the basic functional modules included in APCS is the autonomous preventive restoration control module (APRCM), developing the object control rules and preventing it from a fault or limiting possible fault effects via fast restoration of generation and regulation abilities.

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.

Evaluation of the correctness of operation of adaptive under-impedance criterion for HV single and double-circuit overhead power line with increased capacity

The paper presents the idea of the developed adaptive algorithm of under-impedance criterion which improves the efficiency of operation of distance protection for HV overhead lines with increased capacity. The paper also presents results of the effectiveness of the developed algorithm for an HV single and double-circuit overhead line during resistive and non-resistive faults. Streszczenie. W publikacji przedstawiono ideę działania opracowanego algorytmu adaptacyjnego kryterium podimpedancyjnego poprawiającego działanie zabezpieczeń w liniach o obciążalnościach znacznie przekraczających klasycznie określaną obciążalność dopuszczalną oraz wyniki skuteczności działania algorytmu dla ochrony linii w przypadku wystąpienia zwarć w liniach jednotorowych i dwutorowych. Algorytmu adaptacyjny kryterium podimpedancyjnego poprawiającego działanie zabezpieczeń w liniach o obciążalnościach znacznie przekraczających klasycznie określaną obciążalność dopuszczalną

Przenoszenie zwarć niesymetrycznych przez przesuwniki fazowe

Phase Shifting Transformers during unsymmetrical faults may change the power grid operation conditions. These conditions may differ from the “classical” ones that are typical for the grid operating conditions without these Phase Shifting Transformers. Thus, the value distribution of phase currents on both sides of the Phase Shifting Transformers may be different. (The „Propagation” of Unsymmetrical Faults by Phase Shifting Transformers). Słowa kluczowe: przesuwniki fazowe, zwarcie niesymetryczne, zmiana rozpływu prądu zwarciowego.

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.

Neural Network-Based Adaptive Protection System

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 chapter presents an approach to an adaptive protective systems problem in complex power generating units. First, we demonstrate the complex interdependencies between various parameters of EPS protection systems. Then, we present an approach, based on protection and adaptation criteria, for designing a neural network based adaptive protection system.