Estudo e analise dos sistemas de proteção em subestações automatizadas de energia elétrica

Electrical energy is present in the lives of all people and is extremely important that it be delivered to end users with plenty of quality, safety and low costs. The electric power substations are responsible for transmission and distribution of electricity generating sources to consumers, and with technological advances and the subsequent automation of same, the electricity began to be delivered with greater continuity and reliability. Protection systems in substations are largely responsible for making the electricity reaches the final consumer with quality, since their function is to prevent the spread of any type of failure occurred at any point of transmission to the load centers. These systems consist primarily by the current transformers and potential, by the protective relays and circuit breakers and switchgear. The processors send the necessary data to the relays and, if those detect any abnormality in the system, operate the opening command of the branch circuit breakers to isolate where the fault. Therefore, it is essential to better understand the operation of such equipment, as well as the overall system. This work aims to study the main substation equipment, current transformers and potential and, especially, protection relays, in order to obtain the advantages that automated systems can provide

Estudo comparativo entre subestações ao tempo e subestações isoladas a gás

In this paper are compared two methods of deploying electrical substations, conventional type, when installed at open areas (Air Insulated Switchgear - AIS), and compact gas-insulated (Gas Insulated Switchgear - GIS) when installed inside buildings. With the expansion of urban centers, areas available for deployment of conventional substations become increasingly difficult to find in these locations. Also due to speculation in urban areas, it becomes feasible to install Gas Insulated Switchgear. This paper presents and evaluates criteria with advantages and disadvantages for application of the two methodologies, aiming to assist in decisionmaking moment of choice in deployment of Electric Power Substations in two scenarios. It is expected that at the end of this work, the criteria evaluated assist in this decision making

Using artificial intelligence for the control of medium voltage substations

This paper introduces a method for the supervision and control of devices in electric substations using fuzzy logic and artificial neural networks. An automatic knowledge acquisition process is included which allows the on-line processing of operator actions and the extraction of control rules to replace gradually the human operator. Some experimental results obtained by the application of the implemented software in a simulated environment with random signal generators are presented.

A neural approach to evaluate the effect of lightning in power transformers

This paper proposes the application of computational intelligence techniques to assist complex problems concerning lightning in transformers. In order to estimate the currents related to lightning in a transformer, a neural tool is presented. ATP has generated the training vectors. The input variables used in Artificial Neural Networks (ANN) were the wave front time, the wave tail time, the voltage variation rate and the output variable is the maximum current in the secondary of the transformer. These parameters can define the behavior and severity of lightning. Based on these concepts and from the results obtained, it can be verified that the overvoltages at the secondary of transformer are also affected by the discharge waveform in a similar way to the primary side. By using the tool developed, the high voltage process in the distribution transformers can be mapped and estimated with more precision aiding the transformer project process, minimizing empirics and evaluation errors, and contributing to minimize the failure rate of transformers. © 2009 The Berkeley Electronic Press. All rights reserved.

Fault section estimation in automated distribution substations

In this paper, a methodology based on Unconstrained Binary Programming (UBP) model and Genetic Algorithms (GAs) is proposed for estimating fault sections in automated distribution substations. The UBP model, established by using the parsimonious set covering theory, looks for the match between the relays' protective alarms informed by the SCADA system and their expected states. The GA is developed to minimize the UBP model and estimate the fault sections in a swift and reliable manner. The proposed methodology is tested by utilizing a real-life automated distribution substation. Control parameters of the GA are tuned to achieve maximum computational efficiency and reduction of processing time. Results show the potential and efficiency of the methodology for estimating fault section in real-time at Distribution Control Centers. ©2009 IEEE.

Optimal switch allocation for automatic load transfer in distribution substations

This work proposes a methodology for optimized allocation of switches for automatic load transfer in distribution systems in order to improve the reliability indexes by restoring such systems which present voltage classes of 23 to 35 kV and radial topology. The automatic switches must be allocated on the system in order to transfer load remotely among the sources at the substations. The problem of switch allocation is formulated as nonlinear constrained mixed integer programming model subject to a set of economical and physical constraints. A dedicated Tabu Search (TS) algorithm is proposed to solve this model. The proposed methodology is tested for a large real-life distribution system. © 2011 IEEE.