Danilo Hernane Spatti

Real-Time Voltage Regulation in Power Distribution System Using Fuzzy Control

Two different fuzzy approaches to voltage control in electric power distribution systems are introduced in this paper. The real-time controller in each case would act on power transformers equipped with under-load tap changers. Learning systems are employed to turn the voltage-control relays into adaptive devices. The scope of this study has been limited to the power distribution substation, and the voltage measurements and control actions are carried out on the secondary bus. The capacity of fuzzy systems to handle approximate data, together with their unique ability to interpret qualitative information, make it possible to design voltage-control strategies that satisfy the requirements of the Brazilian regulatory bodies and the real concerns of the electric power distribution companies. Fuzzy control systems based on these two strategies have been implemented and the test results were highly satisfactory.

Fuzzy Control System for Voltage Regulation In Power Transformers

A fuzzy control strategy for voltage regulation in electric power distribution systems is introduced in this article. This real-time controller would act on power transformers equipped with under-load tap changers. The fuzzy system was employed to turn the voltage-control relays into adaptive devices. The scope of the present study has been limited to the power distribution substation, and both the voltage measurements and control actions are carried out on the secondary bus. The capacity of fuzzy systems to handle approximate data, together with their unique ability to interpret qualitative information, make it possible to design voltage control strategies that satisfy both the requirements of the Brazilian regulatory bodies and the real concerns of the electric power distribution companies. A prototype based on the fuzzy control strategy proposed in this paper has also been implemented for validation purposes and its experimental results were highly satisfactory.

Artificial Neural Network Architectures and Training Processes

The architecture of an artificial neural network defines how its several neurons are arranged, or placed, in relation to each other. These arrangements are structured essentially by directing the synaptic connections of the neurons.

Multilayer Perceptron Networks

Multilayer Perceptron (MLP) network features, at least, one intermediate (hidden) neural layer, which is placed between the input layer and the respective output layer.

Intelligent Systems for the Detection of Internal Faults in Power Transmission Transformers

This chapter presents an approach based on expert systems, which is intended to identify and to locate internal faults in power transformers, as well as to provide an accurate diag‐ nosis (predictive, preventive and corrective), so that proper maintenance can be per‐ formed. In fact, the main difficulty in using conventional methods, based on analysis of acoustic emissions or dissolved gases, lies in how to relate the measured variables when there is an internal fault in a transformer. This kind of situation makes it difficult to de‐ sign optimized systems, because it prevents the efficient location and identification of pos‐ sible defects with sufficient rapidity. In addition, there are many cases where the equipment must be turned off for such tests to be carried out. Thus, this chapter proposes an architec‐ ture for an intelligent expert system for efficient fault detection in power transformers us‐ ing different diagnosis tools, based on techniques of artificial neural networks and fuzzy inference systems. Based on acoustic emission signals and the concentration of gases present in insulating mineral oil and electrical measurements, intelligent expert systems are able to provide, as a final result, the identification, characterization and location of any electrical fault occurring in transformers.

Optimized selection approach of transformer protection devices against atmospheric discharges using expert system

The objective of this paper consists of presenting a design of expert system that assists the procedures involved with the protection specification of transformers and equipments against atmospheric discharges, allowing also to analyze in a detailed and systematic way the behavior of the respective voltage transients that are generated at the supplying area. For such purpose, the expert system developed in this research makes the efficient integration of approaches and techniques that take into account the characteristic aspects of the atmospheric discharges, the experimental analyses that represent the phenomenon and the mathematical models that allow to map the process involved with the formation of the lightning.

Forecast of Stock Market Trends Using Recurrent Networks

Conventional methods for predicting the behavior of financial papers are based on specialist’s analysis and decision-making, and automatic methods are unavailable for most situations.

Computational Tools for Data Processing in Smart Cities

Smart Grids provide many benefits for society. Reliability, observability across the energy distribution system and the exchange of information between devices are just some of the features that make Smart Grids so attractive. One of the main products of a Smart Grid is to data. The amount of data available nowadays increases fast and carries several kinds of information. Smart metres allow engineers to perform multiple measurements and analyse such data. For example, information about consumption, power quality and digital protection, among others, can be extracted. However, the main challenge in extracting information from data arises from the data quality. In fact, many sectors of the society can benefit from such data. Hence, this information needs to be properly stored and readily available. In this chapter, we will address the main concepts involving Technology Information, Data Mining, Big Data and clustering for deploying information on Smart Grids.

Using intelligent systems in experimental signal analysis for power transformer diagnosis

This paper presents detailed intelligent techniques concepts commonly used in power transformer signals analysis. It will be given more attention to Dissolved Gas Analysis (DGA), Transformer Turn Ratio (TTR) and Induced Voltage tests. The main purpose of the work is to establish a database and intelligent system specification that stores all data acquired from testing and therefore make it possible, for an expert system based on intelligent tools, make integration and data analysis.

Using decision support systems for efficient diagnosis of power transmission transformer

This paper presents a tool for managing, storing and processing of various experimental tests performed on power transmission transformers. Such devices represent one of the most valuable assets for utilities and their service removals (by non-scheduled ways or failures), result in long periods of disruption for consumers as well as large financial losses. Thus, there is a constant search involving the development of tools to accomplish the task of identifying prominent failures, especially those that combine conventional and intelligent tools for this purpose.