Chapters authored
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.
Part of the book: Smart Cities Technologies
Emerging Technologies for Renewable Energy Systems
Considering all aspects involving smart grid deployment, several subjects extrapolate the electrical sector. In the Brazilian scenario, it can be clear that power companies cannot support, by themselves, all steps for establishing renewable energy sources in smart grid systems. The technology demands are greater than what the electric sector can deliver. Such discussions about regulations of renewable energy sources are largely discussed in the society. The search for deploying eolic and solar generation with big energy farms are opposite to the smart grid and smart city renewable energy concept, which require decentralized actions. This chapter will show the concepts of eolic and solar energy sources specifically in the context of Smart Grids.
Part of the book: Smart Cities Technologies
Computational Intelligence to Estimate Fault Rates in Power Transformers
Asset management in power transmission systems is one of the significant practices carried out by power companies. With the aging of the devices, the development of optimized tools, capable of considering failure rates, regulatory scenarios, and operational parameters, is increasingly mandatory. The purpose of this work is to present a statistics-based tool for optimized asset management. For such an objective, we have developed a computational method based on database processing and statistical studies that can support decision-making on preventive maintenance in the equipment of the electric sector. The final system interface is Business Intelligence-based.
Part of the book: Application of Expert Systems
Efficient Asset Management Practices for Power Systems Using Expert Systems
Electric power companies have high financial costs due to poor asset management practices. Therefore, it is crucial to use decision-making processes to decrease the global costs of an active asset and to extend its lifetime to a maximum. Asset management programs, which are frequently used to tackle optimization problems, aim to guide the use of the physical assets of a business, mainly by optimizing their lifetime. Efficient asset management practices establish operation and maintenance for each equipment, from the time the equipment is acquired until the appropriate time for its replacement. So, based on these assumptions, we propose a method to assist asset management decision-making in the electric power companies, which is embodied by computer software.
Part of the book: Application of Expert Systems