Journal of Electrical and Computer Engineering

Computational Intelligence Applied to Smart Grids


Publishing date
01 Apr 2021
Status
Closed
Submission deadline
11 Dec 2020

1UNESP - São Paulo State University, São Paulo, Brazil

2UNESP - São Paulo State University, Ilha Solteira, Brazil

3UNICAMP – State University of Campinas, Campinas, Brazil

4CNPq (National Council for Scientific and Technological Development), Lago Sul, Brazil

5University of Calgary, Calgary, Canada

This issue is now closed for submissions.
More articles will be published in the near future.

Computational Intelligence Applied to Smart Grids

This issue is now closed for submissions.
More articles will be published in the near future.

Description

In the past decade, expansions in electrical systems due to urban growth have led to an increase in investments by utilities in the development of new techniques/technologies and protection philosophies. The main focus is to improve the reliability, quality, and efficiency of the electricity supply by modernizing the electric power energy systems, i.e., devices and operations. On the one hand, device modernization is related to the use of intelligent concepts that enable the whole system to operate with minimal intervention from the operator. On the other hand, the modernization of operation, which is a result of the device’s modernization, intends to render the system proactive, i.e., the operation and management become more efficient due to the anticipation of information related to any occurrence of the feeder. From this perspective, a new paradigm, defined as a smart grid, was created.

Smart grid systems explore the relationship between the power supply sector, the environment, and consumers. The production of electrical power is accomplished with distinct sources of energy, i.e., traditional and renewable. The renewable methods allow the generation to be centralized or distributed, such as hydro, thermal, wind, and solar. Then, the transmission systems for these sources of energy must be designed to operate with greater efficiency and flexibility, where the consumers choose the power supply company from which he/she will buy electricity. The new technologies rely upon two types of technologies; electrical and digital equipment technology, and information technology. The first refers to the use of high-speed semiconductor components in communication, control, and protection. The second comprises a large set of procedures and techniques for processing and analyzing information.

In this perspective, it is necessary to develop an integrated system combining the acquisition, processing, and analysis of data that will incorporate into the system the concepts of intelligence and learning capacity. Some of the techniques available for this purpose are artificial immune systems, deep learning, DNA computing, fuzzy logic, intelligent computing, optimization, neural networks, reservoir computing, and quantum computing, among others.

Thus, the aim of this Special Issue is to bring together many quality contributions in order to make available an extensive collection of intelligent methodologies that present important and innovative solutions in smart grid system applications. Both original research articles, and reviews discussing the current state of the art, are welcomed.

Potential topics include but are not limited to the following:

  • Auto-reconfiguration methods employed in active distribution networks and virtual power plants
  • Communication and control for smart power networks
  • Cybersecurity in smart grid systems
  • Development of smart home and city concepts
  • Electric load and price forecasting for reliable and secure operation of the electric power system (generation, transmission, and distribution)
  • Hierarchical structure of micro grids
  • Integration and control of new sustainable electric energy sources
  • Intelligent monitoring and protection applied to anticipatory fault acting systems (detection, classification, and location)
  • Intelligent optimization applied to optimal power flow
  • Power quality analysis
  • Preventive control (strategies for blackout prevention and transient stability analysis)
Journal of Electrical and Computer Engineering
 Journal metrics
Acceptance rate17%
Submission to final decision90 days
Acceptance to publication37 days
CiteScore3.900
Journal Citation Indicator0.410
Impact Factor-
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Article of the Year Award: Outstanding research contributions of 2020, as selected by our Chief Editors. Read the winning articles.