Mathematical Problems in Engineering

Applications of Artificial Intelligence in Smart Grids


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

Lead Editor

1Chung Yuan Christian University, Taoyuan City, Taiwan

2University of Wisconsin, Milwaukee, USA

3Harbin Engineering University, Harbin, China

4University of the Ryukyus, Nishihara, Japan

This issue is now closed for submissions.

Applications of Artificial Intelligence in Smart Grids

This issue is now closed for submissions.

Description

Artificial Intelligence is applied successfully to solve many industrial problems, such as neural networks, fuzzy logic controls, evolutionary computation, and hybrid intelligent systems, etc. Recently, deep learning networks have received much attention as they can deal with more complex non-linear problems.

A power system is a large non-linear and dynamic power grid, in which people request the electric utility to deliver electric power in a stable and reliable manner from a generation system through transmission and distribution systems to end-users. Accordingly, the development of advanced technologies and novel methods using state-of-the-art artificial intelligence to deal with problems in the smart grid is essential. In particular, distributed generation resources, energy storage system, and advanced control/operation are addressed in the smart grid.

This Special Issue aims to collate original papers about artificial intelligence applied to the smart grid and will present important results of work based on fuzzy control, neural network, evolutionary computation, and hybrid intelligent systems as well as deep learning. The works can be applied research, development of new procedures or components, original application of existing knowledge, or new design approaches. Review articles describing the state of the art are also welcomed.

Potential topics include but are not limited to the following:

  • Grid integration of distributed generation resources
  • Power system operation and control
  • Power system reliability and stability
  • Load, renewable power and electricity price forecasting
  • Distribution system automation and control
  • Maximum power tracking control to renewables
  • Adaptive neurofuzzy control in electrical power generation, transmission, and distribution
  • Neurofuzzy modelling for fault diagnosis in electrical machines and power electronics used in the smart grid
Mathematical Problems in Engineering
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