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All Journal Brilliance: Research of Artificial Intelligence
Mohamed Khaleel
Karabuk University
Decision Sciences, Operations Research & Management Mathematics Other

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Artificial Intelligent Techniques for Identifying the Cause of Disturbances in the Power Grid Mohamed Khaleel; Salah Ali Abulifa; Adel Ali Abulifa
Brilliance: Research of Artificial Intelligence Vol. 3 No. 1 (2023): Brilliance: Research of Artificial Intelligence, Article Research May 2023
Publisher : ITScience (Information Technology and Science)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i1.2165

Abstract

The intricacy of the power system configuration, coupled with the contemporary trends in power generation and demand, renders the attainment of adequate supply quality a daunting task for distribution companies. Several regulations govern the power quality (PQ) of the electrical system. In addition, EN-50160 outlines the voltage characteristics supplied by public electricity networks, which directly impact distribution companies. Secondly, the EN-61000 standards series regulates the electromagnetic compatibility of network-connected devices, which affects the loads. Both power companies and device manufacturers are responsible for ensuring and being impacted by the quality of supply. Artificial Intelligence (AI) techniques refer to a variety of methods and algorithms that enable machines to perform tasks that typically require human-like intelligence, such as perception, reasoning, learning, and decision-making. AI techniques include machine learning, natural language processing, computer vision, robotics, expert systems, and other approaches that use algorithms to analyze and understand complex data, recognize patterns, and make predictions or decisions based on that data Notwithstanding the regulations, there are still unresolved aspects of the supply quality, one of the most significant being the location of the origin of disturbances. This article presents an investigation of the main techniques used to identify the cause of disturbances and locate their origin in the power grid.
Artificial Intelligence in Engineering Mohamed Khaleel; Abdussalam Ali Ahmed; Abdulgader Alsharif
Brilliance: Research of Artificial Intelligence Vol. 3 No. 1 (2023): Brilliance: Research of Artificial Intelligence, Article Research May 2023
Publisher : ITScience (Information Technology and Science)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i1.2170

Abstract

Artificial intelligence (AI) has moved past its primitive stages and is now poised to revolutionize various fields, making it a disruptive technology. This technology is expected to completely transform traditional engineering in design, electrical, communication, and renewable energy approaches that have been human-centred. Despite being in its early stages, AI-powered engineering applications can work with vague design parameters and resolve intricate engineering problems that cannot be tackled using traditional design, electrical, communication, and renewable energy methods. This article aims to shed light on the current progress and future research trends in AI applications in engineering concepts, focusing on the ramp-up period of the last 5 years. Various methods such as machine learning, genetic algorithm, and fuzzy logic have been carefully evaluated from an engineering standpoint. AI-powered design studies have been reviewed and categorized for different design stages such as inspiration, idea and concept generation, evaluation, optimization, decision-making, and modeling. The review shows that there has been an increased interest in data-based design methods and explainable artificial intelligence in recent years. The use of AI methods in engineering applications has proven to be efficient, fast, accurate, and comprehensive, particularly with the use of deep learning methods and combinations that address situations where human capacity is inadequate. However, it is crucial to choose the appropriate AI method for an engineering problem to achieve successful results.
Intelligent Control Techniques for Microgrid Systems Mohamed Khaleel
Brilliance: Research of Artificial Intelligence Vol. 3 No. 1 (2023): Brilliance: Research of Artificial Intelligence, Article Research May 2023
Publisher : ITScience (Information Technology and Science)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i1.2192

Abstract

Microgrids (MG) are complex systems that integrate distributed energy resources to provide reliable and efficient power to local loads. Due to the dynamic and uncertain nature of the MG environment, intelligent control techniques have become a popular solution to ensure optimal performance. This paper provides an overview of the recent advances in intelligent control techniques applied in MG, including neural networks, model predictive control, game theory, deep reinforcement learning, and Bayesian controllers. The paper also presents a discussion of the advantages and limitations of these techniques, highlighting the challenges associated with implementing them in MG systems. Finally, investigation of the existing literature on the performance of intelligent control techniques in MG systems is presented, providing insights into their effectiveness in improving the energy efficiency, stability, and reliability of MG systems.
Co-Authors Abdulgader Alsharif Abdussalam Ali Ahmed Adel Ali Abulifa Salah Ali Abulifa