Methodologies of Artificial Intelligence in Power System
Keywords:
Technology of Power Systems, ANN, Fuzzy Logic, AIAbstract
Much of the emphasis in energy systems assessment has shifted away from previous mathematical modeling, which originated in the areas of operations research, control theory, as well as numerical methods, and toward the less stringent approaches of artificial intelligence (AI) from the probably early 1980s. Frameworks, fuzzy sets, artificial neural networks (ANN), as well as, most lately, adaptive computation are the most common AI methods used in energy systems application areas. Such methodologies, as well as the energy application programs, will be discussed in this study. The goal of this study is to showcase some primary artificial intelligence technology utilized in power systems, wherein previous techniques will be unable to keep up with all functioning and routing conditions. By managing voltages, consistency, current flows, and load frequency, such strategies improve the energy service's performance and efficiency. AI technology to be used in power system operation, supervision, and management. Furthermore, the article will focus discuss the long-term benefits of using AI in power systems.
References
Bimal K. Bose, “Artificial intelligence techniques in smart grid and renewable energy systems— some example applications,” Proc. IEEE, vol. 105(11), pp. 2262–2273, 2017, [Online]. Available: 10.1109/JPROC.2017.2756596
W. R. Anis Ibrahim and M. M. Morcos, “Artificial intelligence and advanced mathematical tools for power quality applications: a survey,” IEEE Trans. Power Deliv., vol. 17(2), pp. 668–673, 2002, doi: 10.1109/61.997958.
A. Alshraideh, M. Al-Lozi, and M. Alshurideh, “The impact of training strategy on organizational loyalty via the mediating variables of organizational satisfaction and organizational performance,” J. Soc. Sci., vol. 6(2), p. . 383–394., 2017, [Online]. Available: http://centreofexcellence.net/J/JSS/Vol6/No2/JSSarticle17,6_2_pp383-394
S. A. Salloum, M. Al-Emran, and K. Shaalan, “The impact of knowledge sharing on information systems: a review, Knowledge Management in Organizations,” KMO 2018, 2018, [Online]. Available: https://doi.org/10.1007/978-3-319-95204-8_9
R. P. Nath and V. N. Balaji, “Artificial intelligence in power systems,” IOSR J. Comput. Engg, pp. 661–2278, 2014, [Online]. Available: www. Iosrjournals.org
