Перейти к основному содержанию
AkademIndex

Продукты

Для разработчиков

AkademBaseОткрытый API экосистемы
Статья

Energetics Systems and artificial intelligence: Applications of industry 4.0

Tanveer AhmadEnergy and Electricity Research Center, International Energy College, Jinan University, Zhuhai, Guangdong Province, 519070, ChinaHongyu ZhuSchool of Electrical Engineering, Guangxi University, Nanning, 530004, ChinaDongdong ZhangSchool of Electrical Engineering, Guangxi University, Nanning, 530004, ChinaRasikh TariqFacultad de Ingeniería, Universidad Autónoma de Yucatán, Av. Industrias No Contaminantes por Anillo Periférico Norte, Apdo. Postal 150, Cordemex, Mérida 97203, Yucatán, MexicoA. BassamFacultad de Ingeniería, Universidad Autónoma de Yucatán, Av. Industrias No Contaminantes por Anillo Periférico Norte, Apdo. Postal 150, Cordemex, Mérida 97203, Yucatán, MexicoFasee UllahDepartment of Computer Science and IT, Sarhad University of Science and Information Technology, PakistanAhmed Saeed AlGhamdiDepartment of computer engineering, collage of computers and information technology, Taif University, P.O. Box 11099, Taif 21944, Saudi ArabiaSultan S. AlshamraniDepartment of Information Technology, College of Computer and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
2021en
ABI

Аннотация

Industrial development with the growth, strengthening, stability, technical advancement, reliability, selection, and dynamic response of the power system is essential. Governments and companies invest billions of dollars in technologies to convert, harvest, rising demand, changing demand and supply patterns, efficiency, lack of analytics required for optimal energy planning, and store energy. In this scenario, artificial intelligence (AI) is starting to play a major role in the energy market. Recognizing the importance of AI, this study was conducted on seven different energetics systems and their variety of applications, including: i) electricity production; ii) power delivery; iii) electric distribution networks; iv) energy storage; v) energy saving, new energy materials, and devices; vi) energy efficiency and nanotechnology; and vii) energy policy, and economics. The main drivers are the four key techniques used in current AI technologies, including: i) fuzzy logic systems; ii) artificial neural networks; iii) genetic algorithms; and iv) expert systems. In developed countries, the power industry has started using AI to connect with smart meters, smart grids, and the Internet of Things devices. These AI technologies will lead to the improvement of efficiency, energy management, transparency, and the usage of renewable energies. In recent decades/years, new AI technology has brought significant improvements to how power system devices monitor data, communicate with the system, analyze input–output, and display data in unprecedented ways. New applications in the energy system become feasible when these new AI developments are incorporated into the energy industry. But on the contrary, much more investment is needed in global research into AI and data-driven models. In terms of power supply, AI can help utilities provide customers with renewable and affordable electricity from complex sources in a secure manner, while at the same time providing these customers with the opportunity to use their own energy more efficiently. Moreover, policy recommendations, research opportunities, and how industry 4.0 will improve sustainability have been briefly described.

Перевод пока недоступен

Идентификаторы

Цитирования и источники

Цитирований: 2Использованных источников: 0