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Applications of Big Data and AI in Electric Power Systems Engineering
Abstract
The production, transmission, and distribution of energy can only be made stable and continuous by detailed analysis of the data. The energy demand needs to be met by a number of optimization algorithms during the distribution of the generated energy. The pricing of the energy supplied to the users and the change for investments according to the demand hours led to the formation of energy exchanges. This use costs varies for active or reactive powers. All of these supply-demand and pricing plans can only be achieved by collecting and analyzing data at each stage. In the study, an electrical power line with real parameters was modeled and fault scenarios were created, and faults were determined by artificial intelligence methods. In this study, both the power flow of electrical power systems and the methods of meeting the demands were investigated with big data, machine learning, and artificial neural network approaches.
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