Abstract
The Industry 4.0 concept involves the use of intelligent technology to improve the production processes, such as using centralized management at the system level, which leads to faster and more flexible energy management. Thus, large and small industrial and utility companies need to create a system for predicting electricity consumption. This paper is devoted to the development of a methodology for obtaining a power consumption predictive model based on the use of fuzzy regression analysis. The proposed technique of forming a fuzzy predictive model, considering the weekly and annual cycles, made it possible to simply form a kind of prediction schedule of daily electricity consumption of any complexity. A criterion applied considers both the degree of estimates closeness to the raw data and the degree of fuzziness. The predicting model provides an opportunity to obtain a daily electricity consumption schedule for any day of the month of the year, as well as a short-term daily prediction. The testing results and study of the proposed method effectiveness are presented.
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Tymchuk, S., Shendryk, S., Shendryk, V., Abramenko, I., Kazlauskaite, A. (2020). The Methodology of Obtaining Power Consumption Fuzzy Predictive Model for Enterprises. In: Ivanov, V., Trojanowska, J., Pavlenko, I., Zajac, J., Peraković, D. (eds) Advances in Design, Simulation and Manufacturing III. DSMIE 2020. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-50794-7_21
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