| Issue |
E3S Web of Conf.
Volume 384, 2023
Rudenko International Conference “Methodological Problems in Reliability Study of Large Energy Systems” (RSES 2022)
|
|
|---|---|---|
| Article Number | 01030 | |
| Number of page(s) | 4 | |
| DOI | https://doi.org/10.1051/e3sconf/202338401030 | |
| Published online | 26 April 2023 | |
Forecasting of electricity consumption by industrial enterprises with a continuous nature of production
1 Tashkent State Technical University named by Islam Karimov, Tashkent, 100095, Uzbekistan
2 Karakalpak State University, Nukus, 230101, Uzbekistan
* Corresponding author: ilider1987@yandex.com
The development of models for forecasting electricity consumption is a complex process, due to the non-linear dependence of electricity consumption on factors that affect the forecast indicators. Since the current forecasting methods do not take into account this non-linearity, the difference between the actual and forecast indicators of electricity consumption often exceeds the allowable values. To determine the required forecast indicators with high accuracy is the use of artificial intelligence methods. In this paper, when predicting electricity consumption, the method of autoregression of the integrated moving average is used. An enlarged block diagram of the algorithm for predicting power consumption using the ARIMA method has been developed.
© The Authors, published by EDP Sciences, 2023
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