Conducting an analysis of the accuracy of the results when building a model for predicting electricity tariffs using the example of the Kaluga Region
Keywords:
analysis, forecast, time series, accuracy, stationarity, electric power, samplingAbstract
The study is devoted to forecasting electricity prices in the Kaluga region using the ARIMA model. The key factors influencing price dynamics are considered: seasonality, weather conditions, economic activity and geographical features. Based on the analysis of the time series, the optimal model configuration is selected. The results showed high accuracy of the forecast based on historical data, however, an increase in error was observed in the test interval, due to the variability of the data. The model demonstrates reliability, but requires further optimization taking into account additional factors.
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