Forecasting electricity demand in Greece by employing functional data analysis.

What is it about?

Unlike traditional methods that predict a single future point, this approach forecasts a curve representing daily power consumption. This functional object enables electricity providers to better tailor their pricing and supply strategies in the upcoming day's megawatt hours (MWh) market. To achieve this, the ARIMA algorithm supplemented by functional principal components is utilized for one-step-ahead forecasting. The analysis also incorporates a functional regression using a functional linear model for functional responses, identifying patterns that link one day's consumption to the preceding day. The results demonstrate that the FDA-based method enhances the accuracy of short-term demand forecasts, outperforming classical time series algorithms and neural networks. By providing a more dynamic and comprehensive model of electricity demand, this approach offers significant implications for energy policy and management practices.

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Why is it important?

Because it implements a new theory in a practical problem. Functional Data Analysis is a new mathematical model that predicts curves instead of points.