Forecasting Electricity Prices: An Optimize Then Predict-Based Approach

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Abstract

We are interested in electricity price forecasting at the European scale. The electricity market is ruled by price regulation mechanisms that make it possible to adjust production to demand, as electricity is difficult to store. These mechanisms ensure the highest price for producers, the lowest price for consumers and a zero energy balance by setting day-ahead prices, i.e. prices for the next 24h. Most studies have focused on learning increasingly sophisticated models to predict the next day's 24 hourly prices for a given zone. However, the zones are interdependent and this last point has hitherto been largely underestimated. In the following, we show that estimating the energy cross-border transfer by solving an optimization problem and integrating it as input of a model improves the performance of the price forecasting for several zones together.


Bibtex (lrde.bib)

@InProceedings{	  tschora.23.ida,
  author	= {L{\'e}onard Tschora and Erwan Pierre and Marc Plantevit
		  and C{\'e}line Robardet},
  editor	= {Cr{\'e}milleux, Bruno and Hess, Sibylle and Nijssen,
		  Siegfried},
  title		= {Forecasting Electricity Prices: An Optimize Then
		  Predict-Based Approach},
  booktitle	= {Advances in Intelligent Data Analysis XXI},
  year		= 2023,
  publisher	= {Springer Nature Switzerland},
  address	= {Cham},
  pages		= {446--458},
  abstract	= {We are interested in electricity price forecasting at the
		  European scale. The electricity market is ruled by price
		  regulation mechanisms that make it possible to adjust
		  production to demand, as electricity is difficult to store.
		  These mechanisms ensure the highest price for producers,
		  the lowest price for consumers and a zero energy balance by
		  setting day-ahead prices, i.e. prices for the next 24h.
		  Most studies have focused on learning increasingly
		  sophisticated models to predict the next day's 24 hourly
		  prices for a given zone. However, the zones are
		  interdependent and this last point has hitherto been
		  largely underestimated. In the following, we show that
		  estimating the energy cross-border transfer by solving an
		  optimization problem and integrating it as input of a model
		  improves the performance of the price forecasting for
		  several zones together.},
  isbn		= {978-3-031-30047-9},
  doi		= {10.1007/978-3-031-30047-9_35}
}