Forecasting electricity load plays a crucial role regarding decision making and planning for economical purposes. Besides, in light of the recent privatization and deregulation of the power industry, the forecasting of future electricity load turned out to be a very challenging problem. Electricity demand is also an important determinant for electricity spot prices which, in turn, influence the pricing of futures contracts in electricity markets. Empirical data about electricity loads highlight a clear seasonal behavior (higher loads during the winter season), which is partly due to climatic effects. The authors also emphasize the presence of load periodicity at a weekly basis (electricity load is usually lower on weekends or holidays) and at a daily basis (electricity load is clearly influenced by the hour). Finally, a long-term trend may depend on the general economic situation (for example, industrial production affects electricity load). All these features must be captured by the model. The purpose of this paper is then to build an hourly electricity load model. The deterministic component of the model requires linear regression while the authors investigate the stochastic component through classical time series tools. The calibration of the model is performed by using data coming from the Italian market in a 5 years period (2007- 2011). Then, the researchers perform a Monte Carlo simulation in order to compare the simulated values with respect to the real data (both in sample and out of sample inspection). The reliability of the model will be deduced using standard tests which highlight a good fit of the simulated values. © Giovanni Masala, Stefania Marica, 2015.

Electricity load modeling: an application to Italian market

MASALA, GIOVANNI BATISTA;
2015-01-01

Abstract

Forecasting electricity load plays a crucial role regarding decision making and planning for economical purposes. Besides, in light of the recent privatization and deregulation of the power industry, the forecasting of future electricity load turned out to be a very challenging problem. Electricity demand is also an important determinant for electricity spot prices which, in turn, influence the pricing of futures contracts in electricity markets. Empirical data about electricity loads highlight a clear seasonal behavior (higher loads during the winter season), which is partly due to climatic effects. The authors also emphasize the presence of load periodicity at a weekly basis (electricity load is usually lower on weekends or holidays) and at a daily basis (electricity load is clearly influenced by the hour). Finally, a long-term trend may depend on the general economic situation (for example, industrial production affects electricity load). All these features must be captured by the model. The purpose of this paper is then to build an hourly electricity load model. The deterministic component of the model requires linear regression while the authors investigate the stochastic component through classical time series tools. The calibration of the model is performed by using data coming from the Italian market in a 5 years period (2007- 2011). Then, the researchers perform a Monte Carlo simulation in order to compare the simulated values with respect to the real data (both in sample and out of sample inspection). The reliability of the model will be deduced using standard tests which highlight a good fit of the simulated values. © Giovanni Masala, Stefania Marica, 2015.
File in questo prodotto:
File Dimensione Formato  
IMFI_1_2015_Giovanni Masala2.pdf

Solo gestori archivio

Tipologia: versione editoriale
Dimensione 1.69 MB
Formato Adobe PDF
1.69 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/110922
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 6
  • ???jsp.display-item.citation.isi??? ND
social impact