In the last few years we have observed deregulation in electricity markets and an increasing interest in price dynamics has been developed especially to consider all stylized facts shown by spot prices. Only few papers have considered the Italian Electricity Spot market since it has been deregulated recently. Therefore, this contribution is an investigation with emphasis on price dynamics accounting for technologies, market concentration, congestions and volumes. We aim to understand how these four variables affect zonal prices since these ones combine to bring about the single national price (prezzo unico d'acquisto, PUN). Hence, understanding its features is important for drawing policy indications referred to production planning and selection of generation sources, pricing and risk{hedging problems, monitoring of market power positions and nally to motivate investment strategies in new power plants and grid interconnections. Implementing Reg-ARFIMA-GARCH models, we assess the forecasting performance of selected modelsshowing that they perform better when these factors are considered.

Forecasting Italian Electricity Zonal Prices with Exogenous Variables

GROSSI, Luigi
2012

Abstract

In the last few years we have observed deregulation in electricity markets and an increasing interest in price dynamics has been developed especially to consider all stylized facts shown by spot prices. Only few papers have considered the Italian Electricity Spot market since it has been deregulated recently. Therefore, this contribution is an investigation with emphasis on price dynamics accounting for technologies, market concentration, congestions and volumes. We aim to understand how these four variables affect zonal prices since these ones combine to bring about the single national price (prezzo unico d'acquisto, PUN). Hence, understanding its features is important for drawing policy indications referred to production planning and selection of generation sources, pricing and risk{hedging problems, monitoring of market power positions and nally to motivate investment strategies in new power plants and grid interconnections. Implementing Reg-ARFIMA-GARCH models, we assess the forecasting performance of selected modelsshowing that they perform better when these factors are considered.
Electricity prices; Production technologies; Market power; Residual Supply Index; Congestions; Volumes; Fractional Integration; Forecasting
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/430154
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