An Intelligent System For Price Forecasting Accuracy Assessment

Author

Canazza, Virginia ; Li, Guang ; Liu, Chen Ching ; Lucarella, Dario ; Venturini, Andrea

Author_Institution

CESI-T & D Networks, Milan

fYear

2005

fDate

6-10 Nov. 2005

Firstpage

92

Lastpage

99

Abstract

For a market player, in order to perform an optimal risk management, it is important to have not only suitable price forecasting tools taking into account the most significant price drivers but also methods to quantify their accuracy. This paper proposes an intelligent system for price forecasting accuracy assessment (ISPF). The core of ISPF is a fuzzy interpolator of the effects of the price drivers; the output is a set of pre-defined price indices over a medium term period. The computational efficiency of ISPF allows its repeated application in a Monte Carlo methodology, in order to calculate the price indices corresponding to a very large number of price drivers values combinations and, then, to determine the probability distributions of the corresponding price indices. The paper reports an application of the proposed ISPF to the forecasted Italian market scenario for year 2005

Keywords

Monte Carlo methods; power markets; pricing; risk analysis; Monte Carlo method; electricity market; electricity spot price; fuzzy interpolator; fuzzy logic electricity price forecasting; intelligent system; optimal risk management; price forecasting accuracy assessment; probability distribution; sensitivity analysis; Analytical models; Computational efficiency; Economic forecasting; Electricity supply industry; Intelligent systems; Monte Carlo methods; Probability distribution; Risk management; Statistical analysis; Supply and demand;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems Application to Power Systems, 2005. Proceedings of the 13th International Conference on

Conference_Location

Arlington, VA

Print_ISBN

1-59975-174-7

Type

conf

DOI

10.1109/ISAP.2005.1599246

Filename

1599246