Universidad Complutense de Madrid
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An Explanatory Analysis of Electricity Prices within Day-Ahead Spanish Energy Market by Using a Graphical Automatization with R

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Velasco, J.M. y González Pérez, Beatriz y Minana, Guadalupe y López, Victoria y Caro, Raquel (2014) An Explanatory Analysis of Electricity Prices within Day-Ahead Spanish Energy Market by Using a Graphical Automatization with R. In Proceedings of 2014 IEEE International Conference on Progress in Informatics and Computing. IEEE, pp. 631-636. ISBN 978-1-4799-2033-4

URL Oficial: http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=6972411&abstractAccess=no&userType=inst



Resumen

Since 1998, the Spanish and Portuguese Administrations began to share a common path in building the Iberian Electricity Market (MIBEL). This cooperation has been very successful, not only for its contribution to the existence of an electricity market on an Iberian level, but also on a European scale, as a significant step in building the Internal Energy Market. The price of electricity in the MIBEL is very changeable. This creates a lot of uncertainty and risk in market actors. Due to continuous changes in demand and marginal price adjustment, buyers and sellers can not know in advance the evolution of prices. Our interest is to study of this uncertainty since the perspective of the buyer and not the seller's perspective. The aim of this work is to develop a graphical analysis of the variables involved in the Spanish Energy Market in order to explain the electric price and provide to small traders, that could be interested in participating in that market, better knowledge of the schedule. On the other hand, large industrial consumers use this information to design strategies to optimize its production capacity and improve their production costs. In this article the variable of interest is the marginal price instead of demand. This paper provides a graphical analysis by means of an easily reproducible automatization with the R project for statistical computing that allows to explore, visualize and understand the key variables that define its final value. Mibel 2011 and 2012 data are used for ilustrations. The results show the importance of the calendar effect, seasonality and trend as principal factors to take into account for posterior fases: modeling and forecasting.


Tipo de documento:Sección de libro
Información Adicional:

2nd IEEE International Conference on Progress in Informatics and Computing (PIC), Shanghai, MAY 16-18, 2014

Palabras clave:electricity market; exploratory analysis; R language
Materias:Ciencias > Informática
Ciencias > Matemáticas > Estadística aplicada
Código ID:32892
Depositado:26 Aug 2015 07:53
Última Modificación:04 Sep 2015 07:37

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