TY - JOUR
T1 - A longitudinal model for MIBEL energy prices
AU - Borges, Ana
AU - Silva, Eliana Costa E.
AU - Covas, Ricardo
N1 - Funding Information:
Acknowledgements: This work was partially supported by ESGI 119 an initiative supported by COST Action TD1409, Mathematics for Industry Network (MI-NET), COST is supported by the EU Framework Programme Horizon 2020. E. Costa e Silva and A. Borges were supported by Center for Research and Innovation in Business Sciences and Information Systems (CIICESI), ESTG - P.Porto.
Publisher Copyright:
© 2018, World Scientific and Engineering Academy and Society. All rights reserved.
PY - 2018
Y1 - 2018
N2 - We propose to contribute to the problematic of Electricity Price Forecasting with a longitudinal statistical approach. We focus our interest on forecasting intra-day prices using hourly data (disaggregated data) in a multivariate approach rather than in the usually used univariate approach, by adjusting a mixed-effects longitudinal model to the Iberian Electricity Market hourly prices from January 1th 2015 to June 26th 2016, in a total of 13 032 observations. Results indicate that a longitudinal approach considering a mixed-effects model, with month and weekday as fixed effects, hour group as random effect and an AutoRegressive component of order 7 describing the within hour dependence, yield a model that explains the intra-day and intra-hour dynamics for the electricity hourly prices.
AB - We propose to contribute to the problematic of Electricity Price Forecasting with a longitudinal statistical approach. We focus our interest on forecasting intra-day prices using hourly data (disaggregated data) in a multivariate approach rather than in the usually used univariate approach, by adjusting a mixed-effects longitudinal model to the Iberian Electricity Market hourly prices from January 1th 2015 to June 26th 2016, in a total of 13 032 observations. Results indicate that a longitudinal approach considering a mixed-effects model, with month and weekday as fixed effects, hour group as random effect and an AutoRegressive component of order 7 describing the within hour dependence, yield a model that explains the intra-day and intra-hour dynamics for the electricity hourly prices.
KW - Electricity price forecasting
KW - Longitudinal mixed-effects model
KW - MIBEL
UR - http://www.scopus.com/inward/record.url?scp=85041840057&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:85041840057
SN - 1991-8763
VL - 13
SP - 26
EP - 33
JO - WSEAS TRANSACTIONS on SYSTEMS and CONTROL
JF - WSEAS TRANSACTIONS on SYSTEMS and CONTROL
ER -