TY - GEN
T1 - Time series data mining for energy prices forecasting
T2 - 16th International Conference on Intelligent Systems Design and Applications, ISDA 2016
AU - e Silva, Eliana Costa
AU - Borges, Ana
AU - Teodoro, M. Filomena
AU - Andrade, Marina A.P.
AU - Covas, Ricardo
N1 - Sem PDF conforme despacho.
PY - 2017/1/1
Y1 - 2017/1/1
N2 - Recently, at the 119th European Study Group with Industry, the Energy Solutions Operator EDP proposed a challenge concerning electricity prices simulation, not only for risk measures purposes but also for scenario analysis in terms of pricing and strategy. The main purpose was short-term Electricity Price Forecasting (EPF). This analysis is contextualized in the study of time series behavior, in particular multivariate time series, which is considered one of the current challenges in data mining. In this work a short-term EPF analysis making use of vector autoregressive models (VAR) with exogenous variables is proposed. The results show that the multivariate approach using VAR, with the season of the year and the type of day as exogenous variables, yield a model that explains the intra-day and intra-hour dynamics of the hourly prices.
AB - Recently, at the 119th European Study Group with Industry, the Energy Solutions Operator EDP proposed a challenge concerning electricity prices simulation, not only for risk measures purposes but also for scenario analysis in terms of pricing and strategy. The main purpose was short-term Electricity Price Forecasting (EPF). This analysis is contextualized in the study of time series behavior, in particular multivariate time series, which is considered one of the current challenges in data mining. In this work a short-term EPF analysis making use of vector autoregressive models (VAR) with exogenous variables is proposed. The results show that the multivariate approach using VAR, with the season of the year and the type of day as exogenous variables, yield a model that explains the intra-day and intra-hour dynamics of the hourly prices.
KW - Data mining
KW - Electricity prices forecasting
KW - Multivariate time series
KW - Vector autoregressive models
UR - http://www.scopus.com/inward/record.url?scp=85014384507&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-53480-0_64
DO - 10.1007/978-3-319-53480-0_64
M3 - Conference contribution
AN - SCOPUS:85014384507
SN - 9783319534794
T3 - Advances in Intelligent Systems and Computing
SP - 649
EP - 658
BT - Intelligent Systems Design and Applications - 16th International Conference on Intelligent Systems Design and Applications, ISDA 2016
A2 - Novais, Paulo
A2 - Madureira, Ana Maria
A2 - Abraham, Ajith
A2 - Gamboa, Dorabela
PB - Springer Verlag
Y2 - 16 December 2016 through 18 December 2016
ER -