Forecasting Electricity Spot Prices Accounting for Wind Power Predictions
Publication: Research - peer-review › Journal article – Annual report year: 2013
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Forecasting Electricity Spot Prices Accounting for Wind Power Predictions. / Pinson, Pierre; Jónsson, Tryggvi; Nielsen, Henrik Aa.; Nielsen, Torben S.
In: I E E E Transactions on Sustainable Energy, Vol. 4, No. 1, 2013, p. 210-218 .Publication: Research - peer-review › Journal article – Annual report year: 2013
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TY - JOUR
T1 - Forecasting Electricity Spot Prices Accounting for Wind Power Predictions
A1 - Pinson,Pierre
A1 - Jónsson,Tryggvi
A1 - Nielsen,Henrik Aa.
A1 - Nielsen,Torben S.
AU - Pinson,Pierre
AU - Jónsson,Tryggvi
AU - Nielsen,Henrik Aa.
AU - Nielsen,Torben S.
PB - I E E E
PY - 2013
Y1 - 2013
N2 - A two-step methodology for forecasting of electricity spot prices is introduced, with focus on the impact of predicted system load and wind power generation. The nonlinear and nonstationary influence of these explanatory variables is accommodated in a first step based on a nonparametric and time-varying regression model. In a second step, time-series models, i.e., ARMA and Holt–Winters, are applied to account for residual autocorrelation and seasonal dynamics. Empirical results are presented for out-of-sample forecasts of day-ahead prices in the Western Danish price area of Nord Pool's Elspot, during a two year period covering 2010–2011. These results clearly demonstrate the practical benefits of accounting for the complex influence of these explanatory variables.
AB - A two-step methodology for forecasting of electricity spot prices is introduced, with focus on the impact of predicted system load and wind power generation. The nonlinear and nonstationary influence of these explanatory variables is accommodated in a first step based on a nonparametric and time-varying regression model. In a second step, time-series models, i.e., ARMA and Holt–Winters, are applied to account for residual autocorrelation and seasonal dynamics. Empirical results are presented for out-of-sample forecasts of day-ahead prices in the Western Danish price area of Nord Pool's Elspot, during a two year period covering 2010–2011. These results clearly demonstrate the practical benefits of accounting for the complex influence of these explanatory variables.
KW - Adaptivity
KW - Electricity prices
KW - Forecasting
KW - Nonlinear modeling
KW - Nonparametric modeling
KW - Robustness
U2 - 10.1109/TSTE.2012.2212731
DO - 10.1109/TSTE.2012.2212731
JO - I E E E Transactions on Sustainable Energy
JF - I E E E Transactions on Sustainable Energy
SN - 1949-3029
IS - 1
VL - 4
SP - 210
EP - 218
ER -