Next Article in Journal
Cloud Energy Storage System Operation with Capacity P2P Transaction
Next Article in Special Issue
Electricity Prices and Consumer Behavior, Case Study Serbia—Randomized Control Trials Method
Previous Article in Journal
Maximum Power Point Tracking Based on Reinforcement Learning Using Evolutionary Optimization Algorithms
Previous Article in Special Issue
Analysing the Drivers of Electricity Demand in Spain after the Economic Crisis
Open AccessArticle

The Impact of Forecasting Jumps on Forecasting Electricity Prices

1
Department of Econometrics and Operations Research, Cracow University of Economics, 27 Rakowicka Street, 31-510 Cracow, Poland
2
Department of Statistics, Cracow University of Economics, 27 Rakowicka Street, 31-510 Cracow, Poland
*
Author to whom correspondence should be addressed.
Energies 2021, 14(2), 336; https://doi.org/10.3390/en14020336
Received: 16 November 2020 / Revised: 4 January 2021 / Accepted: 5 January 2021 / Published: 9 January 2021
(This article belongs to the Special Issue Energy Demand and Prices)
The paper is devoted to forecasting hourly day-ahead electricity prices from the perspective of the existence of jumps. We compare the results of different jump detection techniques and identify common features of electricity price jumps. We apply the jump-diffusion model with a double exponential distribution of jump sizes and explanatory variables. In order to improve the accuracy of electricity price forecasts, we take into account the time-varying intensity of price jump occurrences. We forecast moments of jump occurrences depending on several factors, including seasonality and weather conditions, by means of the generalised ordered logit model. The study is conducted on the basis of data from the Nord Pool power market. The empirical results indicate that the model with the time-varying intensity of jumps and a mechanism of jump prediction is useful in forecasting electricity prices for peak hours, i.e., including the probabilities of downward, no or upward jump occurrences into the model improves the forecasts of electricity prices. View Full-Text
Keywords: electricity prices; forecasting; jumps; jump-diffusion model; generalised ordered logit model; time-varying jump intensity electricity prices; forecasting; jumps; jump-diffusion model; generalised ordered logit model; time-varying jump intensity
Show Figures

Figure 1

MDPI and ACS Style

Kostrzewski, M.; Kostrzewska, J. The Impact of Forecasting Jumps on Forecasting Electricity Prices. Energies 2021, 14, 336. https://doi.org/10.3390/en14020336

AMA Style

Kostrzewski M, Kostrzewska J. The Impact of Forecasting Jumps on Forecasting Electricity Prices. Energies. 2021; 14(2):336. https://doi.org/10.3390/en14020336

Chicago/Turabian Style

Kostrzewski, Maciej; Kostrzewska, Jadwiga. 2021. "The Impact of Forecasting Jumps on Forecasting Electricity Prices" Energies 14, no. 2: 336. https://doi.org/10.3390/en14020336

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop