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ARIMA models to predict next-day electricity prices
Abstract
Price forecasting is becoming increasingly relevant to producers and consumers in the new competitive electric power markets. Both for spot markets and long-term contracts, price forecasts are necessary to develop bidding strategies or negotiation skills in order to maximize benefit. This paper provides a method to predict next-day electricity prices based on the ARIMA methodology. ARIMA techniques are used to analyze time series and, in the past, have been mainly used for load forecasting, due to their accuracy and mathematical soundness. A detailed explanation of the aforementioned ARIMA models and results from mainland Spain and Californian markets are presented.
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Citations
Cited by
Electricity price forecasting: A review of the state-of-the-art with a look into the future
Weron, R. (2014) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2014.08.008 · Cited by 1,646
Predicting Taxi–Passenger Demand Using Streaming Data
Moreira-Matias, L., Gama, J., Ferreira, M., Mendes-Moreira, J., & Damas, L. (2013) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2013.2262376 · Cited by 721
A moving-average filter based hybrid ARIMA–ANN model for forecasting time series data
Babu, C. N., & Reddy, B. E. (2014) · Applied Soft Computing · doi:10.1016/j.asoc.2014.05.028 · Cited by 503
Day-Ahead Price Forecasting of Electricity Markets by a New Fuzzy Neural Network
Amjady, N. (2006) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2006.873409 · Cited by 371
Internet of Things Based Smart Grids Supported by Intelligent Edge Computing
Chen, S., Wen, H., Wu, J., Lei, W., Hou, W., Liu, W., Xu, A., & Jiang, Y. (2019) · IEEE Access · doi:10.1109/access.2019.2920488 · Cited by 297
Metadata
- Authors
- Contreras, J., Espinola, R., Nogales, F. J., & Conejo, A. J.
- Venue
- IEEE Transactions on Power Systems
- Published
- 2003-08
- Volume
- 18
- Issue
- 3
- Pages
- 1014-1020
- ISSN
- 0885-8950 (ISSN-L)
- OpenAlex
- W2126831543
- Cited by
- 1,553
- References
- 0
- FWCI
- 20.45
- Type
- journal article
- Language
- en
- Open access
- closed
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- Contreras, J., Espinola, R., Nogales, F. J., & Conejo, A. J. (2003). ARIMA models to predict next-day electricity prices. IEEE Transactions on Power Systems. https://doi.org/10.1109/tpwrs.2002.804943
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