Mixed Models for Short-Run Forecasting of Electricity Prices: Application for the Spanish Market
By Carolina García-Martos, José Raúl Rodríguez Rodríguez, M.J. Sanchez. IEEE Transactions on Power Systems, 2007
138 citations recorded by the source corpus.
Short-run forecasting of electricity prices has become necessary for power generation unit schedule, since it is the basis of every profit maximization strategy. In this article a new and very easy method to compute accurate forecasts for electricity prices using mixed models is proposed. The main idea is to develop an efficient tool for one-step-ahead forecasting in the future, combining several prediction methods for which forecasting performance has been checked and compared for a span of several years. Also as a novelty, the 24 hourly time series has been modelled separately, instead of the complete time series of the prices. This allows one to take advantage of the homogeneity of these 24 time series. The purpose of this paper is to select the model that leads to smaller prediction errors and to obtain the appropriate length of time to use for forecasting. These results have been obtained by means of a computational experiment. A mixed model which combines the advantages of the two new models discussed is proposed. Some numerical results for the Spanish market are shown, but this new methodology can be applied to other electricity markets as well
Subfields: Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/e9f6ef42d79d13b896b4cd64c333de3d90a51f73
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In Electrical and Electronic Engineering
Citations in the corpus
- Uncertainty-Aware Household Appliance Scheduling Considering Dynamic Electricity Pricing in Smart Home (2013, methodology): “scheme is independent of pricing models or pricing prediction models as is described in [38], [39].”