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This paper aims to provide a unified frame for discussing, summarizing and organizing the main advances in electricity price modeling using the continuous time series modeling approach. This work is organized in three topics: how have been extracted the deterministic patterns present in the daily prices; how have been modeled the stochastic component using mean-reversion models; and how have been...
In this paper we suggest the use of robust STAR (Smooth Transition AutoRegressive) processes to model and forecast electricity prices observed on deregulated markets. The robustness of the model is achieved by extending to time series the M-type estimator based on the polynomial weighting function first introduced for independent multivariate data. The robust M-STAR estimator can be considered as...
This paper presents a support vector machine based combined load-price short term forecasting algorithm. The algorithm is implemented as a classifier and predictor for both load and price values. The implicit relationship between price and load is modeled employing time series. A pre-classification technique is applied to reject the unwanted data before starting the process of the data using the proposed...
This paper tests the hypothesis that the ongoing restructuring process in the European electricity sector has led to a common European market for electricity. Based on a Principal Component Analysis (PCA) of wholesale electricity prices in 2002–2006, we reject the assumption of full market integration. For several pairs of countries, the weaker hypothesis of (bilateral) convergence is accepted based...
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