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Capítulo de Libro
Partitioning-Clustering Techniques Applied to the Electricity Price Time Series
(2007)
Clustering is used to generate groupings of data from a large dataset, with the intention of representing the behavior of a system as accurately as possible. In this sense, clustering is applied in this work to extract ...
Capítulo de Libro
Time-Series Prediction: Application to the Short-Term Electric Energy Demand
(2003)
This paper describes a time-series prediction method based on the kNN technique. The proposed methodology is applied to the 24-hour load forecasting problem. Also, based on recorded data, an alternative model is developed ...
Capítulo de Libro
Application of Evolutionary Computation Techniques to the Optimal Short-Term Scheduling of the Electrical Energy Production
(2003)
In this paper, an evolutionary technique applied to the optimal short-term scheduling (24 hours) of the electric energy production is presented. The equations that define the problem lead to a nonlinear mixed-integer ...
Capítulo de Libro
Influence of kNN-Based Load Forecasting Errors on Optimal Energy Production
(2003)
This paper presents a study of the influence of the accuracy of hourly load forecasting on the energy planning and operation of electric generation utilities. First, a k Nearest Neighbours (kNN) classification technique ...
Capítulo de Libro
A Comparison of Two Techniques for Next- Day Electricity Price Forecasting
(2002)
In the framework of competitive markets, the market’s participants need energy price forecasts in order to determine their optimal bidding strategies and maximize their benefits. Therefore, if generation companies have a ...
Capítulo de Libro
Electricity Market Price Forecasting: Neural Networks versus Weighted-Distance k Nearest Neighbours
(2002)
In today’s deregulated markets, forecasting energy prices is becoming more and more important. In the short term, expected price profiles help market participants to determine their bidding strategies. Consequently, accuracy ...