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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 ...
Artículo
Electricity Market Price Forecasting Based on Weighted Nearest Neighbors Techniques
(Institute of Electrical and Electronics Engineers (IEEE), 2007)
This paper presents a simple technique to forecast next-day electricity market prices based on the weighted nearest neighbors methodology. First, it is explained how the relevant parameters defining the adopted model are ...
Artículo
Evolutionary techniques applied to the optimal short-term scheduling of the electrical energy production
(Elsevier, 2008)
This paper presents an evolutionary technique applied to the optimal short-term scheduling (24 h) of the electric energy production. The equations that define the problem lead to a non-convex non-linear programming problem ...
Ponencia
Aplicación de Técnicas de Clustering a la Serie Temporal de los Precios de la Energía en el Mercado Eléctrico
(Thomson, 2007)
La principal tarea de las técnicas de clustering es formar grupos de elementos que presenten una conducta similar a partir de una base de datos. Se trata de generar un modelo capaz de simular el comportamiento del sistema ...
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 ...
Ponencia
Discovering Patterns in Electricity Price Using Clustering Techniques
(2007)
Clustering is a process of grouping similar elements gathered or occurred closely together. This paper presents two clustering techniques, K-means and Fuzzy Cmeans, for the analysis of the electricity prices time series. ...
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 ...