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Chapter of Book
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 ...
Chapter of Book
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 ...
Chapter of Book
Digital factory for small- and medium-sized advanced transport companies
(Taylor and Francis, 2022-01)
The project develops the concept and implementation of Industry 4.0 for small- and medium-sized companies, which is currently lacking in the industrial sector. The aim is to obtain a methodology or procedure to facilitate ...
Chapter of Book
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 ...
Chapter of Book
Overload screening of transmission systems using neural networks
(1998)
The process of determining whether a power system is in a secure or insecure state is a crucial task which must be addressed on-line in any Energy Management System. In this paper, an Artificial Neural Network, capable of ...
Chapter of Book
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 ...
Chapter of Book
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 ...
Chapter of Book
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 ...
Chapter of Book
Development of a surveillance system for maintenance and diagnosis of buses based on can-bus data transmitted wirelessly
(Taylor and Francis, 2022-01)
From the point of view of vehicle maintenance, one of the most important systems of urban buses is the cooling system. These vehicles run typically more than 80,000 km per year, and the radiator of the system gets fouled ...