  Dynamic Prediction of Energy Delivery Capacity of Power Networks : Unlocking the Value of Real-Time Measurements.; ; et al in Proceedings of the third IEEE PES Conference on Innovative Smart Grid Technologies (2012, January) This paper describes recent advances in prediction software using advanced data-mining tools, and shows how this can significantly increase the operational value of the data gathered. These new tools ... [more ▼] This paper describes recent advances in prediction software using advanced data-mining tools, and shows how this can significantly increase the operational value of the data gathered. These new tools allow for new operational procedures to be defined that increase the usages of the network without decreasing security of supply. We will use the example of dynamic line rating, i.e. determining the thermal rating of an overhead line based on real-time environmental parameters (temperature, wind speed & direction and solar radiation) to highlight how the use of numerical data-mining tools can help us reliably predict future behavior of power networks. [less ▲] Detailed reference viewed: 35 (8 ULg)A Machine Learning Approach for Material Detection in Hyperspectral ImagesMarée, Raphaël  ; Stevens, Benjamin ; Geurts, Pierre et alin Proc. 6th IEEE Workshop on Object Tracking and Classification Beyond and in the Visible Spectrum (OTCBVS-CVPR09) (2009) In this paper we propose a machine learning approach for the detection of gaseous traces in thermal infra red hyperspectral images. It exploits both spectral and spatial information by extracting subcubes ... [more ▼] In this paper we propose a machine learning approach for the detection of gaseous traces in thermal infra red hyperspectral images. It exploits both spectral and spatial information by extracting subcubes and by using extremely randomized trees with multiple outputs as a classifier. Promising results are shown on a dataset of more than 60 hypercubes. [less ▲] Detailed reference viewed: 35 (12 ULg)Application of the Galileo system for a better synchronization of electrical power systems; Capitanescu, Florin ; et al(2007, July) In this paper we present objectives and strategies of the NAVELEC research project funded by the European Union Galileo Joint Undertaking (GJU/05/2423). The project objective is to assess how the European ... [more ▼] In this paper we present objectives and strategies of the NAVELEC research project funded by the European Union Galileo Joint Undertaking (GJU/05/2423). The project objective is to assess how the European Global Navigation Satellite System related solutions can enhance the operation and control of the European power system over wide areas. Some basic functionalities of the GALILEO system are given first, then we summarize the questionnaire, set at the initial stage of the project, and provide the analysis of received responses from transmission system operators. Two generic strategies to upgrade existing electrical power transmission networks with functionalities, as well as major steps to upgrade underlying infrastructures, are discussed in this paper. [less ▲] Detailed reference viewed: 25 (1 ULg)Process monitoring using a combination of data driven techniques and model based data validation; Heyen, Georges ; et alin Revista de Chimie (2007), 58(4), 423-426 Process monitoring is made difficult when measurements are subjected to errors, since pertinent information is hidden in the measurement noise. To address this issue, one can use model based data ... [more ▼] Process monitoring is made difficult when measurements are subjected to errors, since pertinent information is hidden in the measurement noise. To address this issue, one can use model based data validation, or rely on statistical techniques to analyze large historical data sets (data mining). An industrial case study is presented here, where a model based approach (data validation) is compared to data driven techniques. [less ▲] Detailed reference viewed: 56 (7 ULg) A probabilistic approach to power system network planning under uncertainties; ; et al in Proceedings of the IEEE Bologna Power Tech Conference (2003) This work proposes a methodology and a practical tool for the study of long-term network planning under uncertainties. In this approach the major external uncertainties during the planning horizon are ... [more ▼] This work proposes a methodology and a practical tool for the study of long-term network planning under uncertainties. In this approach the major external uncertainties during the planning horizon are modeled as macroscenarios at different future time instants. On the other hand, the random nature of actual operating conditions is taken into account by using a probabilistic model of microscenarios based on past statistics. Massive Monte-Carlo simulations are used to generate and simulate a large number of scenarios and store the detailed results in a relational database. Data mining techniques are then applied to extract information from the database so as to rank scenarios and network reinforcements according to different criteria. [less ▲] Detailed reference viewed: 18 (3 ULg) |
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