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Wind power will become a major contributor to electricity supply in many countries around the world over the next decades. Therefore, the wind farms owners must be equipped with tools that allow assisting them in managing and planning the wind power generation.
The present research paper presents five different clustering methods to identify typical load profiles of medium voltage (MV) electricity consumers. These methods are intended to be used in a smart grid environment to extract useful knowledge about customer's behaviour. The obtained knowledge can be used to support a decision tool, not only for utilities but also for consumers. Load profiles can...
Cost-sensitive learning is of critical importance in many domains including bankruptcy prediction where the costs of different errors are unequal. Most existing classification methods aim to minimize overall error based on the assumption that the costs are equal. This paper presents three cost-sensitive learning vector quantization (LVQ) approaches to incorporate cost matrix in classification. Experimental...
This paper deals with the establishment of a characterization methodology of electric power profiles of medium voltage (MV) consumers. The characterization is supported on the data base knowledge discovery process (KDD). Data Mining techniques are used with the purpose of obtaining typical load profiles of MV customers and specific knowledge of their customers' consumption habits. In order to form...
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