Title :
Electricity pricing in liberalized market using consumer characterization
Author :
Garamvölgyi, M. ; Varga, L.
Author_Institution :
E.ON Hungaria Zrt., Budapest, Hungary
Abstract :
Electricity market liberalization gives the opportunity to customers to choose their electricity supplier. In this new circumstance more exact knowledge of consumer behavior is essential for designing specific pricing strategies, where the pricing considers the consumption patterns from various types of customers. In our paper artificial intelligence techniques (self-organizing maps, neural networks) are applied for consumer characterization and classification. After the characterization procurement costs were calculated for the different consumer groups. Based on the obtained results relationship could be determined between procurement costs and consumer´s load patterns in order to support our traders in procurement activity.
Keywords :
artificial intelligence; consumer behaviour; power engineering computing; power markets; pricing; self-organising feature maps; artificial intelligence technique; consumer behavior; consumer characterization; consumer classification; electricity market liberalization; electricity supplier; neural networks; pricing strategy design; self-organizing map; Artificial intelligence; Computational intelligence; Consumer behavior; Costs; Data mining; Energy consumption; Pattern recognition; Pricing; Procurement; Statistical analysis; consumer characterization; electricity pricing; neural networks; self-organizing map;
Conference_Titel :
Energy Market, 2009. EEM 2009. 6th International Conference on the European
Conference_Location :
Leuven
Print_ISBN :
978-1-4244-4455-7
DOI :
10.1109/EEM.2009.5207210