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The electricity market has been significantly changing in the last decade. The deployment of smart meters is enabling the logging of huge amounts of data relating to the operations of utilities with the potential of being translated into valuable knowledge on the behaviour of consumers. This work proposes a methodology for predicting the typical daily load profile of electricity usage based on static data using fuzzy clustering and modelling. The methodology intends to: (1) determine consumer segments based on the metering data using the fuzzy c-means clustering algorithm, and (2) develop Takagi-Sugeno fuzzy models in order to predict the demand profile of the consumers.

Fuzzy clustering and prediction of electricity demand based on household characteristics