Application of Honey Bee Mating Optimization algorithm to load profile clustering

A broad range of intelligent metering solutions in the form of Automated Meter Reading (AMR) or Advanced Metering Infrastructure (AMI) are used today in electrical networks to meet the challenges posed by the development of electricity markets. In parallel, Load Profiling (LP-ing) techniques based on intelligent software solutions, can be used to support market access of small consumers who are not equipped with digital meters. This paper proposes a new approach to the LP clustering problem based on the Honey-Bee Mating Optimization (HBMO) algorithm. The results show a good behavior of the proposed algorithm in terms of robustness and stability with respect to the structure of the database. The proposed approach requires fewer parameters to be calibrated, in comparison with other alternative methods.