Statistical modeling of aggregated electricity consumption and distributed wind generation in distribution systems using AMR data

This paper presents a methodology for carrying out statistical analysis of electricity consumption and distributed wind generation in distribution systems in order to investigate their combined effect, e.g., to give a probabilistic estimate of the effective peak net load. Hourly consumption profiles and the expected deviations from the profiles are estimated for different consumer group sizes of different types using automatic meter reading (AMR) data. In addition, a statistical approach to wind power modeling is presented. The consumption and generation models are then combined to give a probabilistic estimate of their combined effect in the long term using Monte Carlo simulations. The presented methodology is applicable to new locations without measurements. To showcase the applicability of the proposed methodology, three wind power and two electricity consumption scenarios are presented and compared.