Abstract
The article analyzes various approaches to the modeling of daily electricity load schedules and proposes a methodology for improving the "bottom-up" behavioral model of the load of household consumers. The method is based on averaging generated random load schedules for a given type of household on a particular day of the year. Averaging is carried out by season and length of daylight. Next, working days and weekends are distinguished in each interval. Despite some differences, this work does not separate holidays, Saturdays, and Sundays to avoid unnecessary details. The selected parameters for dividing the averaging intervals allow you to obtain a relatively compact set of model data and, at the same time, preserve the features of the load on different days of the year and hours of the day. Household load profiles with varying steps of day distribution and the main difference of such distribution are considered. Models that more accurately convey the sporadic nature of prosumer consumption compared to typical load schedules are built for two types of households. A detailed analysis of the averaged load graphs was carried out in comparison with the typical graph and the generated load graphs. Averaged load schedules are suitable for modeling the operating modes and control algorithms of the prosumer energy generation and storage system.
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