Sizing Domestic Batteries For Load Smoothing And Peak Shaving Based On Real-World Demand Data

Distributed battery energy storage provides a potential system-wide solution to issues of increasing variability in electricity supply and demand. In this research, we take a demand-driven approach to determining residential battery capacity based on a detailed analysis of measured time series (with perminute resolution) of individual household demand. We consider two modes of battery operation: (i) load smoothing around the average and (ii) peak shaving, where the battery ensures grid power demand does not exceed a set threshold. We determine the battery capacity (in kWh) required for each mode of operation based on an individual household's demand patterns-independent of specific battery characteristics. In addition, we also compare the battery capacity required for the individual houses with that required for the aggregated demand of a collection of households. Our results show that the battery capacity requirements for these modes of operation can vary by more than 10 kWh per house and have a large seasonal variation. They also show that aggregation reduces the per-house battery requirements by 50% for load smoothing and 90% for peak shaving. These results have important implications for battery deployment strategies. In particular, they show that coordinated battery deployment at the street or building complex level is likely to have significant economic benefits. (C) 2021 Elsevier B.V. All rights reserved.