Data-Driven Sizing of PV-Battery Systems Across Different Load Profiles: A Focus on Field Measurements in Winter

Sizing photovoltaic (PV) arrays and battery energy storage systems (BESS) effectively, especially to meet demands during winter when solar generation is low and consumption is high, is a critical challenge for achieving energy autonomy. This paper addresses this by using relatively high-resolution (5 Hz) field measurements of PV power generation and detailed consumption profiles from a residential household with and without a ground-source heat pump, an office building and a warehouse, all collected during the winter period (late January to mid-March) in southern Germany. The main methodology of this paper involves normalizing the real-world PV production data and consumer load profiles. Two dimensionless sizing parameters are introduced: α for PV array size relative to annual consumption and β for BESS capacity, also relative to annual consumption. This allows for a systematic simulation of various oversizing and undersizing scenarios. Performance is quantified using self-sufficiency and excess energy metrics. This paper demonstrates that even during the challenging winter months, modest PV oversizing (e.g., α = 2) combined with a BESS equivalent to a fraction of annual consumption (e.g., β = 1) can significantly improve self-sufficiency, in some cases doubling or quadrupling it compared to systems with minimal or no storage. However, this paper, also shows that further increases in system size yield only marginal gains in self-sufficiency, which is important to consider given practical constraints such as available roof space and BESS investment costs during winter. This paper gives a method for a more realistic system sizing, moving beyond generalized heuristics by focusing on the demanding winter period.