A reliability-oriented energy storage sizing assessment method for PV systems based on energy decomposition

This study proposes a physically interpretable energy-decomposition-based framework for energy storage sizing assessment, aiming to provide a new analytical paradigm for evaluating storage requirements in photovoltaic (PV) systems. Based on the intrinsic generation characteristics of PV systems and the regularity of human electricity consumption, the proposed method first decomposes both PV generation and electricity load into deterministic and stochastic components at the annual timescale. The storage requirements associated with these two components are then quantified separately, and the storage demand under different guarantee levels is derived. Finally, the proposed method is benchmarked against the conventional time-series integration approach, and its reliability is rigorously validated. The results show that, at the annual scale, storage demand is dominated by the deterministic component. At the daily scale, the power requirement is sensitive to both electricity generation and load, whereas the energy capacity requirement is mainly governed by the degree of mismatch between them. Comparisons with the time-series integration method further confirm the robustness and stability of the proposed framework. Overall, the method provides a novel and systematic perspective for quantifying storage demand in PV systems and can serve as an effective assessment tool for decision-makers.