Optimal configuration of grid-forming energy storage systems for small-signal stability enhancement of new power systems: from black-box admittance modeling perspective

The large-scale integration of renewable energy substantially increases the risk of wide-band oscillations in new power systems. However, the widespread use of black-box grid-connected converters renders stability assessment methods that rely on explicit control models inapplicable. This paper proposes a unified framework for stability analysis and enhancement tailored to systems containing black-box converters. The framework offers an end-to-end workflow encompassing admittance identification, system-level modal resonance analysis, and the optimal planning of grid-forming energy storage systems (GFM-ESS) to improve stability margins. To address the challenges of GFM-ESS placement and sizing under multi-modal resonance scenarios, an integrated optimization strategy combining an improved sparrow search algorithm (ISSA) with s-domain modal analysis is proposed. Case studies demonstrate the effectiveness of the proposed framework in: (1) accurately characterizing converter grid-side dynamics, (2) providing a quantitative, system-level stability assessment, and (3) significantly improving stability margins through optimally planned GFM-ESS units.