Robust Co-planning of distributed photovoltaics and energy storage for enhancing the hosting capacity of active distribution networks

The inherent uncertainty of photovoltaic systems (PVs) combined with the limited hosting capacity of conventional distribution networks constrains accessible PV capacity, consequently reducing both economic efficiency and voltage stability. To address these challenges, this study proposes an integrated co-planning framework that explicitly incorporates PV uncertainty via a distributionally-robust optimization model designed to enhance grid hosting capacity. The proposed framework systematically embeds short-circuit current constraints to co-optimize economic benefits and operational security. The methodology employs a two-stage optimization approach. First, a distributionally-robust optimization algorithm constructs a probability distribution set for PV uncertainty to improve scenario representation. Subsequently, a second-order cone programming (SOCP) model is formulated for coordinated PV and the energy storage system (ESS) deployment under multiple scenarios, aiming to minimize total economic costs and voltage deviations. Notably, the model incorporates dynamic short-circuit current constraints at grid connection points, in which PV uncertainty is accounted for through iterative calculations using an equivalent voltage source method. To enhance computational efficiency, an improved column-and-constraint generation (C&CG) algorithm is developed by integrating cutting planes derived from short-circuit current validation results. Case studies conducted on a 43-bus distribution network in Zhejiang Province demonstrate that the proposed method achieves a 60% increase in permissible PV capacity and a 16.7% reduction in voltage deviation compared to conventional approaches without ESS coordination or those using decoupled planning strategies. These results validate the effectiveness of integrated short-circuit current constraints in facilitating high renewable penetration while maintaining grid operational security.