Robust comprehensive PV hosting capacity assessment model for active distribution networks with spatiotemporal correlation

Variate but similar microclimate in different buses of a distribution system usually leads to correlated photovoltaic (PV) outputs. Such correlation may reduce the PV output uncertainty and enhance the hosting capacity of active distribution networks (ADNs). To fully elucidate the hosting capacity of geographically dispersed PV, this paper proposes a novel robust comprehensive PV capacity assessment model that considers both the spatiotemporal correlation of PV output and active distribution network management (ADNM) techniques. In the proposed model, the historical PV output data of the vicinity region are employed to generate the empirical spatial and temporal correlation matrix and ellipsoidal uncertainty sets for arbitrary PV site pairs. The uncertainty of PV outputs is addressed by a two-stage robust optimization. Concerning distribution network characteristics, the proposed capacity assessment model employs a convex conic quadratic format of AC power flow equations that are transformed into second-order cone programming. A historical PV output dataset from Suzhou China and a 59-bus rural distribution system in an adjacent city was used to demonstrate the effectiveness of the proposed PV hosting capacity assessment methodology. The hosting capacity results indicate that both spatial and temporal correlations can enhance the PV hosting capacity. Considering both the spatial and temporal leads to a significant increase in PV hosting capacity. To obtain an accurate PV hosting capacity, both spatial and temporal features should be simultaneously considered.