Optimal Operation and Photovoltaic Consumption Assessment of Active Distribution System Considering Photovoltaic Output Dynamic Correlation

With the increasing penetration of photovoltaic (PV) generation in distribution networks, the impact of spatial correlation and output uncertainty among multiple PV stations on system operation becomes increasingly significant. This paper proposes an optimal operation and PV consumption assessment method taking into account the PV output dynamic correlation. First, a PV output uncertainty model is proposed by combining the seasonal autoregressive integrated moving average (SARIMA) model and dynamic conditional correlation generalised autoregressive conditional heteroskedasticity (DCC‐GARCH), forming a SARIMA‐DCC‐GARCH framework. In parallel, Electric Vehicle (EV) load uncertainty is characterised using probabilistic statistics and Monte Carlo (MC) simulations. Second, an affine modelling approach is employed for uncertainty power flow analysis, where system state responses to perturbations are linearised and reformulated as deterministic constraints within the scheduling problem. Third, a flexible resource (FR) cooperative optimisation scheduling strategy is designed to alleviate the local pressure during high output hours, improve PV consumption efficiency and ensure operational security. Case studies show that the proposed method can improve the level of PV consumption and reduce the system operating cost while guaranteeing voltage safety.