A Distributionally Robust Dispatch Strategy for Distribution Networks Providing Power Support to the Main Grid Considering Tail Risk Assessment

With the increasing scale of centralized photovoltaic-plus-storage power stations, they are required not only to supply local load demands but also to provide power support to the upstream grid. The coupled interactions among renewable energy output, sharp fluctuations in local loads, and limited tie-line support capacity cause conventional dispatching methods to face issues in rare extreme scenarios, such as shortfalls in scheduled power delivery, increased imported power during peak support periods, load shedding, and voltage violations. To address these issues, this paper proposes a Wasserstein distributionally robust dispatch strategy for active distribution networks (ADNs) tailored for Upstream Power Support (UPS) tasks, incorporating tail risk assessment. An ADN operation model is established that integrates PV, energy storage, interruptible loads, and a bidirectional interface with the main grid, where the scheduled power delivery during UPS periods characterizes the support demand to the upper grid. A comprehensive risk loss function, encompassing load shedding, power shortfalls, peak-period power import, PV curtailment, and voltage violations, is constructed, and Conditional Value-at-Risk (CVaR) is employed to capture the tail risk caused by extreme scenarios. A Wasserstein ambiguity set is built around the empirical distribution of finite historical samples, and via dual reformulation, the worst-case distribution conditional risk model is transformed into a tractable mixed-integer second-order cone programming problem. Case studies on modified IEEE 33-bus and 69-bus ADN test systems demonstrate that the proposed method achieves a trade-off between routine operational costs and extreme-scenario security. By optimizing day-ahead charging/discharging schedules of energy storage, it reduces scheduled power shortfalls under low-PV and high-load conditions, as well as peak-period power import dependence, thereby enhancing the power support capability and supply resilience of the active distribution network.