Multi-time Scale Active and Reactive Power Joint Optimization of Hydrogen-Containing Active Distribution Network

The burgeoning proliferation of renewable energy sources presents significant challenges for the operational management of active distribution networks, chiefly concerning the economical and secure management of distributed power output uncertainties. Concurrently, the increasing adoption of hydrogen energy within distribution networks, owing to its environmental advantages, underscores the need for effective solutions. Addressing the aforementioned challenges within hydrogen-containing active distribution network, this study proposes a comprehensive approach centered on multi-time scale optimization of active and reactive power. This approach comprises two key components: day-ahead scheduling and intra-day correction, aimed at mitigating the intermittency of renewable energy and minimizing the impact of prediction errors on network operation. Furthermore, leveraging insights into the coupling dynamics between active and reactive power within distribution networks and the flexible control capabilities inherent to hydrogen-based equipment, the proposed methodology facilitates the optimization of network losses through coordinated active and reactive power management. Consequently, this not only maximizes operational benefits but also ensures the safe functioning of active distribution networks. The efficacy and viability of the proposed methodology are demonstrated through rigorous simulation analyses and computational assessments.