POA-GWO-CSO-Based Coordinated Source-Load-Storage Interactive Optimal Dispatch Strategy for Active Distribution Networks
High-penetration renewable integration in the Ningxia region induces substantial wind and photovoltaic curtailment, exposing the limitations of single-sided dispatch formulations that treat generation, demand, and storage independently. This study develops a coordinated source-load-storage interactive optimal dispatch strategy for active distribution networks, solved via a hybrid Pelican Optimization Algorithm-Grey Wolf Optimizer-Crisscross Optimization (POA-GWO-CSO) framework. A detailed building thermal dynamics model is constructed from a resistance-capacitance network, quantifying the thermal storage of envelopes and enabling air-conditioning loads to function as virtual energy storage under user comfort constraints. Source-side wind and photovoltaic output prediction models incorporate forecast-error quantification; storage-side battery life-cycle constraints dynamically match source-load temporal mismatches. A multi-objective dispatch strategy minimizes system operating cost while maximizing renewable consumption. The hybrid algorithm embeds the alpha-beta-delta leadership mechanism of GWO and the horizontal-vertical crisscross operations of CSO into the POA framework, improving local search precision and convergence efficiency. Validation on the actual Minning Town dataset demonstrates that the proposed strategy reduces operating cost and increases renewable utilization relative to conventional dispatch approaches, confirming the effectiveness of multi-side coordination for high-renewable active distribution networks.