Abstract <p>The variability of loads in near-zero-energy buildings with photovoltaic direct-drive inverter air-conditioning systems poses challenges for traditional load control methods, which often rely on simple models and fixed rules. This makes it difficult to optimize shutdown, duty cycles, and temperature control, affecting energy utilization and operational stability. To tackle these issues, we propose a cluster load control method utilizing improved modeling and algorithms tailored for these systems. This involves constructing detailed thermodynamic and electrical models to analyze load characteristics and establish effective control strategies. We also introduce a load control model based on an enhanced DEPSO algorithm, focusing on minimizing operational costs while meeting conditions. Experimental results indicate that this approach leads to stable, efficient operation and significantly reduces energy consumption and carbon emissions, demonstrating its effectiveness in optimizing air-conditioning cluster load control in near-zero-energy buildings.</p>