Research and Application of Multi-Load Control Method Based on Predictive Model

The technique of multi-load management is crucial in load scheduling and control, yet it often encounters issues with imprecise scheduling. The conventional particle swarm algorithm fails to address the complexities of multi-load control in this domain, leading to suboptimal outcomes. To improve on this, we introduced a predictive model-based approach for electrical multi-load control, which we then examined. We started by utilizing evolutionary computation principles to pinpoint influential variables and categorized metrics according to the needs of the multi-load control method, thus minimizing disruptive elements. Subsequently, these principles helped devise a comprehensive multi-load control strategy using the predictive model, followed by an exhaustive review of the results. MATLAB simulations reveal that, under specific evaluation measures, the new predictive model outperforms the standard particle swarm algorithm, offering better accuracy in multi-load control and faster processing times for related factors.