Load control technology for cascade optimization operation of comprehensive energy system based on combination variable weight

Abstract The load cascade status data of the integrated energy system belongs to multidimensional and multi-source data, and there are uncertain changes. The predicted results have high errors compared to the actual situation, resulting in high network losses and low load balancing rates, which urgently need to be controlled. Combining variable weights to respond to the demand for cascade loads in the integrated energy system and using the variational mode decomposition method to decompose the cascade load sequence data and construct a load forecasting model. Construct the objective function and constraints for load control in the cascade optimization operation of the integrated energy system and use an improved immune ant colony algorithm to solve the objective function of the load prediction model, achieving load control in the cascade optimization operation of the integrated energy system. The experimental results show that the proposed method has a low error between the predicted results and the actual situation of the cascade load in the integrated energy system. Load control can reduce network losses and improve the load balancing rate.