Chemical energy dispatch and multi‐objective programming based on multi‐population optimization and BAS

Abstract Due to the highly continuous, complex energy coupling, and multi‐energy synergy characteristics of chemical production processes, traditional experience‐based or single‐objective energy scheduling methods struggle to simultaneously address energy consumption, fluctuations, and carbon emission constraints. Therefore, this paper constructs a multi‐objective energy scheduling model for chemical production, targeting operating costs, carbon emissions, and scheduling stability, and proposes an improved beetle foraging algorithm that integrates multiple swarming mechanisms. Experiments show that in a typical chemical energy system, the comprehensive energy utilization rate of this method was increased by 12.34% compared with the traditional method, the steam‐power supply and demand balance deviation was reduced by 27.81%, and the system energy efficiency stability coefficient was increased to 0.93. The results show that the proposed model not only realizes the economic and low‐carbon collaborative optimization of chemical energy dispatch, but also provides a generalizable technical path and engineering reference value for intelligent dispatch and green manufacturing of complex process systems.