Abstract:Integrated Energy System (IES) is an important measure to build a clean, low-carbon, safe and efficient modern energy system. To address the problem of traditional optimization algorithms being unable to effectively handle complex nonlinear relationships and high-dimensional control models, this paper proposes a low-carbon control strategy for integrated energy systems based on an improved particle swarm optimization (PSO) algorithm. A multi-objective and multi constraint optimization model considering three indicators, namely total cost, carbon emissions, and system imbalance, was constructed specifically around the economic, environmental, and balanced operation goals of IES. Then, the improved adaptive weight factors and Cauchy mutation strategy are introduced into the standard particle swarm algorithm to enhance global convergence and population diversity. Finally, a numerical simulation was conducted using a certain park as the research object. Research has shown that the improved particle swarm algorithm has good global adaptability and faster convergence speed, effectively reducing carbon emissions without significant increase in system economic costs. The research results can provide theoretical support for IES overall planning.