基于自适应粒子群算法的热电联产系统优化调度  

Optimization and Scheduling of Cogeneration Systems Based on Adaptive Particle Swarm Optimization Algorithm

作　　者：薛丰 XUE feng(Chn Energy Huizhou Cogeneration Co.,Ltd.,Guangdong huizhou 516082,China)

机构地区：[1]国能(惠州)热电有限责任公司,广东惠州516082

出　　处：《自动化与仪器仪表》2025年第3期310-312,317,共4页Automation & Instrumentation

摘　　要：为了提高热电联产系统运行的经济性,提出了一种基于自适应粒子群算法的热电联产系统优化调度模型。以热电联产系统总运行成本最小为目标函数,综合考虑各项约束条件,建立了热电联产系统优化调度模型。采用自适应粒子群算法对模型进行求解,并将求解结果与粒子群算法和遗传算法进行对比,仿真结果表明,自适应粒子群算法优化结果的精度更高,稳定性更好,收敛时间更短,验证了所提热电联产系统优化调度的正确性和有效性。In order to improve the economic efficiency of the operation of cogeneration systems,a self-adaptive particle swarm optimization algorithm based optimization scheduling model for cogeneration systems is proposed.A thermal power cogeneration system optimization scheduling model was established with the objective function of minimizing the total operating cost and considering various constraints.The adaptive particle swarm optimization algorithm was used to solve the model,and the solution results were compared with particle swarm optimization algorithm and genetic algorithm.The simulation results showed that the optimization results of the adaptive particle swarm optimization algorithm had higher accuracy,better stability,and shorter convergence time,which verified the correctness and effectiveness of the proposed optimization scheduling for cogeneration systems.

关 键 词：热电联产系统 优化调度 自适应粒子群算法 总运行成本 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]