基于改进雪雁算法的热电联产系统经济调度优化  

CHP system ED optimization based on improved snow geese algorithm

作　　者：邱志勇 莫愿斌[1,2] QIU Zhiyong;MO Yuanbin(Instiute of Artificial Intelligence,Guangxi University for Nationalities,Nanning 530006,China;Key Laboratory of Hybrid Computing and Integrated Circuit Design Analysis,Nanning 530006,China)

机构地区：[1]广西民族大学人工智能学院,广西南宁530006 [2]广西混杂计算与集成电路设计分析重点实验室,广西南宁530006

出　　处：《现代电子技术》2025年第6期127-135,共9页Modern Electronics Technique

摘　　要：热电联产技术由于具有经济、低排放、高效能源利用等众多优势,在现代电力系统中应用广泛。文中研究包括多机组在内的热电联产经济调度优化,建立了考虑机组阀点载荷效应、爬坡速率限制等因素的热电联产模型,并对热电联产机组进行了热电解耦改造。针对该模型中数值算法求解存在的无效迭代次数多、收敛精度低甚至不收敛的问题,提出一种具有速度约束的自适应布朗运动雪雁算法,通过约束速度大小以及有规律地调整雪雁算法中布朗运动幅度大小,达到增加有效迭代次数、提高收敛精度的目的。在该模型中进行改进雪雁算法与原始雪雁算法以及其他算法的寻优测试对比,结果表明改进雪雁算法在寻优测试中取得了较好的效果,比其他算法更能减少支出。Combined heat and power(CHP)technology is widely used in modern power system because of its advantages of economy,low emission and high efficiency in energy utilization.The economic dispatch(ED)optimization of CHP is researched,the CHP model considering factors such as valve point load effects and ramp rate limitations of the unit is built,and the thermoelectric decoupling transformation of CHP unit is also carried out.In order to solve the problems of many invalid iterations,low convergence accuracy or even non-convergence of numerical algorithms in this model,an adaptive Brownian motion snow geese algorithm with velocity constraints is proposed.By constrains the velocity and regularly adjusts the Brownian motion amplitude in the snow goose algorithm,the effective iterations are increased and the convergence accuracy is improved.In this model,the improved snow Goose algorithm is compared with the original snow Goose algorithm and other algorithms.The results show that the improved snow Goose algorithm can achieve better results in the optimization test,and can reduce the cost more than other algorithms.

关 键 词：雪雁算法 热电联产 经济调度优化 自适应布朗运动 速度约束 热电解耦 

分 类 号：TN929.5-34[电子电信—通信与信息系统] TM743[电子电信—信息与通信工程]