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作 者:刘宝伟 邹宽胜 张兆军 林志芳 LIU Baowei;ZOU Kuansheng;ZHANG Zhaojun;LIN Zhifang(School of Electrical Engineering and Automation,Jiangsu Normal University,Xuzhou 221116,China)
机构地区:[1]江苏师范大学电气工程及自动化学院,江苏徐州221116
出 处:《现代电子技术》2024年第24期97-104,共8页Modern Electronics Technique
基 金:国家自然科学基金项目(12205122);徐州市基础研究计划项目(KC21001)。
摘 要:针对可再生能源在电力系统中大量渗透引起的不确定性,基于线性自抗扰控制展开互联混合电力系统负荷频率控制的研究,提出一种混沌自适应正余弦算法,用于自抗扰控制器的参数设计。首先,融合混沌序列和反向学习策略对种群进行初始化;其次,设计了一种自适应转换参数机制,并在更新方程中加入个体历史最优解;最后,采用莱维飞行扰动策略对最优解进行扰动。同时,将所提算法与其他群智能算法在13个基准函数上进行测试比较,并以含发电机速率约束和调速器死区等非线性因素的双区域混合电力系统为例进行仿真实验。仿真结果表明,改进的优化算法具有较好的寻优精度和收敛速度,所提出的控制策略能够消除负载扰动和可再生能源引起的频率、功率偏差,系统具有快速响应的能力和较好的鲁棒性能。In allusion to the uncertainty caused by the high-penetration of renewable energy resources in power systems,the research on load-frequency control is carried out based on linear auto-disturbance rejection control(ADRC),and a chaotic adaptive sine cosine algorithm is proposed for the parameter design of the auto-disturbance controller.Chaotic sequences and reverse learning strategies are integrated to initialize the population.The adaptive conversion parameter machine is designed,and the individual historical optimal solutions are added to the updating equations.The greedy levy flight mutation scheme is used for the flight mutation.The proposed algorithm is tested and compared with other swarm intelligence algorithms on 13 benchmark functions,and the simulation experiments are conducted by taking two-area hybrid power system containing nonlinear factors,such as generation rate constraint and governor dead band,as an example.The simulation results show that the improved optimization algorithm has better optimization accuracy and convergence speed,the proposed control strategy can eliminate the frequency deviations and power deviations caused by load disturbances and renewable energy sources,and the power system has the ability of fast response and good robustness.
关 键 词:互联混合电力系统 负荷频率控制 线性自抗扰控制 混沌自适应正余弦算法 抗干扰能力 鲁棒性
分 类 号:TN915.853-34[电子电信—通信与信息系统] TP273[电子电信—信息与通信工程] TM743[自动化与计算机技术—检测技术与自动化装置]
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