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作 者:李冠雷 杨国勋 陈鹏 王硕禾 LI Guanlei;YANG Guoxun;CHEN Peng;WANG Shuohe(School of Eleetrical and Electronic Engineering,Shijiazhuang Tiedao University,Shijiazhuang 050043,China;Hebei Technology lnnovation Centre for Distributed Energy Applications,Shijiazhuang 050000,China;Power China Hebei Electric Power Engineering Co.Ltd,,Shijiazhuang 050031,China;Hebei Kunneng Electric Power Engineering Consulting Co.Ltd.,Shijiazhuang 050000,China)
机构地区:[1]石家庄铁道大学电气与电子工程学院,河北石家庄050043 [2]河北省分布式能源应用技术创新中心,河北石家庄050000 [3]河北省电力勘测设计研究院有限公司,河北石家庄050031 [4]河北鲲能电力工程咨询有限公司,河北石家庄050000
出 处:《石家庄铁道大学学报(自然科学版)》2024年第3期120-126,共7页Journal of Shijiazhuang Tiedao University(Natural Science Edition)
基 金:河北省分布式能源应用技术创新中心项目(225676132H)。
摘 要:针对传统粒子群算法在求解电气化公路供电系统最优潮流问题时易陷入局部最优解等问题,为提高算法的全局搜索能力,采用牛顿拉夫逊法对交直流混合潮流交替迭代求解,得出供电系统潮流分布,提出以最小系统损耗为目标的交直流混合最优潮流模型,设计了一种改进的线性递减惯性权重自适应学习因子粒子群算法(改进LDW-PSO算法).仿真结果显示,与传统粒子群算法和线性递减权重算法相比,改进算法收敛速度更快,计算精度更高,为电气化公路供电系统的最优潮流计算提供了理论支撑和技术参考.Aiming at the problem that traditional particle swarm algorithm is prone to fall into the local optimal solution when solving the optimal power flow problem of electrified highway power supply system,in order to improve the algorithm's global search ability,the Newton-Raphson method was adopted to solve the AC/DC mixed flow alternately and iteratively,and the flow distribution of the pow-er supply system was obtained:A hybrid optimal AC/DC model with the obiective of minimizing system loss was proposed,and an improved particle swarm algorithm with linearly decreasing inertia weights and adaptive learning factors was designed,The simulation results show that the improved algorithm converges faster and has higher computational accuracy than the traditional particle swarm algorithm and the linear decreasing weight algorithm,It provides theoretical support and technical reference for the optimal power flow calculation of electrified highway power supply system.
关 键 词:电气化公路 交直流混合配电网 改进LDW-PSO算法 最优潮流
分 类 号:TM743[电气工程—电力系统及自动化]
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