Optimization of four‑circuit wire arrangement based on improved BP neural network and multi‑objective particle swarm optimization algorithm
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(1.Shandong Electric Power Engineering Consulting Institute Co., Ltd., Jinan 250013, China;2. School of Electrical Engineering,Shandong University, Jinan 250012, China)

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TM752

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    Abstract:

    The multi?circuit line configuration can effectively solve the problems in line reconstruction and construction amidst the increasing shortage of transmission corridors. The conductor spatial arrangement and phase sequence determination for long?distance transmission lines pose great challenges in the design and maintenance of overhead transmission systems. This paper utilizes the ATP?EMTP simulation software to build a model of 500 kV four?circuit transmission line on the same tower, and simulates the induced voltage and current values with different line lengths, tower spacings, vertical and horizontal inter?circuit gaps, phase sequence arrangements, and tower nominal heights. Employing a BP neural network optimized by genetic algorithm, this paper achieve to predict the induced voltage and current values under unknown conductor spatial arrangements and phase sequences. Subsequently, according to the relevant electromagnetic environment control criteria, the multi?objective particle swarm optimization algorithm is used to optimize the conductor layout and phase sequence arrangement for overhead transmission lines. This process yields a four?circuit conductor arrangement meeting the electromagnetic environment requirements, thus providing a reference for the selection of substation grounding switches.

    Reference
    [1] 高明鑫,胡志坚,倪识远,等.四回非全线平行线路零序分布参数测量方法[J].电工技术学报,2022,37(6):1351?1364. GAO Mingxin,HU Zhijian,NI Shiyuan,et al.Measurement method for zero sequence distribution parameters of four non full line parallel lines[J].Transactions of China Electrotechnical Society,2022,37(6):1351?1364.
    [2] 杨加伦,夏令志,操松元,等.基于特定重现期的电网舞动区域分布图绘制方法[J].电网与清洁能源,2022,38(5):79?85+94. YANG Jialun,XIA Lingzhi,CAO Songyuan,et al.A method for drawing the distribution map of power grid fluctuation area based on a specific recurrence period[J].Power System and Clean Energy,2022,38(5): 79?85+94.
    [3] 冯谟可,王傲群,袁帅,等.国产化电磁暂态仿真平台发展方向分析及展望[J].电力系统自动化,2022,46(10):64?74. FENG Moke,WANG Aoqun,YUAN Shuai,et al.Analysis and prospect of the development direction of localized electromagnetic transient simulation platform[J].Automation of Electric Power Systems,2022,46(10): 64?74.
    [4] 商立群,吉宁.基于电磁时间反转理论的非全程同杆双回线故障测距[J].电力系统保护与控制,2022,50(5):128?135. SHANG Liqun,JI Ning.Fault location of non full range double circuit lines on the same pole based on electromagnetic time reversal theory[J].Power System Protection and Control,2022,50(5):128?135.
    [5] 王华彪,李小勇.基于融合注意力机制改进双向长短时记忆网络在电动汽车充电负荷中的预测研究[J].电网与清洁能源,2022,38(6):104?112. WANG Huabiao,LI Xiaoyong.Research on improving bidirectional long short term memory network based on fusion attention mechanism for predicting electric vehicle charging load[J].Power System and Clean Energy,2022,38(6): 104?112.
    [6] 黄树帮,陈耀,金宇清.碳中和背景下多通道特征组合超短期风电功率预测[J].发电技术,2021,42(1):60?68. HUANG Shubang,CHEN Yao,JIN Yuqing.Ultra short term wind power prediction based on multi?channel feature combination under the background of carbon neutrality[J].Power Generation Technology,2021,42(1): 60?68.
    [7] 肖丽平,吕超,田紫君.统一电能质量调节器的结构及控制策略综述[J].智慧电力,2021,49(12):1?10. XIAO Liping,Lü Chao,TIAN Zijun.Overview of the structure and control strategy of unified power quality regulators[J].Smart Power,2021,49(12): 1?10.
    [8] 朱显辉,于越,师楠,等.BP神经网络的分层优化研究及其在风电功率预测中的应用[J].高压电器,2022,58(2):158?163+170. ZHU Xianhui,YU Yue,SHI Nan,et al.Research on layered optimization of BP neural network and its application in wind power prediction[J].High Voltage Apparatus,2022,58(2): 158?163+170.
    [9] JIANG Q,HUANG R M,HUANG Y C,et al.Application of BP neural network based on genetic algorithm optimization in evaluation of power grid investment risk[J].IEEE Access,2019,7:154827?154835.
    [10] 朱艳伟,石新春,但扬清,等.粒子群优化算法在光伏阵列多峰最大功率点跟踪中的应用[J].中国电机工程学报,2012,32(4):42?48. ZHU Yanwei,SHI Xinchun,DAN Yangqing,et al.Application of PSO algorithm in global MPPT for PV array[J].Proceedings of the CSEE,2012,32(4):42?48.
    [11] 江炳蔚,魏斌,何浩,等.磁耦合谐振式无线电能传输技术在电力系统中的应用[J].发电技术,2022,43(1):32?43. JIANG Bingwei,WEI Bin,HE Hao,et al.The application of magnetic coupling resonant radio energy transmission technology in power systems[J].Power Generation Technology,2022,43(1): 32?43.
    [12] 姚金霞,郭志红,朱振华,等.500 kV同塔双回线路感应电压、电流的研究[J].华北电力技术,2006(1):23?25+28. YAO Jinxia,GUO Zhihong,ZHU Zhenhua,et al.Research on inductive voltage and inductive current of 500 kV double?circuit transmission line[J].North China Electric Power,2006(1):23?25+28.
    [13] 吴田,徐小康,黎鹏,等.500 kV交直流同塔输电线路感应电压和电流的多因素分析[J].高压电器,2022,58(5):47?55. WU Tian,XU Xiaokang,LI Peng,et al.Multi factor analysis on induced voltage and current of 500 kV AC/DC transmission lines on the same tower[J].High Voltage Apparatus,2022,58(5):47?55.
    [14] 时浩,肖海平,刘彦鹏.基于BP神经网络和最小二乘支持向量机的灰熔点预测和对比[J].发电技术,2022,43(1):139?146. SHI Hao,XIAO Haiping,LIU Yanpeng.Prediction and comparison of ash melting point based on BP neural network and least squares support vector machine[J].Power Generation Technology,2022,43(1): 139?146.
    [15] 韩建富,肖春,宋小兵,等.基于GA?BP神经网络的能源互联网窃电行为识别方法[J].电气传动,2022,52(14):38?44. HAN Jianfu,XIAO Chun,SONG Xiaobing,et al.An identification method of electicity theft on energy internet based on GA?BP neural network[J].Electric Drive,2022,52(14):38?44.
    [16] 魏震波,鞠啟,易刚春,等.基于改进LFM算法的主动解列断面搜索方法[J].智慧电力,2021,49(4):82?88. WEI Zhenbo,JU Qi,YI Gangchun,et al.An active splitting section search method based on improved LFM algorithm[J].Smart Power,2021,49(4): 82?88.
    [17] 陈永龙,石麒,王二庆.基于GA理论与QPSO?ELM结合的短期负荷预测方法[J].湖南电力,2022,42(1):64?70. CHEN Yonglong,SHI Qi,WANG Erqing.Short?term load forecasting method based on QPSO?ELM combined with GA theory[J].Hunan Electric Power,2022,42(1):64?70.
    [18] 郑云龙,罗日成,邹明,等.330 kV同塔双回输电线路下平行运行的380 kV线路感应电压电流仿真计算[J].电力科学与技术学报,2021,36(1):216?222. ZHENG Yunlong,LUO Richeng,ZOU Ming,et al.Induced voltage and current simulation of 380 kV line parallel operating under 330 kV double?circuit transmission lines[J].Journal of Electric Power Science and Technology,2021,36(1):216?222.
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陈 鹏,郎需军,国 震,杨 博,耿 行.基于改进BP神经网络和多目标粒子群算法的四回路导线布置优化[J].电力科学与技术学报英文版,2023,38(4):151-161. CHEN Peng, LANG Xujun, GUO Zhen, YANG Bo, GENG Hang. Optimization of four‑circuit wire arrangement based on improved BP neural network and multi‑objective particle swarm optimization algorithm[J]. Journal of Electric Power Science and Technology,2023,38(4):151-161.

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  • Online: November 06,2023
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