Journal of Electrical Engineering ›› 2022, Vol. 17 ›› Issue (4): 309-317.doi: 10.11985/2022.04.033
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LIU Jiangtao1(), YAN Qiaona1(), ZHOU Tao2, SHAO Lei3, CHEN Zhong4
Received:
2021-06-28
Revised:
2022-04-08
Online:
2022-12-25
Published:
2023-02-03
CLC Number:
LIU Jiangtao, YAN Qiaona, ZHOU Tao, SHAO Lei, CHEN Zhong. Load Forecasting of Metro Power Supply System Based on Deep Recurrent Neural Network[J]. Journal of Electrical Engineering, 2022, 17(4): 309-317.
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[1] | 龚孟荣. 地铁供电系统设计及仿真研究[D]. 成都: 西南交通大学, 2013. |
GONG Mengrong. Design and simulation of metro power supply system[D]. Chengdu: Southwest Jiaotong University, 2013. | |
[2] | 李家旭. 地铁车站负荷计算方法的探讨[J]. 科技创新与应用, 2017(20):77-78. |
LI Jiaxu. Discussion on the load calculation method of metro station[J]. Science and Technology Innovation and Application, 2017(20):77-78. | |
[3] | 崔洪敏, 刘炜, 李鲲鹏, 等. 城市轨道交通牵引变电所负荷过程及概率特性研究[J]. 城市轨道交通研究, 2019, 22(7):33-37. |
CUI Hongmin, LIU Wei, LI Kunpeng, et al. Study on load process and probability characteristics of traction substation of urban rail transit[J]. Urban Rail Transit Research, 2019, 22(7):33-37. | |
[4] | 徐舒. 南京地铁牵引供电系统负荷建模与仿真及其对电网影响分析[D]. 南京: 东南大学, 2006. |
XU Shu. Load modeling and simulation of traction power supply system in Nanjing metro and analysis of its influence on power grid[D]. Nanjing: Southeast University, 2006. | |
[5] | FAN G F, PENG L L, HONG W C. Short term load forecasting based on phase space reconstruction algorithm and bi-square kernel regression model[J]. Applied Energy, 2018(34):224-232. |
[6] | ZHANG J L, WEI Y M, LI D Z, et al. Short term electricity load forecasting using a hybrid model[J]. Energy, 2018(46):158-167. |
[7] | 彭鹏, 彭佳红. 基于多元线性回归模型的电力负荷预测研究[J]. 中国安全生产科学技术, 2011, 7(9):158-161. |
PENG Peng, PENG Jiahong. Research on the prediction of power load based on multiple linear regression model[J]. Journal of Safety Science and Technology, 2011, 7(9):158-161. | |
[8] | 张俊芳, 吴伊昂, 吴军基. 基于灰色理论负荷预测的应用研究[J]. 电力自动化设备, 2004(5):24-27. |
ZHANG Junfang, WU Yiang, WU Junji. Application of gray system theory in load forecasting[J]. Electric Power Automation Equipment, 2004(5):24-27. | |
[9] | 黄伟, 费维刚, 王炳革, 等. 模糊理论在中长期负荷预测中的应用[J]. 电力系统及其自动化学报, 1999(4):25-29. |
HUANG Wei, FEI Weigang, WANG Bingge, et al. The application and medium of fuzzy theory in the long term load forecasting[J]. Proceedings of the CSU-EPSA, 1999(4):25-29. | |
[10] | 王新, 孟玲玲. 基于EEMD-LSSVM的超短期负荷预测[J]. 电力系统保护与控制, 2015, 43(1):61-66. |
WANG Xin, MENG Lingling. Super-short-term load prediction based on EEMD-LSSVM[J]. Power System Protection and Control, 2015, 43(1):61-66. | |
[11] |
张刚, 刘福潮, 王维洲, 等. 电网短期负荷预测的BP-ANN方法及应用[J]. 电力建设, 2014, 35(3):54-58.
doi: 10.3969/j.issn.1000-7229.2014.03.010 |
ZHANG Gang, LIU Fuchao, WANG Weizhou, et al. BP-ANN method and its application for short-term load prediction of power grid[J]. Electric Power Construction, 2014, 35(3):54-58.
doi: 10.3969/j.issn.1000-7229.2014.03.010 |
|
[12] | 吴元香. 基于遗传算法的电力负荷预测[J]. 科技信息, 2013(6):472. |
WU Yuanxiang. Power load prediction based on genetic algorithm[J]. Science and Technology Information, 2013(6):472. | |
[13] |
BASHIR Z A, EL-HAWARY M E. Applying wavelets to short-term load forecasting using PSO-based neural networks[J]. IEEE Transactions on Power Systems, 2009, 24(1):20-27.
doi: 10.1109/TPWRS.2008.2008606 |
[14] | 宋晓辉, 白晓民, 易俗. 一种考虑负荷特性变化的改进线性回归负荷预测法[J]. 供用电, 2006(1):23-26. |
SONG Xiaohui, BAI Xiaomin, YI Su. An improved linear regression load prediction method considering the variation of load characteristics[J]. Power Supply and Consumption, 2006(1):23-26. | |
[15] | 马婉贞, 杜斌. 基于改进灰色理论的中长期负荷预测方法研究[J]. 智能城市, 2019, 5(23):20-21. |
MA Wanzhen, DU Bin. Research on medium and long term load forecasting method based on improved grey theory[J]. Smart City, 2019, 5(23):20-21. | |
[16] | 陈志巧. 基于模糊理论的电力负荷预测研究[J]. 山东科技大学学报, 2006(2):81-83. |
CHEN Zhiqiao. Research on power load prediction based on fuzzy theory[J]. Journal of Shandong University of Science and Technology, 2006(2):81-83. | |
[17] | 杨治中. 地铁供电系统安装工程的施工管理[J]. 集成电路应用, 2020, 37(11):176-177. |
YANG Zhizhong. Construction management of subway power supply system installation project[J]. Integrated Circuit Application, 2020, 37(11):176-177. | |
[18] | 孟新心. 轨道交通供电系统智能运维平台研究与应用[J]. 电气化铁道, 2020, 31(S1):94-96. |
MENG Xinxin. Research and application of intelligent operation and maintenance platform for rail transit power supply system[J]. Electric Railway, 2020, 31(S1):94-96. | |
[19] | 于松伟, 杨兴山. 城市轨道交通供电系统设计原理与应用[M]. 成都: 西南交通大学出版社, 2008. |
YU Songwei, YANG Xingshan. Design principle and application of urban rail transportation power supply system[M]. Chengdu: Southwest Jiaotong University Press, 2008. | |
[20] | 欧阳慧林. 城市轨道交通供电方案研究[J]. 广东输电与变电技术, 2009, 11(5):64-67. |
OUYANG Huilin. Study on power supply scheme of urban rail transit[J]. Guangdong Power Transmission and Transformation Technology, 2009, 11(5):64-67. | |
[21] | 杨亚兵. 地铁供电系统中的并行送电技术探讨[J]. 智能城市, 2020, 6(13):73-74. |
YANG Yabing. Discussion on parallel power transmission technology in metro power supply system[J]. Smart City, 2020, 6(13):73-74. | |
[22] | 谭丽娜, 白冰. 城市轨道交通供电系统浅析[J]. 教育教学论坛, 2012(36):190-191. |
TAN Lina, BAI Bing. Analysis of power supply system of urban rail transit[J]. Education and Teaching Forum, 2012(36):190-191. | |
[23] | 黄胜德, 张巍. 地下铁道供电[M]. 北京: 中国电力出版社, 2009. |
HUANG Shengde, ZHANG Wei. Underground railway power supply[M]. Beijing: China Electric Power Press, 2009. | |
[24] | 李光蕊. 北京地铁负荷建模及其对城市配电网影响的分析[D]. 北京: 北京交通大学, 2015. |
LI Guangrui. Modeling of metro load in Beijing and its impact on urban distribution network[D]. Beijing: Beijing Jiaotong University, 2015. | |
[25] | 张惠茹, 贾利民, 王莉, 等. 面向列车节能控制的时刻表优化[J]. 铁道学报, 2019, 41(2):8-15. |
ZHANG Huiru, JIA Limin, WANG Li, et al. Study of timetable optimization based on train enemy saving control[J]. Journal of the China Railway Society, 2019, 41(2):8-15. | |
[26] | 胡海涛, 郑政, 何正友, 等. 交通能源互联网体系架构及关键技术[J]. 中国电机工程学报, 2018, 38(1):12-24,339. |
HU Haitao, ZHENG Zheng, HE Zhengyou, et al. Transportation and energy Internet architecture and key technologies[J]. Proceedings of the CSEE, 2018, 38(1):12-24,339. | |
[27] | 常金蓉. 轨道交通供电系统牵引负荷建模及其电能质量评估方法[D]. 兰州: 兰州理工大学, 2020. |
CHANG Jinrong. Traction load modeling and power quality evaluation method of rail transit power supply system[D]. Lanzhou: Lanzhou University of Technology, 2020. | |
[28] |
ZHANG Zehan, JIANG Teng, LI Shuanghong, et al. Automated feature learning for nonlinear process monitoring:An approach using stacked denoising autoencoder and k-nearest neighbor rule[J]. Journal of Process Control, 2018, 64:49-61.
doi: 10.1016/j.jprocont.2018.02.004 |
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