MMC-RPC的多维泰勒网优化控制策略

宋平岗; 魏文龙; 陈紫君; 陈子豪

doi:10.13890/j.issn.1000-128X.2023.02.014

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MMC-RPC的多维泰勒网优化控制策略

电力牵引与控制 | 更新时间：2024-08-02

- MMC-RPC的多维泰勒网优化控制策略
- Multi-dimensional Taylor network optimal control strategy of MMC-RPC
- 机车电传动 2023年第2期页码：123-130
- 作者机构：
  
  华东交通大学电气与自动化工程学院，江西南昌 330013
- 作者简介：
  
  魏文龙（1997—），男，硕士研究生，主要从事高压直流输电方面的研究；E-mail: 15797790760@163.com
- 基金信息：
  
  国家自然科学基金项目(51367008)
- DOI：10.13890/j.issn.1000-128X.2023.02.014
  中图分类号： U223.5
- 纸质出版日期：2023-03-10，
  
  收稿日期：2022-07-16，
- 稿件说明：
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宋平岗, 魏文龙, 陈紫君, 等. MMC-RPC的多维泰勒网优化控制策略[J]. 机车电传动, 2023(2): 123-130.

SONG Pinggang, WEI Wenlong, CHEN Zijun, et al. Multi-dimensional Taylor network optimal control strategy of MMC-RPC[J]. Electric Drive for Locomotives,2023(2): 123-130.
宋平岗, 魏文龙, 陈紫君, 等. MMC-RPC的多维泰勒网优化控制策略[J]. 机车电传动, 2023(2): 123-130. DOI： 10.13890/j.issn.1000-128X.2023.02.014.

SONG Pinggang, WEI Wenlong, CHEN Zijun, et al. Multi-dimensional Taylor network optimal control strategy of MMC-RPC[J]. Electric Drive for Locomotives,2023(2): 123-130. DOI： 10.13890/j.issn.1000-128X.2023.02.014.

摘要

为进一步解决铁路牵引供电系统中无功功率、负序电流和谐波失真率高等对电能质量的影响，将多维泰勒网（Multi-dimensional Taylor Network

MTN）优化控制应用于与模块化多电平换流器结合的铁路功率调节器（Railway Power Conditioner with Modular Multilevel Converter

MMC-RPC）。相比传统双闭环PI控制器，多维泰勒网控制器的优点在于抗扰动能力更强、鲁棒性更好和谐波失真率更低等。针对参数整定问题，将

轴电流参考值与实际值之间误差平方的积分作为输出性能指标，并运用粒子群算法对MTN当中的参数进行优化。在MATLAB/Simulink软件中分别搭建了MMC-RPC采用MTN控制器和PI控制器的仿真模型，对电气化铁路中常见的一侧供电臂有机车负载和负载突变2种常见工况进行对比，验证了MTN控制器在MMC-RPC中的可行性和优越性。

Abstract

In order to solve the influence of high reactive power

negative sequence current and harmonic distortion rate on power quality in railway traction power supply system

multi-dimensional Taylor network optimization control was applied to railway power conditioner with modular multilevel converter (MMC-RPC). Compared with traditional double closed-loop PI controller

multi-dimensional Taylor network (MTN) controller has advantages of strong anti-disturbance ability

better robustness and lower harmonic distortion rate. Aiming at the parameter setting problem

the integral of the error square between the reference value and the actual value of the

axis current was used as the output performance index

and the particle swarm optimization algorithm was used to optimize the parameters in MTN. In MATLAB/Simulink

the simulation models of MMC-RPC using MTN controller and PI controller were built respectively

and the two common working conditions of loc

omotive load and load mutation were compared in electrified railway

which verified the effectiveness and superiority of MTN controller in MMC-RPC.

关键词

铁路功率调节器模块化多电平换流器多维泰勒网控制器粒子群算法

Keywords

railway static power conditionermodular multilevel convertermulti-dimensional Taylor network controllerparticle swarm optimization

references

ROUDSARI H M, JALILIAN A, JAMALI S. Flexible fractional compensating mode for railway static power conditioner in a V/v traction power supply system[J]. IEEE Transactions on Industrial Electronics, 2018, 65(10): 7963-7974.

邓文丽, 戴朝华, 陈维荣, 等. 铁路功率调节器研究进展[J]. 中国电机工程学报, 2020, 40(14): 4640-4655.

DENG Wenli, DAI Chaohua, CHEN Weirong, et al. Research progress of railway power conditioner[J]. Proceedings of the CSEE, 2020, 40(14): 4640-4655.

ALHARBI M, ISIK S, BHATTACHARYA S. Reliability comparison and evaluation of MMC based HVDC systems[C]//IEEE. 2018 IEEE Electronic Power Grid. Charleston: IEEE, 2018: 1-5.

FREYTES J, AKKARI S, RAULT P. Dynamic analysis of MMC-based MTDC grids: use of MMC energy to improve voltage behavior[J]. IEEE Transactions on Power Delivery, 2019, 34(1): 137-148.

宋平岗, 周振邦, 林家通, 等. 基于微分平坦理论的MMC-RPC控制器设计[J]. 机车电传动, 2017(3): 14-19.

SONG Pinggang, ZHOU Zhenbang, LIN Jiatong, et al. Design of controller for MMC-RPC based on differential flatness control theory[J]. Electric Drive for Locomotives, 2017(3): 14-19.

ZHANG Dinghua, ZHANG Zhixue, WANG Weian, et al. Negative sequence current optimizing control based on railway static power conditioner in V/v traction power supply system[J]. IEEE Transactions on Power Electronics, 2016, 31(1): 200-212.

MA Fujun, ZHU Zhen, MIN Jun, et al. Model analysis and sliding mode current controller for multilevel railway power conditioner under the V/v traction system[J]. IEEE Transactions on Power Electronics, 2019, 34(2): 1243-1253.

李晨龙, 严洪森. 基于多维泰勒网的超前d步预测模型[J]. 控制与决策, 2021, 36(2): 345-354.

LI Chenlong, YAN Hongsen. d-step-ahead predictive model based on multi-dimensional Taylor network[J]. Control and Decision, 2021, 36(2): 345-354.

张超, 严洪森. 永磁同步电机调速系统的多维泰勒网逆控制[J]. 控制与决策, 2019, 34(10): 2085-2094.

ZHANG Chao, YAN Hongsen. Multi-dimensional Taylor network inverse control of speed variable system for permanent magnet synchronous motor[J]. Control and Decision, 2019, 34(10): 2085-2094.

LI Chenlong, YAN Hongsen. Identification of nonlinear time-delay system using multi-dimensional Taylor network model[C]//IEEE. 2018 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale. Hangzhou: IEEE, 2018: 87-90.

SUN Qiming, ZHANG Chao, JIANG Nanyun, et al. Data-driven nonlinear near-optimal regulation based on multi-dimensional Taylor network dynamic programming[J]. IEEE Access, 2020, 8: 36476-36484.

朱琳, 蒋毅, 佟来生, 等. 基于多维泰勒网优化控制的悬浮控制方法研究[J]. 机车电传动, 2020(6): 85-87.

ZHU Lin, JIANG Yi, TONG Laisheng, et al. Study on levitation control method based on multi-dimensional Taylor network optimal control[J]. Electric Drive for Locomotives, 2020(6): 85-87.

周小杰, 阮毅, 汪飞. 单相并网变换器预测直接功率控制策略研究[J]. 中国电机工程学报, 2014, 34(30): 5269-5276.

ZHOU Xiaojie, RUAN Yi, WANG Fei. A predictive direct power control scheme for single-phase grid-connected converters[J]. Proceedings of the CSEE, 2014, 34(30): 5269-5276.

XU Wei, ISMAIL M M, LIU Yi, et al. Parameter optimization of adaptive flux-weakening strategy for permanent-magnet synchronous motor drives based on particle swarm algorithm[J]. IEEE Transactions on Power Electronics, 2019, 34(12): 12128-12140.

YANG Zebin, LU Chengling, SUN Xiaodong, et al. Study on active disturbance rejection control of a bearingless induction motor based on an improved particle swarm optimization-genetic algorithm[J]. IEEE Transactions on Transportation Electrification, 2021, 7(2): 694-705.

魏立新, 王浩, 穆晓伟. 基于粒子群算法倒立摆分数阶PID 参数优化[J]. 控制工程, 2019, 26(2): 196-201.

WEI Lixin, WANG Hao, MU Xiaowei. Control of revolving inverted pendulum based on PSO-FOPID controller[J]. Control Engineering of China, 2019, 26(2): 196-201.

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