采用变分模态分解的微型燃气轮机发电系统混合储能功率分配策略

李月明; 丁泽民; 余又红; 刘永葆

doi:10.7652/xjtuxb202310018

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采用变分模态分解的微型燃气轮机发电系统混合储能功率分配策略

—————————————————————— | 更新时间：2025-05-08

- 采用变分模态分解的微型燃气轮机发电系统混合储能功率分配策略
- Hybrid Energy Storage Power Distribution Strategy for Micro Gas Turbine Power Generation System Based on Variational Mode Decomposition
- 西安交通大学学报 2023年57卷第10期页码：183-195
- 作者机构：
  
  海军工程大学动力工程学院,武汉,430033
- 作者简介：
  
  : 2023-03-16。作者简介: 李月明(1996—),男,硕士生
  丁泽民(通信作者),男,讲师,硕士生导师。基金项目: 国家科技重大专项资助项目(J2019-Ⅰ-0012-0012)。
- 基金信息：
  
  : 2023-03-16。作者简介: 李月明(1996—),男,硕士生;丁泽民(通信作者),男,讲师,硕士生导师。基金项目: 国家科技重大专项资助项目(J2019-Ⅰ-0012-0012)。
- DOI：10.7652/xjtuxb202310018
  中图分类号： U665.12
- 网络首发：2023-10-10，
  
  纸质出版：2023
- 稿件说明：
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李月明, 丁泽民, 余又红, 等. 采用变分模态分解的微型燃气轮机发电系统混合储能功率分配策略[J]. 西安交通大学学报, 2023,57(10):183-195.

LI Yueming, DING Zemin, YU Youhong, et al. Hybrid Energy Storage Power Distribution Strategy for Micro Gas Turbine Power Generation System Based on Variational Mode Decomposition[J]. 2023, 57(10): 183-195.
李月明, 丁泽民, 余又红, 等. 采用变分模态分解的微型燃气轮机发电系统混合储能功率分配策略[J]. 西安交通大学学报, 2023,57(10):183-195. DOI： 10.7652/xjtuxb202310018.

LI Yueming, DING Zemin, YU Youhong, et al. Hybrid Energy Storage Power Distribution Strategy for Micro Gas Turbine Power Generation System Based on Variational Mode Decomposition[J]. 2023, 57(10): 183-195. DOI： 10.7652/xjtuxb202310018.

摘要

为缓解大功率脉冲负载投切造成的船舶燃气轮机发电系统功率波动

将由飞轮储能装置和蓄电池组成的混合储能系统应用于船舶燃气轮机发电系统

提出一种采用变分模态分解(VMD)和模糊控制策略的船舶微型燃气轮机发电系统混合储能功率分配策略。基于算术优化算法优化的变分模态分解(AOA-VMD)

实现混合储能系统中飞轮储能和蓄电池功率的初级分配; 考虑飞轮储能转速和蓄电池荷电状态安全运行范围

设计两个并列的模糊控制器

调节飞轮储能和蓄电池的初级功率

实现飞轮储能和蓄电池功率的二次分配。建立包括燃气轮机、发电机、混合储能系统和脉冲功率负载的船舶微型燃气轮机发电系统模型并开展性能仿真。结果表明

考虑混合储能后

脉冲负载投切所造成的直流母线电压最大波动减小了6.4%

对应的微燃机转速最大变化率减小了0.02%。对比采用传统滤波器和未经优化VMD的算法

采用AOA-VMD算法分解脉冲负载的功率波动信号:投入峰值功率为40 kW的脉冲功率负载时

直流母线电压波动量分别减小3 V和2.4 V

对应的微燃机转速波动率分别减小0.012%和0.014%; 切除上述负载时

电压分别减小2.7 V和0.6 V

转速波动率分别减小0.018%和0.012%。仿真结果验证了所提采用变分模态分解的混合储能功率分配策略的有效性与优越性。

Abstract

To mitigate power fluctuations caused by high-power pulse load switching in ship gas turbine power generation systems

this research proposes a hybrid energy storage power allocation strategy for ship micro gas turbine power generation systems. The strategy involves the application of a hybrid energy storage system composed of flywheel energy storage devices and batteries. It incorporates variational mode decomposition(VMD)and fuzzy control strategy. The primary allocation of flywheel energy storage and batteries in the hybrid system is achieved using arithmetic optimization algorithm-based optimized variational mode decomposition(AOA-VMD). Two parallel fuzzy controllers are designed to regulate flywheel energy storage and battery primary power

considering the safe operation ranges of flywheel energy storage speed and battery state of charge. This shipboard micro gas turbine power generation system model

including gas turbine

generator

hybrid energy storage system

and pulse power load

is established for performance simulation. The results indicate that incorporating hybrid energy storage reduces the maximum fluctuation in DC bus voltage caused by pulse load switching by 6.4%

with a corresponding decrease of 0.02% in maximum change rate of micro gas turbine speed. When compared to traditional filter and unoptimized VMD algorithms

applying the AOA-VMD algorithm for power fluctuation signal decomposition reduces DC bus voltage fluctuation by 3 V and 2.4 V

respectively

when subjected to a peak power pulse load of 40 kW. The associated micro gas turbine speed fluctuation rates decrease by 0.012% and 0.014%. When the aforementioned load is removed

voltage reduction is observed at 2.7 V and 0.6 V respectively

with corresponding speed fluctuation rate reductions of 0.018% and 0.012%. Through simulation

proof of the effectiveness and superiority of the proposed hybrid energy storage power allocation strategy based on variational mode decomposition is affirmed.

关键词

Keywords

references

DOERRY N, AMY J, KROLICK C. History and the status of electric ship propulsion, integrated power systems, and future trends in the U.S. Navy [J]. Proceedings of the IEEE, 2015, 103(12): 2243-2251.

ALAFNAN H, ZHANG Min, YUAN Weijia, et al. Stability improvement of DC power systems in an all-electric ship using hybrid SMES/battery [J]. IEEE Transactions on Applied Superconductivity, 2018, 28(3): 1-6.

FADDEL S, SAAD A A, YOUSSEF T, et al. Decentralized control algorithm for the hybrid energy storage of shipboard power system [J]. IEEE Journal of Emerging and Selected Topics in Power Electronics, 2020, 8(1): 720-731.

ZHOU Zhibin, BENBOUZID M, FRÉDÉRIC CHARPENTIER J, et al. A review of energy storage technologies for marine current energy systems [J]. Renewable and Sustainable Energy Reviews, 2013, 18: 390-400.

AL SHAQSI A Z, SOPIAN K, AL-HINAI A. Review of energy storage services, applications, limitations, and benefits [J]. Energy Reports, 2020, 6(S7): 288-306.

吴海峰, 鲁军勇, 马伟明, 等. 大功率混合储能装置控制策略研究 [J]. 西安交通大学学报, 2015, 49(2): 93-98.

WU Haifeng, LU Junyong, MA Weiming, et al. Control strategy for high power hybrid energy storage device [J]. Journal of Xi'an Jiaotong University, 2015, 49(2): 93-98.

MOUSAVI G S M, FARAJI F, MAJAZI A, et al. A comprehensive review of flywheel energy storage system technology [J]. Renewable and Sustainable Energy Reviews, 2017, 67: 477-490.

SHARMA P, KUMAR V. Current technology of supercapacitors: a review [J]. Journal of Electronic Materials, 2020, 49(6): 3520-3532.

涂伟超, 李文艳, 张强, 等. 飞轮储能在电力系统的工程应用 [J]. 储能科学与技术, 2020, 9(3): 869-877.

TU Weichao, LI Wenyan, ZHANG Qiang, et al. Engineering application of flywheel energy storage in power system [J]. Energy Storage Science and Technology, 2020, 9(3): 869-877.

SEBASTIÁN R, PEÑA ALZOLA R. Flywheel energy storage systems: review and simulation for an isolated wind power system [J]. Renewable and Sustainable Energy Reviews, 2012, 16(9): 6803-6813.

YAO Jun, YU Mengting, GAO Wenzhong, et al. Frequency regulation control strategy for PMSG wind-power generation system with flywheel energy storage unit [J]. IET Renewable Power Generation, 2017, 11(8): 1082-1093.

李红, 储江伟, 袁善坤. 车用电磁耦合式飞轮储能装置的性能 [J]. 华南理工大学学报(自然科学版), 2020, 48(6): 50-57.

LI Hong, CHU Jiangwei, YUAN Shankun. Performance of vehicle electromagnetic coupling flywheel energy storage device [J]. Journal of South China University of Technology(Natural Science Edition), 2020, 48(6): 50-57.

HUTCHINSON A, GLADWIN D T. Optimisation of a wind power site through utilisation of flywheel energy storage technology [J]. Energy Reports, 2020, 6(S5): 259-265.

KULKARNI S, SANTOSO S. Impact of pulse loads on electric ship power system: with and without flywheel energy storage systems [C]//2009 IEEE Electric Ship Technologies Symposium. Piscataway, NJ, USA: IEEE, 2009: 568-573.

LI Yueming, DING Zemin, YU Youhong, et al. Mitigation effect of flywheel energy storage on the performance of marine gas turbine DC microgrid under high-power load mutation [J]. Energy Reports, 2023, 9: 1380-1396.

HOU Jun, SONG Ziyou, HOFMANN H F, et al. Control strategy for battery/flywheel hybrid energy storage in electric shipboard microgrids [J]. IEEE Transactions on Industrial Informatics, 2021, 17(2): 1089-1099.

BARELLI L, BIDINI G, CIUPAGEANU D A, et al. Real time power management strategy for hybrid energy storage systems coupled with variable energy sources in power smoothing applications [J]. Energy Reports, 2021, 7: 2872-2882.

林舜江, 杨智斌, 卢苑, 等. 含光伏的天然气冷热电联供园区微网能量优化调度 [J]. 华南理工大学学报(自然科学版), 2019, 47(3): 9-19.

LIN Shunjiang, YANG Zhibin, LU Yuan, et al. Optimal energy scheduling of photovoltaic natural gas, cooling, heating and power co-supply park micro-network [J]. Journal of South China University of Technology(Natural Science Edition), 2019, 47(3): 9-19.

HOU Jun, SUN Jing, HOFMANN H. Control development and performance evaluation for battery/flywheel hybrid energy storage solutions to mitigate load fluctuations in all-electric ship propulsion systems [J]. Applied Energy, 2018, 212: 919-930.

HOU Jun, SONG Ziyou, HOFMANN H, et al. Adaptive model predictive control for hybrid energy storage energy management in all-electric ship microgrids [J]. Energy Conversion and Management, 2019, 198: 111929.

张宇涵, 杜贵平, 雷雁雄, 等. 直流微网混合储能系统控制策略现状及展望 [J]. 电力系统保护与控制, 2021, 49(3): 177-187.

ZHANG Yuhan, DU Guiping, LEI Yanxiong, et al. Current status and prospects of control strategy for a DC micro grid hybrid energy storage system [J]. Power System Protection and Control, 2021, 49(3): 177-187.

续丹, 周佳辉, 王斌, 等. 电动汽车混合储能系统的自适应协同控制 [J]. 西安交通大学学报, 2019, 53(4): 38-43, 57.

XU Dan, ZHOU Jiahui, WANG Bin, et al. An adaptive synergetic control strategy for hybrid energy storage system of electric vehicles [J]. Journal of Xi'an Jiaotong University, 2019, 53(4): 38-43, 57.

刘颖明, 王维, 王晓东, 等. 基于飞轮-蓄电池混合储能的风电功率平滑控制 [J]. 电器与能效管理技术, 2017(13): 22-27.

LIU Yingming, WANG Wei, WANG Xiaodong, et al. Wind power smoothing control based on flywheel battery hybrid energy storage [J]. Electrical Energy Management Technology, 2017(13): 22-27.

曹冰玉. 基于直流微网的混合储能系统控制策略研究 [D]. 石河子: 石河子大学, 2021.

李洋, 陈洁, 王小军, 等. 微电网中混合储能双层模糊控制优化策略 [J]. 计算机仿真, 2022, 39(6): 103-107, 398.

LI Yang, CHEN Jie, WANG Xiaojun, et al. Double layer fuzzy control optimization strategy for hybrid energy storage in microgrid [J]. Computer Simulation, 2022, 39(6): 103-107, 398.

熊雄, 王江波, 杨仁刚, 等. 微电网中混合储能模糊自适应控制策略 [J]. 电网技术, 2015, 39(3): 677-681.

XIONG Xiong, WANG Jiangbo, YANG Rengang, et al. A fuzzy adaptive control strategy for composite energy storage system to cope with output power fluctuation of intermittent energy source in microgrid [J]. Power System Technology, 2015, 39(3): 677-681.

付菊霞, 陈洁, 滕扬新, 等. 基于集合经验模态分解的风电混合储能系统能量管理协调控制策略 [J]. 电工技术学报, 2019, 34(10): 2038-2046.

FU Juxia, CHEN Jie, TENG Yangxin, et al. Energy management coordination control strategy for wind power hybrid energy storage system based on EEMD [J]. Transactions of China Electrotechnical Society,2019, 34(10): 2038-2046.

YUAN Yue, SUN Chengchen, LI Mengting, et al. Determination of optimal supercapacitor-lead-acid battery energy storage capacity for smoothing wind power using empirical mode decomposition and neural network [J]. Electric Power Systems Research, 2015, 127: 323-331.

高晓芝, 王磊, 田晋, 等. 基于参数优化变分模态分解的混合储能功率分配策略 [J]. 储能科学与技术, 2022, 11(1): 147-155.

GAO Xiaozhi, WANG Lei, TIAN Jin, et al. Research on hybrid energy storage power distribution strategy based on parameter optimization variational mode decomposition [J]. Energy Storage Science and Technology, 2022, 11(1): 147-155.

杜佳耘, 雷勇, 李永凯, 等. 基于参数优化变分模态分解的混合储能功率分配策略 [J]. 现代电力, 2021, 38(1): 51-59.

DU Jiayun, LEI Yong, LI Yongkai, et al. Hybrid energy storage strategy based on parameter optimized variational mode decomposition [J]. Modern Electric Power, 2021, 38(1): 51-59.

DRAGOMIRETSKIY K, ZOSSO D. Variational mode decomposition [J]. IEEE Transactions on Signal Processing, 2014, 62(3): 531-544.

朱永利, 贾亚飞, 王刘旺, 等. 基于改进变分模态分解和Hilbert变换的变压器局部放电信号特征提取及分类 [J]. 电工技术学报, 2017, 32(9): 221-235.

ZHU Yongli, JIA Yafei, WANG Liuwang, et al. Feature extraction and classification on partial discharge signals of power transformers based on improved variational mode decomposition and Hilbert transform [J]. Transactions of China Electrotechnical Society, 2017, 32(9): 221-235.

ZHANG Yagang, ZHAO Yuan, KONG Chunhui, et al. A new prediction method based on VMD-PRBF-ARMA-E model considering wind speed characteristic [J]. Energy Conversion and Management, 2020, 203: 112254.

XIAO Gang, XU Fen, TONG Lianghuai, et al. A hybrid energy storage system based on self-adaptive variational mode decomposition to smooth photovoltaic power fluctuation [J]. Journal of Energy Storage, 2022, 55(Part B): 105509.

ABUALIGAH L, DIABAT A, MIRJALILI S, et al. The arithmetic optimization algorithm [J]. Computer Methods in Applied Mechanics and Engineering, 2021, 376: 113609.

DUAN Jiandong, FAN Shaogui, AN Quntao, et al. A comparison of micro gas turbine operation modes for optimal efficiency based on a nonlinear model [J]. Energy, 2017, 134: 400-411.

LIN Ping, DU Xian, SHI Yan, et al. Modeling and controller design of a micro gas turbine for power generation [J]. ISA Transactions, 2020, 124: 411-426.

曾维伦, 王旭升, 吕小静, 等. 基于模糊PID的微型燃气轮机发电机组控制性能研究 [J]. 热能动力工程, 2021, 36(10): 212-221.

ZENG Weilun, WANG Xusheng, LV Xiaojing, et al. Research on control performance of micro gas turbine generator set based on fuzzy PID [J]. Journal of Engineering for Thermal Energy and Power, 2021, 36(10): 212-221.

SHINTAI T, MIURA Y, ISE T. Oscillation damping of a distributed generator using a virtual synchronous generator [J]. IEEE Transactions on Power Delivery, 2014, 29(2): 668-676.

ABOSH A H, ZHU Z Q, REN Yuan. Reduction of torque and flux ripples in space vector Modulation-Based direct torque control of asymmetric permanent magnet synchronous machine [J]. IEEE Transactions on Power Electronics, 2017, 32(4): 2976-2986.

SALEHI V, MIRAFZAL B, MOHAMMED O. Pulse-load effects on ship power system stability [C]//IECON 2010-36th Annual Conference on IEEE Industrial Electronics Society. Piscataway, NJ, USA: IEEE, 2010: 3353-3358.

XIE Rui, CHEN Ying, WANG Zhaojian, et al. Online periodic coordination of multiple pulsed loads on all-electric ships [J]. IEEE Transactions on Power Systems, 2020, 35(4): 2658-2669.

LASHWAY C R, ELSAYED A T, MOHAMMED O A. Hybrid energy storage management in ship power systems with multiple pulsed loads [J]. Electric Power Systems Research, 2016, 141: 50-62.

LIAN Jijian, LIU Zhuo, WANG Haijun, et al. Adaptive variational mode decomposition method for signal processing based on mode characteristic [J]. Mechanical Systems and Signal Processing, 2018, 107: 53-77.

ECKERT J J, DE ALKMIN SILVA L C, DEDINI F G, et al. Electric vehicle powertrain and fuzzy control multi-objective optimization, considering dual hybrid energy storage systems [J]. IEEE Transactions on Vehicular Technology, 2020, 69(4): 3773-3782.

SHEN Yongpeng, LI Yuanfeng, TANG Yaohua, et al. An energy management strategy based on fuzzy logic for hybrid energy storage system in electric vehicles [J]. IEEJ Transactions on Electrical and Electronic Engineering, 2022, 17(1): 53-60.

邵梦麟, 梁前超, 闫东, 等. 船用燃气轮机发电机组动态性能仿真 [J]. 舰船科学技术, 2016, 38(4): 71-76.

SHAO Menglin, LIANG Qianchao, YAN Dong, et al. Simulation on dynamic performance of gas turbine-generator set for ships [J]. Ship Science and Technology, 2016, 38(4): 71-76.

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