Secondary frequency modulation control strategy of ship microgrid with model-free adaptive control

被引:0
|
作者
Yao W.-L. [1 ]
Pei C.-B. [1 ]
Chi R.-H. [1 ]
Shao W. [1 ]
Yan C.-Y. [1 ]
机构
[1] Institute of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao
关键词
model-free adaptive control; radial basis function neural network observer; secondary frequency modulation; ship load switching; ship micro-grid; virtual synchronous generator;
D O I
10.15938/j.emc.2023.03.013
中图分类号
学科分类号
摘要
Considering the frequency deviation in off-grid ship microgrid caused by load switching and the design of the secondary frequency modulation controller under complex sea condition disturbance, a second frequency modulation control strategy based on model-free adaptive control(MFAC) for ship microgrid was proposed. The rotor equation of virtual synchronous generator with ship load disturbance was discretized, and the discrete data model about the output angular frequency and the input setting value of virtual mechanical power was given by utilizing compact format dynamic linearization method, where the unknown load disturbance is merged into a nonlinear term. An MFAC controller was designed according to the data model, and a pseudo partial derivative estimation algorithm was given. The nonlinear term containing ship load disturbance was observed by the radial basis function neural network observer, by combining the model-free adaptive control, the control strategy of virtual synchronous generator was improved. The secondary frequency modulation control scheme of ship microgrid under ship load disturbance was presented. Finally, the corresponding simulation model was built to verify accuracy and effectiveness of the proposed control strategy. © 2023 Editorial Department of Electric Machines and Control. All rights reserved.
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页码:135 / 146
页数:11
相关论文
共 29 条
  • [1] LU Zhipeng, SHENG Wanxing, ZHONG Qingchang, Et al., Virtual synchronous generator and its application in microgrid, Proceedings of the CSEE, 34, 16, (2014)
  • [2] ZHONG Qingchang, Virtual synchronous machines and autonomous power systems, Proceedings of the CSEE, 37, 2, (2017)
  • [3] (2015)
  • [4] (2015)
  • [5] ZHU Qiangwei, LI Dongdong, LIN Shunfu, Et al., A self-adaptive inertia and damping combination control of VSG to support frequency stability [ J], IEEE Transactions on Energy Conversion, 32, 1, (2017)
  • [6] TENG Qi, XU Dezhi, YANG Weilin, Et al., Neural network-based integral sliding mode backstepping control for virtual synchronous generators[J], Energy Reports, 7, 3, (2021)
  • [7] CHEN Laijun, WANG Ren, ZHENG Tianwen, Et al., Optimal control of transient response of virtual synchronous generator based on adaptive parameter adjustment, Proceedings of the CSEE, 36, 21, (2016)
  • [8] CHAI Lun, LI Lan, LI Bing, Et al., Strategy of pre-synchronized grid-connection based on improving virtual synchronous generator, Renewable Energy, 37, 7, (2019)
  • [9] SAADATMAND S, SHAMSI P, FERDOWSI M., Adaptive critic design-based reinforcement learning approach in controlling virtual inertia-based grid-connected inverters[J], International Journal of Electrical Power & Energy Systems, 127, (2021)
  • [10] WANG Guoling, HE Fuqiao, LI Zhenyu, Et al., Phase-locked technique in new energy shipboard grid based on second-order generalized integrators [ J ], Electric Machines and Control, 24, 7, (2020)