收藏切换
Frequency Regulation Method for Electric Vehicles Cluster Based on Disturbance Observer and Robust Model Prediction
收藏切换
PDF
Huinan WANG, Yujin WANG
Journal of Power Supply | 2024, 22(5) : 220 - 229
Less
收藏切换
Journal of Power Supply | 2024, 22(5): 220-229
Power System
Frequency Regulation Method for Electric Vehicles Cluster Based on Disturbance Observer and Robust Model Prediction
Full
Huinan WANG, Yujin WANG
Affiliations
  • Marketing Service Center State Grid Shanxi Electric Power Company Taiyuan 030032 China
Published: 2024-09-30 doi: 10.13234/j.issn.2095-2805.2024.5.220
Outline
收藏切换

A frequency regulation method for a large number of electric vehicles (EVs) in an isolated grid with high permeability renewable energy sources is proposed. First, a disturbance observer is designed for the system's order reduction model to generate additional frequency control signals for clustered EVs. This order reduction model is obtained by combining the changes in load, wind power, photovoltaic system and clustered EVs, thus generating a lumped disturbance estimated by the disturbance observer. Second, a robust model predictive control method based on the Tube model is proposed to provide effective control signals to improve the responsiveness of clustered EVs. The control signals are generated to obtain the minimum frequency deviation error by means of the minimum control actions while considering various physical constraints on the system operation. Third, the influence of time delay on communication link is studied through the stability analysis, and the time delay margin is obtained. Finally, through simulation analysis, the effectiveness of the proposed method is verified, and the advantages of the proposed method over traditional model predictive control, fuzzy proportional integral control and linear quadratic regulator control are also verified.

Disturbance observer  /  electric vehicle(EV)  /  load frequency control  /  robust control
Huinan WANG, Yujin WANG. Frequency Regulation Method for Electric Vehicles Cluster Based on Disturbance Observer and Robust Model Prediction[J]. Journal of Power Supply, 2024 , 22 (5) : 220 -229 . DOI: 10.13234/j.issn.2095-2805.2024.5.220
  • State Grid Headquarters Science and Technology Project(5700-202055171A-0-0-00)
Year 2024 volume 22 Issue 5
PDF
307
119
Cite this Article
BibTeX
Article Info
doi: 10.13234/j.issn.2095-2805.2024.5.220
  • Receive Date:2021-06-17
  • Online Date:2025-07-20
  • Published:2024-09-30
Article Data
Affiliations
History
  • Received:2021-06-17
  • Revised:2021-08-13
  • Accepted:2021-08-27
Funding
State Grid Headquarters Science and Technology Project(5700-202055171A-0-0-00)
Affiliations
    Marketing Service Center State Grid Shanxi Electric Power Company Taiyuan 030032 China
References
Share
https://castjournals.cast.org.cn/joweb/dyxb/EN/10.13234/j.issn.2095-2805.2024.5.220
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT