PDF
(7180KB)
Abstract
An alternating current(AC) microgrid is a system that integrates renewable power, power converters, controllers and loads. Hierarchical control can manage the frequency of the microgrid to prevent imbalance and collapse of the system. The existing frequency control methods use traditional proportion integration(PI) controllers, which cannot adjust PI parameters in real-time to respond to the status changes of the system. Hierarchical control driven by fuzzy logic allows real-time adjustment of the PI parameters and the method used a two-layer control structure. The primary control used droop control to adjust power distribution, and fuzzy logic was used in the voltage loop of the primary control. The secondary control was added to make up for frequency deviation caused by droop control, and fuzzy logic was used in the secondary frequency control to deal with the dynamic change of frequency caused by the disturbances of loads. The proposed method was simulated in Matlab/Simulink. In the primary control, the proposed method reduced the total harmonic distortion(THD) of two cycles of the output voltage from 4.19% to 3.89%; in the secondary control, the proposed method reduced the frequency fluctuation of the system by about 0.03 Hz and 0.04 Hz when the load was increased and decreased, respectively. The results show that the proposed methods have a better effect on frequency maintenance and voltage control of the AC microgrid.
Keywords
fuzzy logic
/
hierarchical control
/
frequency regulation
/
droop control
/
alternating current (AC) microgrid
Cite this article
Download citation ▾
Xueyang WU, Yinghao SHAN, Bo SHEN.
Frequency Regulation of Alternating Current Microgrid Based on Hierarchical Control Using Fuzzy Logic.
Journal of Donghua University(English Edition), 2024, 41(5): 536-544 DOI:10.19884/j.1672-5220.202306004
| [1] |
MOHITI M, MONSEF H, ANVARI-MOGHADDAM A, et al. Two-stage robust optimization for resilient operation of microgrids considering hierarchical frequency control structure[J]. IEEE Transactions on Industrial Electronics, 2020, 67(11):9439-9449.
|
| [2] |
GONG C, JI H Q, DING Y F, et al. Research on distributed cooperative control strategy based on hierarchical control of microgrid[C]//Asia Power and Energy Engineering Conference (APEEC). New York: IEEE, 2019:191-198.
|
| [3] |
YIN Y T, DU D J, FEI M, et al. Overview of hierarchical control of AC and DC microgrid[C]//2021 IEEE International Conference on Recent Advances in Systems Science and Engineering (RASSE). New York: IEEE, 2021:1-9.
|
| [4] |
ADINEH B, KEYPOUR R, DAVARI P, et al. Review of harmonic mitigation methods in microgrid:from a hierarchical control perspective[J]. IEEE Journal of Emerging and Selected Topics in Power Electronics, 2021, 9(3):3044-3060.
|
| [5] |
KHONGKHACHAT S, KHOMFOI S. Hierarchical control strategies in AC microgrids[C]//2015 12th International Conference on Electrical Engineering/Electronics,Computer,Telecommunications and Information Technology (ECTI-CON). New York: IEEE, 2015:1-6.
|
| [6] |
GUAN Y J, VASQUEZ J C, GUERRERO J M. Hierarchical controlled grid-connected microgrid based on a novel autonomous current sharing controller[C]//2015 IEEE Energy Conversion Congress and Exposition (ECCE). New York: IEEE, 2015:2333-2340.
|
| [7] |
LI Z W, CHENG Z P, SI J K, et al. Distributed event-triggered hierarchical control of PV inverters to provide multi-time scale frequency response for AC microgrid[J]. IEEE Transactions on Power Systems, 2023, 38(2):1529-1542.
|
| [8] |
HEYDERI R, ALHASHEEM M, DRAGICEVIC T, et al. Model predictive control approach for distributed hierarchical control of VSC-based microgrids[C]//2018 20th European Conference on Power Electronics and Applications (EPE’18 ECCE Europe). New York: IEEE, 2018:1-8.
|
| [9] |
LIANG H F, DING J R, BIAN J, et al. Research on fuzzy droop control of DC microgrid based on consensus algorithm[C]//2020 4th International Conference on Smart Grid and Smart Cities (ICSGSC). New York: IEEE, 2020:76-82.
|
| [10] |
FU Y, ZHANG Z Q, MI Y, et al. Droop control for DC multi-microgrids based on local adaptive fuzzy approach and global power allocation correction[J]. IEEE Transactions on Smart Grid, 2019, 10(5):5468-5478.
|
| [11] |
SHAN Y H, HU J F, CHAN K W, et al. A unified model predictive voltage and current control for microgrids with distributed fuzzy cooperative secondary control[J]. IEEE Transactions on Industrial Informatics, 2021, 17(12):8024-8034.
|
| [12] |
CHOWDHURY A B K, LIANG X D, ZHANG H G. Fuzzy-secondary-controller-based virtual synchronous generator control scheme for interfacing inverters of renewable distributed generation in microgrids[J]. IEEE Transactions on Industry Applications, 2018, 54(2):1047-1061.
|
| [13] |
LONG B, LIAO Y, CHONG K T, et al. Enhancement of frequency regulation in AC microgrid:a fuzzy-MPC controlled virtual synchronous generator[J]. IEEE Transactions on Smart Grid, 2021, 12(4):3138-3149.
|
| [14] |
BAGHAEE H R, MIRSALIM M, GHAREHPETIAN G B. Performance improvement of multi-DER microgrid for small- and large-signal disturbances and nonlinear loads:novel complementary control loop and fuzzy controller in a hierarchical droop-based control scheme[J]. IEEE Systems Journal, 2018, 12(1):444-451.
|
| [15] |
NEVES R V A, MACHADO R Q, OLIVEIRA V A, et al. Multitask fuzzy secondary controller for AC microgrid operating in stand-alone and grid-tied mode[J]. IEEE Transactions on Smart Grid, 2019, 10(5):5640-5649.
|
| [16] |
JAFARI M, MALEKJAMSHIDI Z, ZHU J G, et al. A novel predictive fuzzy logic-based energy management system for grid-connected and off-grid operation of residential smart microgrids[J]. IEEE Journal of Emerging and Selected Topics in Power Electronics, 2020, 8(2):1391-1404.
|
| [17] |
CHEN K, ZHANG Y W, ZHANG Z, et al. Proportion integration differentiation (PID) control strategy of belt sander based on fuzzy algorithm[J]. Journal of Donghua University (English Edition), 2023, 40(2):177-184.
|
| [18] |
MAO J F, ZHANG X T, YIN C Y, et al. Multivariable coordinated nonlinear gain droop control for PV-battery hybrid DC microgrid access system via a T-S fuzzy decision approach[J]. IEEE Access, 2022, 10:89414-89427.
|
Funding
National Natural Science Foundation of China(62303107)
Fundamental Research Funds for the Central Universities,China(2232022G-09)
Fundamental Research Funds for the Central Universities,China(2232021D-38)
Shanghai Sailing Program, China(21YF1400100)